The classification of cancer chronic pain syndromes.
\r\n\tApplied and basic studies - Field studies and lab assays of fungicides can be discussed. We also look for examples of application methods, which may include timing of application, tools for application, fungicide compatibility, phytotoxicity, etc. Field trials have to have at least two years of data;
\r\n\tAdaptation of Integrated Plant Disease Management - How the IPM practice has been adapted in the field. Application of disease risk models, or use of fungicide application aids, which can be hardware or software. The introduction of a new tool for growers can also be included;
\r\n\tNovel fungicides - In addition to the traditional chemical approach, alternative materials (enzymes, oils, extracts, etc.), biological control agents, or plant defense activators can be discussed;
\r\n\tAdaptation of new technologies - Examples will be the use of unmanned vehicles, sensor technologies, advanced sprayers, or disease forecast systems for precision agriculture;
\r\n\tFungicide resistance - Unfortunately, we cannot ignore the fact that fungicide-resistant strains are widespread. Documentation of fungicide-resistant strains, the introduction of new technologies and methods can be discussed.
Cancer is diagnosed for more than 10 million people worldwide each year, and the illness of a malignant tumor is often associated with pain. The consequences of unrelieved cancer pain are devastating [1]. During the established diagnosis of cancer, the pain is present for 40% of tumor patients. The number increases up to 75–80% with the disease spread. About 4 million people in the world each day suffer from pain that comes due to oncological diseases, meaning that almost half of them do not receive proper treatment, and one-third live in severe or unbearable pain [2].
\nDespite increased attention on assessment and management, pain continues to be a prevalent symptom in patients with cancer. With reference to types of cancer, lower pain prevalence rates were demonstrated in prostate cancer compared to head and neck, lung, and breast cancer. Higher prevalence rates were seen in studies from Asia compared to Europe, in studies that used point or week prevalence rates compared to recall periods of a month or year [3].
\nOver the past few decades, we succeeded a better understanding of mechanisms underlying cancer pain, new developments achieved in pharmacologic cancer pain management, and increase in global opioid consumption becoming evident. Nevertheless, one-third of the patients worldwide still did not receive pain medication proportional to their pain intensity levels [4]. Data from Asia and North America revealed comparable prevalence rates, which imply that opioid availability alone is not an explanation for the high prevalence rates [3]. Even after implementation into clinical practice of rapid release opioids (ROOs), which provide faster relief than immediate-release preparations of other opioids, the prevalence of breakthrough pain is still 59% [5]. All these mean the importance of skilled use of opioid analgesics in the relief of cancer pain but also acknowledge the lack of evidence to support clinical practice and guidelines, which in turn causes recommendations in practice guidelines to be based on expert consensus.
\nIn 1986, the World Health Organization (WHO) has published a document entitled “A Declaration of the Rights of Patients with Chronic Cancer.” According to the WHO three-step analgesic ladder, in combination with appropriate dosage guidelines, pain relief should be adequate for 70–90% of patients. A systematic review on pain relief based on the WHO ladder, 20 years after its introduction, demonstrated adequate pain relief in 45–100% of patients [6, 7]. Among subjects of debates to improve the analgesic ladder the benefit of paracetamol (acetaminophen) with Step III opioids for which the evidence is “weak if any,” as well as the use of adjuvant analgesics for which outcomes are generally modest [8]. On the other hand, not only drugs are a guarantee of success in the cancer pain. It is widely accepted that a biopsychosocial approach in assessment and management is needed for treatment of pain in patients with cancer. Cicely Saunders elaborated on the concept of “total pain,” stating that pain is not purely a physical experience but involves various other components of human functioning including personality, mood, behavior, and social relations. A systematic review has identified an association between psychological distress, lack of social support, and cancer pain [9].
\nDifferent barriers have been acknowledged in relation to adequate pain management in patients with cancer. One of the most important reasons is lack of knowledge regarding the assessment and management of cancer pain. Health professionals are cautious when prescribing opioids because of fear of adverse effects, tolerance, and addiction. Otherwise, patients struggle with misconceptions about analgesic use, concerns about pain communication, and a belief that pain is inevitable and uncontrollable [10]. All reasons for the lack of adequate pain control are varied: (a) personal—fear of drug addiction, (b) legal issues by issuing a higher dose of these medicines, (c) material—with regard to the price and quantity of medicinal products, (d) organizational—regular supply and storage of medicines, (e) psychological—the conviction of the patient or his family members that narcotic analgesics can be used only in the last stages of the illness, (f) causes of medical staff in the absence of sufficient knowledge of analgesia and the principles for its administration, and (g) poor adherence to pain medication and poor pain relief, which appear to be more country-specific problems [11].
\nPain is an unpleasant sensory and emotional experience associated with actual or potential tissue damage, or described in terms of such damage. Pain is always subjective [the International Association for the Study of Pain (IASP)]. Cancer-induced pain may be acute or chronic. Cancer-induced pain may be nociceptive or neuropathic or psychogenic, but often it is mixed because there are several causes causing it to occur. The main (basic) is constant pain of controlled intensity. A breakthrough pain occurs when a basic pain is controlled. Breakthrough pain is a temporary exacerbation with high intensity pain, which is felt in patients whose basic pain was adequately treated with opioids [12].
\nCancer pain is not a single entity. It incorporates a range of etiological, pathophysiological, and anatomical subtypes, all requiring unique descriptive terminology, assessment techniques, and treatment modalities [13]. Among patients with cancer, there is substantial heterogeneity in how pain is experienced and in how it appears. In many cases, the constellation of symptoms and signs can suggest a specific cancer pain syndrome [14]. The identification of such a syndrome may help to elucidate the etiology of the pain, direct the diagnostic evaluation, clarify the prognosis for the pain or the disease itself, and guide therapeutic intervention.
\nMost acute cancer pain syndromes are primary as related to a diagnostic test or treatment. However, some are secondary as they are disease related, such as pain due to acute hemorrhage into a tumor, bone pain from a pathologic fracture, etc. Although some tumor-related pains have an acute onset (as after pathological fracture), most of these will persist unless effective treatment for the underlying lesion is provided. Generally, acute cancer pain syndromes are divided: (1) directly related to cancer, (2) cancer diagnostics related, and (3) associated with antineoplastic treatments.
\nA clinical picture of directly related to various cancer syndromes depends on cancer’s etiology, location, surrounding tissues involved, growing speed, and other factors. Cancer-diagnostic-related syndromes also have miscellaneous presentation and can be presented as: (a) headache after lumbar puncture, (b) prostate pain after biopsy, (c) breast pain after mammography; (d) pain after any other intervention, and some others. Acute pain associated with antineoplastic treatments can be presented as: (a) pain related to chemotherapy and (b) pain after radiotherapy [15].
\nRelated to chemotherapy pain has various causes depending on an agent used, a method of inclusion into organism, etc. Most typical are intravenous infusion pain (due to venous spasm, chemical phlebitis, vesicant extravasation, and anthracycline-associated flare), intraperitoneal chemotherapy pain (chemical serositis or infection), mucositis (due to cytotoxicity of cytarabine, doxorubicin, methotrexate, and others), painful peripheral neuropathy (toxicity associated with vinca alkaloids, cis-platinum, oxaliplatin, and paclitaxel), headache (after intrathecal methotrexate), myalgias/arthralgias interferon induced, and others. Pain after radiotherapy can be incident pain precipitated by transport and positioning of the patient for radiotherapy, or it can be caused by acute radiation toxicity. Most typical are: oropharyngeal mucositis, early-onset brachial plexopathy, subacute radiation myelopathy, radiation enteritis and proctitis, and others. Some more acute cancer pain syndromes can be related to infection (herpes zoster) or venous thrombotic events.
\nChronic cancer pain syndromes usually are directly related to the neoplasm itself or to an antineoplastic therapy. The classification is presented in Table 1 [16].
\nChronic cancer pain syndromes | \nClinical presentation | \n
---|---|
Tumor-related somatic pain syndromes | \nMultifocal bone pain | \n
\n | Soft tissue pain | \n
Tumor-related visceral pain syndromes | \n\n |
Tumor-related neuropathic pain | \nLeptomeningeal metastases | \n
\n | Cranial neuralgias | \n
\n | Radiculopathies | \n
\n | Plexopathies | \n
\n | Peripheral mononeuropathies | \n
\n | Paraneoplastic syndromes | \n
Headache | \n\n |
Pain related to antineoplastic treatments | \nChemotherapy-related neuropathy | \n
\n | Bone complications and glucocorticoids | \n
\n | Antiandrogens and gynecomastia | \n
Postsurgical pain syndromes | \nPain and phantom sensation after amputation | \n
Postradiation pain syndromes | \nPlexopathies | \n
\n | Myelopathy | \n
\n | GI tract disorders | \n
\n | Lymphedema | \n
\n | Osteonecrosis | \n
The classification of cancer chronic pain syndromes.
Bone metastases are the most common cause of chronic pain in cancer patients. Bone pain should be differentiated from non-neoplastic causes including osteoporotic fractures (such as associated with multiple myeloma), focal osteonecrosis (due to chemotherapy or corticosteroids, or radiotherapy), and osteomalacia. Vertebrae are the most common sites of bony metastases pain. Typical locations are atlantoaxial destruction and odontoid fracture, C7–T1 syndrome, and T12–L1 (thoracolumbar junction) syndrome. Epidural compression of the spinal cord or cauda equina is a common neurologic complication of cancer. Breast, lung, and prostate cancers each account for 20–25% of events [17]. And back pain is the initial symptom in almost all patients with epidural compression. The pelvis and hip are also common sites of metastatic involvement. Lesions may involve any of the three anatomic regions of the pelvis (ischiopubic, iliosacral, or periacetabular), the hip joint itself, or the proximal femur [18]. Leptomeningeal metastases, which are characterized by diffuse or multifocal involvement of the subarachnoid space by metastatic tumor, occur in 1–8% in patients with systemic cancer [19]. The most common presenting symptoms are headache, cranial nerve palsies, and radicular pain in the low back and buttocks. Gadolinium-enhanced MRI imaging of the neuroaxis is the investigation of choice when leptomeningeal metastases are suspected. Base of skull metastases can be presented with various syndromes: orbital syndrome, parasellar syndrome, middle cranial fossa syndrome, jugular foramen syndrome, trigeminal neuralgia, and others. Neuropathic pains can be presented as painful radiculopathy, postherpetic neuralgia, malignant brachial plexopathy (lymphoma, beast, lung cancers). Brachial plexopathy also is typical for radiation-induced syndromes. Radiation changes in the skin and lymphoedema are commonly associated. Malignant lumbosacral plexopathy is most frequently associated with colorectal, cervical, breast cancers, sarcoma, and lymphoma [20]. Paraneoplastic painful peripheral neuropathy can be related to injury to the dorsal root ganglion (also known as subacute sensory neuronopathy or ganglionopathy) or injury to peripheral nerves [21]. Subacute sensory neuronopathy is usually associated with small cell carcinoma of the lung. Even in the absence of involvement of the chest wall or parietal pleura, lung tumors can produce a visceral pain syndrome, being unilateral or bilateral (less common).
\nMost treatment-related pains are caused by tissue-damaging procedures. Chronic-treatment-related pain syndromes are associated with either a persistent nociceptive complication of an invasive treatment (such as a postsurgical abscess), or more commonly, neural injury. Toxic peripheral neuropathy, avascular (aseptic) necrosis of femoral, or humeral head are among most common treatment-related chronic cancer pain syndromes. Breast surgery pain syndromes are very prevalent, too. Chronic neuropathic pain of variable severity is common for those patients, and severity of pain is correlated positively with the number of lymph nodes removed [22] both with tumor location (upper outer quadrant of the breast).
\nDespite significant medical, pharmacological, and technological advances in the area of cancer pain assessment and management, up to 90% of patients with advanced cancer experience pain [23], which means careful pain assessment is essential for successful pain management. Cancer pain assessment is a complex undertaking. The evaluation begins with a thorough history of both the pain and the underlying malignancy as well as its treatment. A localization and intensity of pain have to be analyzed in detail, constantly indicating it in the diary. After initial treatment, the effect of treatment pain intensity is to be re-evaluated. Because of the potential impact of pain on quality of life, it is also essential to determine the adverse effects of pain on physical and psychosocial well-being, as well as the spiritual impact of the pain. Also, it is important to remember that cancer pain may linger after the cancer is removed (as examples, postmastectomy, postamputation, or postthoracotomy syndrome), and this may have important psychological and spiritual impact. Other factors that may influence the pain experience should be overestimated and discussed with the patient and his family.
\nCurrent recommendations advise that pain severity should be assessed on an 11-point numerical rating scale (NRS) (0–10), with more comprehensive tools including the Brief Pain Inventory (BPI) and McGill Short Form Questionnaire reserved for occasions when more detailed assessment is required [24, 25]. Newer tools including the Alberta Breakthrough Pain Assessment Tool, specifically designed for breakthrough pain, also could be used in the clinical trial setting [26].
\nNumerical rating scale (NRS)—the intensity of pain is measured by asking the patient to select a number from 0 to 10 that describes the intensity of his pain: “0” means “no pain” and “10” means “unbearable pain.” The numbers are arranged in one line. This method is easily understood by many patients, eliminates linguistic and cultural barriers between the investigator and patient, and is most often recommended for pain assessment. The lingual version of NRS can be easily adapted to ill patients who cannot write. In Verbal Rating Scale (VRS), patients are asked to choose the word best suited to describe their pain: no pain, mild pain, moderate pain, severe pain, and unbearable pain.
\nIn Faces pain scale (FPS), five smileys are given, starting from a smiley face to the left (no pain) to a sad, and crying right (“unbearable pain”) (Figure 1). The patient points out the smile that most reflects the pain. The researcher compares the chosen smile with the expression of the patient’s face.
\nLithuanian pain scales (Decree of the Lithuanian MOH V-608, 26-08-2004 [27], English version).
These three pain scales (NRS, VRS, and FPS) are useful clinical tools to assess pain intensity if they are integrated in Table 1, which allows a comparative assessment of the patient’s pain intensity [27].
\nIn Visual analogue scale (VAS), patients are asked to pinpoint their pain in the 10 cm section (in the straight line) as accurately as possible. The end of the left line indicates “no pain” and the right is “unbearable pain.” The method is widely used in scientific research, but not all patient groups are easy to understand.
\nInferred pathophysiology or types of cancer pain (nociceptive/neuropathic) are also core in diagnostics, that is why neurological somatosensory examination using specific sensory stimuli tools (von Frey filament, brush, pin prick, hot/cold water tubes, tuning fork) is essential.
\nIn diagnosing a breakthrough in cancer pain, first is necessary to ask the patient to describe his/her baseline pain over 24 hours, including description of location, intensity, quality, and other features. If continuous pain has fluctuations and breakthrough pain suspected, it is necessary to ask the patient how many different types of breakthrough pains the patient experiences in a 24 hour period following pain variables: location, provocation, quality, etiology, etc. Finally, asking the patient about three most bothersome breakthrough pains allows us to determine what is a breakthrough pain really wearying the patient. Breakthrough pain intensity should be rated by NPS and filled in the pain diary. It also have to be investigated in detail including such characteristics as localization, number of episodes, possible irritant, beginning of pain outbreak, strength, quality, distribution, effectiveness of the medication used. It is also important to evaluate other symptoms of the patient’s pain breakthrough: psychological stress, spiritual suffering, craving for chemicals and medications, and cognitive function.
\nTo conclude the evaluation of cancer pain, it is necessary to agree with the patient what the aim of the intended treatment is, what is the analgesia (score from…to), and what pain intensity is tolerated.
\nThere are a number of significant challenges associated with the precise assessment of a cancer patients’ pain [28]. They include: (1) multiple cancer pain mechanisms, patients often have multiple coexiting pain disorders even in the one cancer as the example of breast cancer, pain can be caused by surgical outcome, tumor spread, chemotherapy and bony metastases to the spine, (2) lack of a universal cancer pain classification system, (3) lack of objective testing modalities, (4) time constraints of staff that failing in continuous reassessment of pain as this is a vital sign to be fully controlled, and (5) individual differences in cancer pain sensitivity.
\nThe National Cancer Institute (NIH, USA) has funded a Patient Reported Outcome Measurement System (PROMIS). This aims to develop a widely available set of standardized instruments to measure subjective outcomes in illnesses, including cancer [29].
\nAdequate pain relief can be achieved in 70–90% of patients when well-accepted treatment guidelines for cancer pain are followed (World Health Organization [30]). Therefore, pain management techniques should be implemented as early as possible to prevent the development of persistent pain, which can lead to a significant reduction in quality of life. Unfortunately, the availability of effective therapy and updated guidelines from reliable leading societies has not eliminated the problem of undertreatment of cancer pain [3]. The causes of undertreatment are multifactorial and reflect the combined effects of clinician-, patient-, and system-related barriers as been provided in this chapter previously (p.2, Introduction).
\nMethods of pain control in cancer pain can be divided into: (a) pharmacological, (b) oncological, (c) surgical, (d) interventional, (e) psychological, (f) physiotherapy, and (g) complementary.
\nMedications are mainstream in the treatment of cancer pain and taken on a regular basis to provide pain relief. They are mostly given by oral administration as this increases ease of use and is usually the most cost-effective solution. Other forms of pain relief medication may be required in some cases, including rectal suppositories, transdermal patches, or injections.
\nThe WHO analgesic ladder provides a structured starting point for the pharmacological treatment of the patient with cancer pain. It is not without controversy, however, some authors questioning the need to start all patients with severe pain on the bottom rung (i.e., managing with paracetamol alone rather than proceeding directly to stronger drugs). Some also have suggested that the second step (weak opioids) should be omitted in favor of low-dose strong opioids for the sake of both clinical effectiveness and simplicity [31]. For mild to moderate cancer pain, simple analgesic medications such as paracetamol or nonsteroidal anti-inflammatory medications (e.g., ibuprofen or aspirin) can usually provide effective pain relief. Nevertheless, opioid analgesics are mainstream in treating the cancer pain as in most cases it is severe or even unbearable [32]. Some important rules must be followed before starting with the prescription with opioids. Careful assessment of the pain and its effect on function, and of the possible risks associated with use of an opioid, are the first step. When opioids are considered, providers should assess every patient for risk factors for addiction. Providers should also employ strategies to reduce the risk of misuse for all patients who are taking opioids. These strategies may include urine testing, checking state prescription drug monitoring programs to evaluate a person’s history of filling prescriptions for controlled substances, doing pill counts, and using patient-provider agreements or contracts.
\nLong-acting opioids may be administered orally or can be given in the form of a transdermal patch. Long-acting opioids are usually started at an initial low dose and titrated upward every 2–3 days for oral formulations and 5–6 days for patches. Short-acting opioid preparations may be used to treat breakthrough pain. One-sixth of the daily opioid requirement is commonly prescribed, and is often a useful starting point. Well-documented side-effects of opioid therapy include sedation, constipation, confusion, nausea and vomiting, pruritus, urinary retention, and occasionally, respiratory depression is necessary. Chronic administration may lead to problems such as tolerance, physical dependence, and addiction. It must be noticed that by case, opioids may worsen pain—a phenomenon known as opioid-induced hyperalgesia. Management principles of side effects include: (a) opioid reduction or cessation, (b) opioid rotation, where one therapeutic opioid is substituted for an equivalent dose of another, (c) symptomatic treatment, and (d) administration of a specific antagonist.
\nAnother group of pharmaceuticals used for the treatment of cancer pain is adjuvants (Table 1). Common adjuvants are antidepressants, anticonvulsant, biphosphonates, and others [33]. An adjustment of adjuvants to the treatment plan of cancer pain is typical if the pain has a neuropathic element or is wholly neuropathic. In such cases, antidepressants and anticonvulsants may be more effective in providing balanced analgesia and better tolerance than the high doses of opioids. Bisphosphonates are helpful in reducing the severity of bone pain secondary to both osteoporotic vertebral collapse and metastatic deposit. They are incorporated into the structure of mineralized bone as pyrophosphate analogues, to be then taken up by active osteoclasts, which are then inhibited. High-dose steroids can be given to reduce inflammation and edema associated with tumor growth, and to partially mitigate local mass effect. Capsular distension of intra-abdominal visceral can be very painful, and steroids may be helpful in this situation. They are also used for the immediate management of metastatic spinal cord compression and in the palliation of intracerebral lesions.
\nChemotherapy, radiotherapy, endocrinotherapy, and immunotherapy are oncological methods used for cancer pain relief. Chemosensitive tumors include small-cell lung carcinoma, myeloma, colorectal, and breast cancers. These drugs are designed to target rapidly dividing cells, but can lead to the well-known side-effects of hair loss, mucositis, and diarrhea. Also, many chemotherapeutic agents are neurotoxic and cause varying degrees of temporary and permanent nerve damage, resulting in peripheral neuropathy.
\nRadiotherapy is particularly useful in the treatment of bony metastases and nonoperable pathological fractures, but may be used in various other contexts where the tumor type is known to be radiosensitive. Several types of radiotherapy exist: (a) localized external beam radiotherapy, (b) wide-field external beam radiotherapy, (c) brachytherapy, and (d) radioisotope treatment. Certain types of tumor may be dependent on circulating hormones to affect growth, and therefore susceptible to manipulation of the endocrine system, for example, prostate cancer. The use of immunotherapy in cancer treatment has shown to improve survival even in some advanced cancers, such as breast tumor.
\nSurgery can be undertaken with curative or palliative intent. If a cancerous tumor is responsible for causing the pain, techniques to reduce the size or obstruction of the tumor offer the greatest benefit. This may involve surgical removal of the tumor or shrinking of the tumor with radiation therapy. Neurosurgery to cut or block the nerves involved in the pain pathways can also help to reduce severe neuropathic pain. Bone fixation may be necessary to palliate a pathological fracture or decompress the spinal cord.
\nThe aim of interventional cancer pain management is to interrupt nociceptive transmission at one or more points between periphery and cortex to achieve adequate analgesia. This can be achieved via reversible, nondestructive techniques for diagnostic purposes and short-term analgesia, or offer a longer-lasting solution via the physical or chemical destruction of the nervous tissue.
\nThe diagnosis of a life-threatening illness has a huge psychological impact on patients and their families. Grief reactions, anxiety, and depression are particularly problematic at nodal points in the cancer pathway: at diagnosis, starting treatment, recurrence, failure of treatment, and facing the prospect of dying. Such psychological states exacerbate, and also are exacerbated by, uncontrolled pain, and addressing them is often of paramount importance in beginning to manage pain and improve the quality of life. Multidisciplinary input, with the use of evidence-based interventions such as cognitive behavioral therapy, distraction and relaxation techniques, graded exercise, and goal setting can be delivered with the involvement of psychologists, physiotherapists, and occupational therapists.
\nThere are some complimentary medicinal techniques that can be used as additional complex in the treatment of cancer pain. These include: (a) acupuncture, which can help to relieve pain through the manipulation of pressure points in the body, (b) biofeedback is a technique that promotes awareness of bodily processes such as heart rate and blood pressure to influence the severity of the pain, (c) distraction techniques such as music therapy can be useful to shift attention away from the pain to a more pleasant stimulus, (d) hot or cold packs can be helpful to regulate pain and provide relief, (e) hypnosis can be used to manage pain by focusing the patient’s consciousness to process pain information more effectively, and (f) relaxation exercises can be used to refocus the attention of the patient on a specific task, such as breathing, to lessen the pain.
\nIn general, an effective strategy for cancer pain management is predicated on several broad principles [34]:
A detailed assessment of the pain should be performed initially; careful reassessment is indicated whenever a change occurs. The initial assessment of the patient with cancer pain always includes a history and examination, and often requires imaging or laboratory tests. The approach may be conceptualized as collecting data are sufficient to characterize key elements of the pain (a specific pain syndrome, the inferred pathophysiology, the etiology of pain, etc.).
The second principle recognizes that pain may be addressed by disease-modifying antineoplastic therapy and other interventions directed against the etiology of the pain. Treatments that address the underlying etiology of pain, such as radiation therapy, surgery, or in some cases, chemotherapy can be integrated into a broader plan of care for symptom control. Treatment of cancer-related pain usually requires close consultation with an oncology specialist, who can provide the necessary information about the availability of antineoplastic therapy.
Whether or not primary disease-modifying therapy is possible, a large proportion of patients with pain due to active cancer require symptomatic treatment. Beginning in the early 1980s, a worldwide consensus has evolved that considers opioid-based pharmacotherapy as the mainstay approach for the symptomatic treatment of cancer patients with active disease and pain that is moderate to severe. This conclusion was originally codified in the World Health Organization’s (WHO) “analgesic ladder” approach, which was originally published in the mid-1980s and has had a global influence on clinical practice and policies pertaining to medication availability.
In 1986, the World Health Organization (WHO) declared cancer pain management algorithm, so called three-step analgesic ladder (Figure 2) [35].
\nCancer pain management—three step WHO analgesic “ladder” [
I step: main medication—aspirin, acetaminophen, and nonsteroidal anti-inflammatory drugs (NSAIDs) are used for the treatment of mild pain (score 1–3 in NAS). Nonopioids can be used as adjuvants in II and III steps analgesia.
\nII step: medication—weak opioids: codeine, dihydrocodeine, and tramadol are used for moderate intensity pain relief (4–6 by NAS). The upper tramadol daily (ceiling) dose is 400 mg. If oral or parental route of administration is not possible, for moderate pain treatment, one can use strong opioids in low doses, e.g., transdermal fentanyl patches.
\nIII step: medication—strong opioids: morphine, fentanyl, methadone, and others are used for severe and intolerable cancer pain (NAS-7-10) relief [36].
\nAdjuvants may be administered in all steps together with main analgesics. They enhance pain relief and decrease or prevent opioids side effects. In 2000, algorithm was revised in decreasing limitations of opioid use, enabling to start treatment with strong opioids if patient is suffering from severe cancer pain. Other modifications of WHO three-step analgesic ladder were later applied (2005), introducing spinal opioids for refractory pain (see Figure 3).
\nModified WHO ladder approach for cancer pain (Fine P G, 2005).
There are two groups of medication for cancer pain management: (1) analgesics: opioids and nonopioids and (2) adjuvants.
\nOpioid analgesics are: (a) weak: tramadol, codeine (and dihydrocodeine) and (b) strong: morphine, fentanyl, methadone, buprenorphine, pethidine [37]. The route of administration are as follows: (a) noninvasive (oral, rectal, transdermal, nasal, sublingual), (b) invasive-parenteral (intramuscular, intravenous, subcutaneous, etc.), including long acting devices such as “morphine pumps “with subcutaneous or epidural catheters and PCA-patient-controlled analgesia option, allowing patient to determine and regulate the needed day and night doses of opioids. The day dose is determined by giving short-acting (immediate release) opioids, such as morphine hydrochloride 1% or morphine sulfate, 1–2% solution injections or tablets (e.g., 10 mg every 4 hours), day dose correction is made after 24–48 hours. After the needed day dosage is achieved (after 3–4 days), we switch to long-acting (slow release) (12–24 hours) morphine medication—tablets, suspension, suppositories, or fentanyl patches (72 hours) [38]. If morphine was administered parenterally, the needed daily oral or rectal dose of morphine should be three times bigger than the injected one earlier. Short-acting (immediate release) opioids should be used for breakthrough pain relief.
\nThe use of opioid analgesics may induce [39]:
tolerance—a state of adaptation in which exposure to a drug induces changes that result in diminution of one or more of the drugs’ effects over time, which is while using opioid, one has to increase its dose after some time due to the decrease in analgesic effect;
physiologic dependence—a state of adaptation that is manifested by a drug-class-specific withdrawal syndrome that can be produced by abrupt cessation, rapid dose reduction, decreasing blood level of the drug, and/or administration of an antagonist. It can be avoided by gradual opioid dose reduction;
psychologic dependence (addiction)—a primary chronic, neurobiologic disease with genetic, psychosocial, and environmental factors influencing its development and manifestations. It is characterized by behavior that includes one or more of the following: impaired control over drug use, compulsive use, and continued use despite harm and craving (AAPM, APS, ASAM, 2001).
Adverse effects of opioids: constipation, nausea/vomiting, respiratory depression, urinary retention, pruritus, sedation, and more rarely, neurotoxic disorders-hallucinations, seizures, delirium, hyperalgesia. To evade or decrease these effects, one uses adjuvants (laxatives, antiemetics) or opioid rotation (changing one strong opioid to another and adapting the dosage).
\nOpioid rotation is a change of one opioid drug to another due to acquired tolerance or unmanageable side effects. These are the rules of opioid rotation:
additional clinical assessment of pain and its diagnostics;
adaptation of the day dosage for the newly prescribed opioid (in 24 hours period);
determine the equianalgesic dose of the new opioid (Table 2);
decrease the determined dose of newly applied opioid by 25–50% to avoid crosstolerance of both drugs and possible inadequacy of the dosage;
if after applying new opioid, the pain relief is not enough and its dose is increased by 100–125%;
titrate new drugs’ dose for 24 hours until good pain control is achieved;
evaluate side effects and drugs’ effectivity; and
pain re-assessment for every 2–3 days.
Medication | \nRoute of administration | \nEquivalent of 10 mg morphine dose | \n
---|---|---|
Codeine | \nOral | \n100 mg | \n
Tramadol | \nOral/parenteral | \n50–100 mg/25–50 mg | \n
Oxycodone | \nOral/parenteral | \n5–7.5 mg/3.33–5 mg | \n
Pethidine | \nParenteral | \n25 mg | \n
Methadone | \nOral | \n5 mg* | \n
Fentanyl | \nPatch | \n0.067 mg** | \n
Morphine | \nParenteral | \n3.33–5 mg | \n
Opioid equianalgesic day doses.
Methadone/morphine, if morphine day dose: (a) >30 mg 1:4, (b) >100 mg 1:8, and (c) >300 mg 12:1.
Fentanyl/morphine, if morphine day dose: (a) 30 mg—12 mcg/hours, (b) 60 mg—25 mcg/hours, (c) 90 mg—37 mcg/hours, (d) 120 mg—50 mcg/hours, etc.
Opioid rotation is applied according to opioids equianalgesic doses table, thus changing the daily dose of the new drug [40].
\nIn the event of opioid overdose antagonist, naloxone is applied.
\nThe adequate pain control is achieved gradually, by dose titration and administration of various treatment options. Preliminary period of time to achieve:
no awakening at night due to pain—2–3 days;
no pain while not in movement (seated or lying in bed)—3–5 days;
no pain while moving—3–7 days (not for patients with multiple vertebral and pelvic bone metastases—for them total pain control may not be achieved); and
for patients experiencing anxiety and depression—3–4 weeks.
Nonopioids: aspirin, paracetamol, and nonsteroidal anti-inflammatory drugs (NSAIDs). They are effective in treating mild pain (score 1–3 by number analogue pain intensity scale (NAS)), due to bone metastases, soft tissue or muscular irritation, and damage. They are treating inflammation and decreasing fever and pain. NSAIDs are COX-1 and COX-2 also COX-3 inhibitors. They can be quite toxic to the GI tract (dyspepsia, erosions, ulcers, bleeding, constipation), slowing thrombocytes aggregation, impairing renal and liver function, enhancing hypervolemia, provoking rashes, headaches, dizziness, and allergic reactions. These drugs have their upper dose limit so-called “ceiling effect” when the analgesic effect cannot be increased but the adverse effects are progressing.
\nGlucocorticoids ( dexamethasone, prednisolone, hydrocortisone)—indications: increased intracranial pressure, spinal cord compression, nerve compression or infiltration, bone metastases, extended liver capsule, soft tissue cancer infiltration (head and neck, abdominal, and pelvic tumors). Contraindications: no absolute contraindications, dose is limited by adverse effects, and being cautious with peptic ulcers, diabetes, cardiovascular dysfunction, and endemic situations. Adverse effects: Cushing syndrome, gastric ulcers, erosions, bleeding, increased appetite, weight, hyperglycemia, diabetes complications, muscle wasting, euphoria, dysphoria, emotional lability, depression, steroidal psychosis, edemas, hypertension, thrombosis, myopathies, decreased immunity to infections, potassium blood levels, liquid detention in the body, insomnia, skin purpura, etc.
\nDrugs for neuropathic pain: antidepressants, anticonvulsants, local anesthetics, and myorelaxants (baclofen).
\nAntidepressants—not always effective for neuropathic pain treatment and is better to prescribe tricyclic antidepressants (TCAs). Start with amitriptyline —10–25 mg dose in the evening and then increase to 50–100 mg/day. If no effective pain relief is achieved, it is discontinued after 1 week of use. Adverse effects: somnolence and hypotension.
\nAnticonvulsants—for neuropathic pain—gabapentin, carbamazepine, and clonazepam. The starting dose is the same as treating epilepsy. Increase until pain relief is achieved, or unmanageable adverse effects (nausea, vomiting, somnolence, ataxia, dizziness, disorientation) occur.
\nLocal anesthetics (lidocaine, mexiletine)—for neuropathic pain systemic treatment when other options are not working. Adverse effects: somnolence, nausea, tremor, dyspepsia (better use while eating).
\nNMDA receptors antagonists (ketamine)—for persistent neuropathic pain and other chronic pain when opioids are not tolerated. Routes of administration of ketamine: oral, intravenous, starting with 100 mg/day, and titration till 500 mg/day. Adverse effects: psychomimetic can be reversed by benzodiazepines and haloperidol.
\nAccording to medical literature, about 20% of women have neuropathic pain after mastectomy and about 1/3 of cancer patients suffer from neuropathic pain (or both—nociceptive and neuropathic—together).
\nBisphosphonates (pamidronate, zoledronic acid)—decrease bone resorption, effective in treating cancer hypercalcemia, decrease bone pain and occurrence of pathologic bone fractures for the patients with bone metastases, inhibit activity of osteoclasts, and are useful with ineffective radiotherapy and analgesics.
\nRadionuclides—Stroncium 89 systemic administration effectively relieves pain due to bone metastases, better works for osteoblastic metastases, and helps about 80% of patients. The response lasts from 3 to 6 months and is evident already after 2–3 weeks. Adverse effects: myelosuppression, monitored by blood tests. Trials with radioisotopes of samarium and rhenium were also performed.
\nPsychotropic drugs—neuroleptics. Common neuroleptics (e.g., haloperidol) have no analgesic effect but decrease anxiety, insomnia, treat nausea, and delirium. Levopromazine has analgesic effect: 20 mg dose is equivalent to 10 mg of morphine. Adverse effects: somnolence and hypotension. Benzodiazepines (diazepam, lorazepam, oxazepam) are useful for muscle spasms or acute bone-muscular pain. Adverse effects: hypotension, somnolence, and fatigue. Psychostimulants: metilphenidate has no analgesic effect and may be used to decrease severe opioid-induced somnolence. Adverse effects: dysphoria, tolerance, and dependence.
\nMyorelaxants—baklofen (act on spinal cord level, start with 5 mg/day dose, and increase till 100 mg/day, for severe hiccup (hiccough)). Adverse effects: fatigue and somnolence. It should be discontinued slowly due to possible withdrawal syndrome and convulsions. Dantrolene—primary effect on muscles. Start with 25 mg/day, and continue with maximal titration till 400 mg/day. Adverse effects: fatigue, somnolence, and hepatotoxicity.
\nIn most patients, cancer pain can be adequately controlled with pain medication; however, in 5–14% of oncological patients’, invasive pain management is needed [41]. Invasive procedures are the part of the option available for cancer pain management. Anesthetic, neurosurgical, or other invasive procedures can be given. Interventional pain management can improve pain control and reduce the amount of systemically administered drugs and their side effects. Also, invasive procedures can be an option when it is not possible to administer oral or parenteral medications. Final decision maker is a physician (anesthetist, pain specialist, and neurosurgeon) who will perform the procedure. He is main person that will decide about indications and contraindications for intervention treatment and will explain and talk with the patient or his relatives about the possibility of intervention and of course risk factors and possible complications. Invasive cancer pain procedures can be divided in to nondestructive and destructive.
\nNondestructive procedures are such that the pain signal is modulated or interrupted (blocked) by the administration of a pharmacological agent to a source of pain. The pharmacological preparation may be administered by a single shot dose or via a catheter for long-term administration of the medication. Usually, the catheter is placed neuroaxially (into the spinal canal) or near the peripheral nerves or plexuses. Peripheral nerve blocks/injections can be used, but they are effective for short term and are usually performed in patients with limited survival when the pain source is one or more nerves or when the pain is caused by pathological fractures or vascular occlusion. As a first-line treatment, these blockades are rarely used and, if applicable, it is necessary to combine with systemic analgesics.
\nNeuraxial invasive procedures can be: intrathecal or epidural. For example, an epidural medication injection (transforaminal or translaminar) or catheter/devise placement is applied in most of the cases when the nerve structures are involved in pain cause.
\nIn case of complicated cases and intolerable pain, opioid analgesics can also be delivered through neuraxial delivery systems. The use of neuraxial system for long term can range from simple percutaneous (tunneled) patient controlled to implantable complex programmable medication delivery systems. Implantable systems are expensive, but safe and their application is always justified, if patient need pain control longer than 3 months and other medical treatments are not effective [42, 43]. These techniques may be on an oncological pain management plan, but they do not generally apply to everyday cases.
\nDestructive procedures can be applied in cases where pharmacological preparations cannot modulate the pain signal. For example, in case of small cell lung cancer and mesothelioma, chest pain is poorly localized, severe, and intolerable. This is because intercostal nerves and their branches can be infiltrated in cancer cells, during metastatic spread and making it difficult to manage the source of pain. Then, the cordotomy can be applied—a neurosurgical procedure in which the spinal cord-spinothalamic tract ablation is performed in the area opposite to the pain. After the ablation pain disappears, but along with the disappearing of pain on the part of the body below, the ablation area develops temperature and paresthesia [44]. Another destructive procedure is rhizotomy, segmental or multisegmental destruction of spinal cord nerve roots. It can be done in several ways: (a) surgically, (b) chemical neurolysis (phenol), and (c) radio-frequency ablation [45, 46].
\nChemical neurolysis is widely used in the treatment of intractable cancer-related pain, especially in abdominal and pelvic cancer-related pain. These procedures can provide prolonged pain relief (3–6 month) and decrease the need of opioids.
\nHigh evidence is for coeliac plexus neurolysis in pancreatic cancer-related pain [47].
\nNeurolytic agents that often used for chemical neurolysis are alcohol, phenol, and glycerol.
\nAll procedures can be done under ultrasound, X-ray, or CT scan. After the procedure, patient may experience significant pain relief and opioid withdrawal symptoms [48].
\nPalliative radiotherapy is effective for the treatment of cancer pain caused by bone and brain metastases, metastatic skin ulcerations, and infiltrative growth of tumor in soft tissues. The summary dose of palliative radiotherapy is smaller than the dose for radical radiotherapy; maximal effect is achieved giving minimal number of radiation fractions (1–5) [49].
\nTranscutaneous electroneurostimulation (TENS)-nerve stimulation via electrodes put on skin, thus, inhibits pain signal in spinal cord. Optimal dose varies for different patients. TENS is used for the treatment of mild and moderate cancer pain but is not effective for visceral pain. TENS is contraindicated for the patients with pacemaker (ECS). Pain relief effect is quick but usually not long-lasting (only for 15–20% of patients).
\nPsychotherapy-introducing patients psychological support groups, delivering enough information; relaxation therapies, meditation; cognitive therapy, auto-training, hypnosis, short psychotherapy seances with psychotherapist. Drug is administered if there is a need to correct renal, liver failure, and antidepressants for depression [50].
\nAcupuncture, physical therapy, mild massage can also be applied.
\nPalliative care includes palliative cancer treatment options, such as palliative radio therapy, palliative surgery, palliative chemotherapy, also pain relief and control of other symptoms caused by advanced cancer [51].
\nMost common symptoms control [53].
\nAnorexia is a loss of appetite, usually with decreased food intake.
Constipation is a common symptom in palliative care. The key should be prevention. Causes can be diseases related to GI obstruction, neurologic (spinal cord compression), hypercalcemia, inactivity; or treatment related-opioids, other medication. Treatment-laxatives, other medication, increasing fluid intake, and dietary consultation.
\nAdvanced cancer patients at the end of life also often exhibit
Aging population and increasing number of long time cancer survivors, some of them finally ending as advanced cancer patients, now especially increase the need of
Palliative care models (WHO directives, 2002) (adapted by Skorupskiene (2018)).
General principles of palliative care:
patient and family as unit of care;
attention to physical, psychological, social, and spiritual needs;
interdisciplinary team approach;
education and support of patient and family;
extends across illnesses and settings; and
bereavement support [55].
The main idea of palliative care-no matter how much the disease is advanced, and what complex treatment has been applied, one always can do something more to improve the quality of life, still left for the patient.
\nPlanning pain relief for cancer pain patients one should take into the consideration possible mechanisms and types of pain (nociceptive, neuropathic, mixed), patients’ wishes, former treatment. If psychological distress is present, talking about pain assessment is needed, if there is suffering, help from the clergymen may be useful. If the signs of drug addiction appear, drug release should be more controlled, physical aspects of pain relief introduced. With cognitive disorders depression and anxiety should be treated, also opioid rotation should be available.
\nCancer pain treatment algorithm [2]:
assessment of pain reason, type, and intensity;
pharmacological pain treatment: basic pain relief, breakthrough pain relief, and adjuvants;
nonpharmacological treatment of pain;
evaluation of results and correction of treatment plan; and
providing constant pain relief and palliative care.
Basic pain | \nBreakthrough pain | \n
---|---|
Start—slow, gradual increase in intensity | \nStart—acute, not predictable | \n
Duration—no less 12 hours/day | \nDuration—from several seconds to 30 minutes | \n
Type—dull, pressing, gnawing… | \nType—acute, shooting, irradiating | \n
Treatment—long acting, slow release opioids, fixed scheme | \nTreatment—short acting, immediate release opioids, on demand basis | \n
After the cause and type of cancer pain is determined, the constant analgesia is started by the easiest route, the patient-oral or transdermal, individualizing the dose, and also providing drugs for relief from other symptoms. The drug is selected taking into consideration the type and intensity of pain, WHO “analgesic ladder,”, also drug combinations, but combined medications should not be used and no placebo drugs as well [56].
\nTo prevent pain becoming chronic, cancer pain relief should be started as soon as pain appears, as it helps to reduce drugs doses, adverse effects, and achieve better drug tolerance. It also reduces the cost of pain treatment, enhances the trust between patient and doctor, and patient is socially active for a longer time. The pain relief effect should be quick, so we can start with stronger medications and later pass on the weaker ones. Different medication is used for different types of pain: (a) nociceptive pain, due to soft tissue, bone damage, and visceral pain are treated by combinations of nonopioids and opioids and (b) neuropathic pain, due to nerve compression—by opioids, glucocorticoids, when nerve is damaged—by antidepressants, anticonvulsants, and NMDA receptor antagonists [57].
\nBreakthrough cancer pain (BTCP) is a transient exacerbation of pain that occurs either spontaneously or in relation to a specific predictable or unpredictable trigger, despite relatively stable and adequately controlled background pain [58]. The frequency is less than four times/day, if it takes more than four times/day, we need to think about lack in background cancer pain control.
\nLeading doctor in BTCP management should preform regular assessments and repeatedly investigate pain management after 1–4 weeks dependably on patient’s complexity.
\nIt is important to understand that the BTCP management is different compared with background cancer pain, which is managed according to the ladder and “by the clock,” while for BTCP, “rescue medication” should be given as needed. Main feature is that the breakthrough cancer pain should be started when background cancer pain is well controlled (Figure 5) [59]. This type of pain can take about from 30 minutes but not more than 60 minutes. The highest intensity of the pain can be reached at tenth minute, and it can take 1–4 episodes/day [60]. For that reason, for BTCP should be given very strong, short-acting opioids.
\nAssociation of Palliative Medicine of Great Britain and Ireland (APM) algorithm for assessing breakthrough cancer pain.
It is better to use the same chemical opioid structure, which is chosen to manage background cancer pain.
\nWhen fentanyl plasters/patches is used, the short-acting medication (buccal or sublingual tablet) for BTCP control can be prescribed. The dose should be titrated up to effective one, because of the lipophilic structure and the absorption, which is through the mucous of the mouth and gastrointestinal tract. There is a variety of short-acting fentanyl forms (Table 3). For example, BTCP management can be started with 200 μg of oral transmucosal fentanyl citrate tablet or 100 μg buccal-soluble film [61].
\nFormulation | \nDescription | \n
---|---|
Nasal spray | \nPhosphate-buffered solution Fentanyl pectin intranasal spray | \n
Sublingual | \nSublingual fentanyl orally disintegrating tablet Sublingual fentanyl tablet | \n
Oromucosal | \nOral transmucosal fentanyl citrate | \n
Buccal tablet | \nEffervescent formulation | \n
Buccal soluble film | \nFentanyl buccal soluble film | \n
Fentanyl short acting formulations.
If for BTP management, immediate-release morphine is chosen, usually one BTP episode is needed, part of 1/6 injecting medication of all morphine day dose. Their pharmacokinetic characteristics have limitations, with a relatively slow onset of action (30–45 minutes) and duration of action of up to 4–6 hours [62].
\nBTCP management consists of other approaches as setting of pain management goals, education of the patient, and depending on the cause of breakthrough pain, occupational therapist, physiotherapist can be involved. Other acute causes as bone fractures, bowel perforation, etc. should be excluded, and if the BTCP can be predicted, pain medication should be given before the coming pain event.
\nThe evaluation of the effectiveness of the pharmacological treatment of BTCP has a four-factor rule [63]:
pain relief;
day activity;
adverse effect of medications; and
possible inappropriate use of opioids.
Possible inappropriate use of opioids is very important factor in pain management, and it should be carefully investigated. It manifests as addiction or pseudoaddiction for strong opioids and can be associated with mental disease. Clinically, it can be seen as seeking for opioids and/or problematic opioid use. In order to correct the possible misconduct in the use of opioids, it is important that these requirements are met before they are given:
to distinguish between people with risk factors (drug users, alcohol dependent, gambling, having mental problems); and
modifying the use of drugs for the prevention of BTCP (by giving a slightly higher dose of slow-release opioid to relieve background pain, try to use nonopioids for BTCP reduction, and family support-controlled home care, etc.) [64].
While treating cancer pain in children and elder patients, one should take into consideration the differences in metabolism, concurrent diseases. Children receive different adapted opioid doses, and opioid rotation is also different (e.g., better pain relief with methadone and not morphine).
\nElderly patients more easily overdose opioids; one cannot double their opioid dose quickly for them. Also, one should be aware of elder persons’ liver and renal function; if there is some failure, the correction is essential before prescribing opioid medication. There are usually a lot of tablets and other oral drugs prescribed for the concurrent diseases, so there is necessary to determine daily opioid dosage very carefully.
\nChronic pain can be a serious, negative consequence of surviving cancer. As a result of remarkable advances in cancer diagnosis and therapy, today there are a record 14 million cancer survivors in the United States. However, an estimated 40% of survivors continue to experience persistent pain as a result of treatment, which can be detrimental to their quality of life [3]. Two-thirds of these individuals are surviving more than 5 years after diagnosis, supporting the need to study pain in this growing population [65]. National Cancer Institute’s Office of Cancer Survivorship characterizes the survivor as a person with a history of cancer who is beyond the acute diagnosis and treatment phase. Risk factors for chronic pain in survivors include the type and invasiveness of the tumor, the treatment regimen used, the time since the cancer treatment has started, and the efficacy of initial pain therapy. Continuous pain is associated with impaired quality of life in this population [66]. As the population of cancer survivors expands, all clinicians, including oncologists, advanced practice providers, and primary care physicians who interact with these individuals, will require the knowledge and skills to implement best practices in the management of chronic pain. When analgesic drugs are used, the imperative to prescribe safely must expand beyond immediate adverse effects, such as the resulting respiratory depression or constipation associated with opioids, to incorporate awareness and mitigation of the long-term consequences of these and other analgesic agents.
\nClinical practice guidelines are issued recently, and they deal comprehensively with the pain people experience after cancer treatment, and are unique in its focus on chronic pain among cancer survivors. Key guideline recommendations include: (1) clinicians should screen for pain at each encounter with a patient. Recurrent disease, second malignancy, or late onset treatment effects should be evaluated, treated, and monitored; (2) clinicians may prescribe nonpharmacologic interventions such as physical medicine and rehabilitation, integrative therapies (e.g., acupuncture and massage), interventional therapies, and psychological approaches (e.g., guided imagery, hypnosis, and meditation); (3) systemic nonopioid analgesics (NSAIDS, acetaminophen) and adjuvant analgesics (selected antidepressants and anticonvulsants), may be prescribed to relieve chronic pain and/or improve physical function; (4) clinicians may prescribe a trial of opioids in carefully selected cancer patients who do not respond to more conservative pain management and who continue to experience pain-related distress or impairment of physical function [67]. The management of cancer survivors suffering chronic pain requires greater consideration of a multimodality plan of care that balances pharmacologic and nonpharmacologic techniques and may necessitate the involvement of an interdisciplinary team; the goals of treatment in these populations may focus on improving function and limiting the long-term adverse effects of pain and of its treatment, as much or more as they do on improving comfort [68].
\nAs therapeutic treatment options and outcomes improve, patients with cancer are living longer. Chronic pain can develop from a variety of sources: peripheral neuropathy, muscle or bone pain, surgery, radiation, and other conditions. Comorbidity with other conditions or syndromes can make assessing chronic pain more difficult. Different chronic pain syndromes may be present for cancer survivors. Chronic inflammatory polyneuropathy is one of many well-recognized pain disorders, together with other treatment-related pain syndromes, such as postsurgical and postradiation pain. Hormonal therapies, such as aromatase inhibitors, can produce arthralgias. As the use of hematopoietic stem-cell transplantation expands, graft-versus-host disease (GVHD) is seen with greater frequency, leading to pain syndromes that can affect almost any organ system. In addition, immunosuppressive agents used to treat GVHD can lead to painful complications (e.g., corticosteroids and avascular necrosis). The recent validation of a tool specific to musculoskeletal symptoms in hematopoietic stem cell transplantation will allow better characterization of this painful phenomenon [69, 70, 71]. The important consideration when designing an usage of analgesics is the potential for harm, and drug-drug interactions with cancer therapies, or other treatments should be considered. Cytochrome P450 CYP 3A and CYP2D6 inhibitors can increase concentrations of opioids, such as codeine, oxycodone, hydrocodone, fentanyl, tramadol, and methadone, metabolized by this system [72, 73]. Methadone and buprenorphine can prolong the QT interval, an effect that can be potentiated by many chemotherapeutic agents, notably doxorubicin [74]. If pain is severe and disabling, and long-term opioid therapy is being considered, the potential for opioid-related harm over time must also be evaluated. Persistent adverse effects such as constipation are well recognized, and risk of sleep-disordered breathing suggests that these conditions must be considered when opioid therapy is initiated and later during the course of treatment. The potential for neurotoxicities, such as persistent mental clouding, increased risk of falls in the elderly, and other phenomena may occur. Opioid-induced hyperalgesia is well described in preclinical models but has uncertain clinical importance; the potential is considered when a patient reports escalating pain in tandem with opioid dose escalation in the absence of identifiable worsening of a pain cause. Opioid-related harm may also result from misuse or abuse, the development of opioid addiction, or the occurrence of drug diversion within the community. The problem of prescription drug abuse is serious, leading to an increase in opioid-related deaths [75]. The treatment of patients with additional chronic conditions, a situation in which the patient may have two or more such conditions, referred to as multiple chronic conditions, is challenging. Insomnia and psychological distress are common conditions in patients with chronic pain, present in 17–90% of adult sufferers, respectively. The most common psychiatric disorders comorbid with chronic pain include depression, anxiety, personality disorders, and PTSD [76]. Evidence also suggests that patients with comorbid conditions are less likely to improve with standard chronic pain treatment [77].
\nBecause cancer posttreatment pain is so complicated; good communication between patients and their medical providers is essential. Cancer survivors may have varying capacities to deal with a great source of information that can sometimes be overwhelming. Some patients may even be reluctant to discuss their pain, seeing it as a sign of weakness or fearing a recurrence; some may see it as an expected and untreatable complication of their cancer treatment. That is why a pain assessment is recommended at every visit. In teasing out how they are coping, clinicians need to ask patients how chronic pain is affecting them and suggest how they can work together to better manage their symptoms and improve their quality of life. The question arises regarding who should provide pain management for the cancer survivor: the oncologist and his or her team, the patient’s primary care provider, a multidisciplinary pain service, or any other professional? Oncology teams providing ongoing care for cancer survivors may be the optimal group to address pain, because they routinely manage a complex regimen of cancer therapies and related symptoms.
\nComprehensive assessment, including the impact of pain on function and quality of life, is warranted for all survivors. Long-term assessment is also needed after clinical trials to better recognize novel or previously unrecognized painful consequences of treatment, including those syndromes that may occur after treatment is completed. Carefully designed, extended studies of pharmacologic and nonpharmacologic interventions to relieve pain and improve function are indicated in this population. An especially relevant and urgent need is research identifying those cancer survivors who respond optimally to opioid therapy and those at greatest risk of adverse effects.
\nCancer care generally requires the technical knowledge and skills of specialty physicians such as medical oncologists, surgeons, and radiation oncologists. General practitioners (GP) may play an essential role because they are often the initial point of contact for patients in obtaining screening or evaluating symptoms, and they may make referrals, coordinate care, and manage symptoms or comorbid conditions. One of the main role for GP also is counseling cancer patients about treatment options and monitoring treatment progress and side effects [78].
\nThe roles of GP’s for patients with cancer such as managing comorbid conditions, chronic pain, or depression, and referring patients to hospice were tested in the study and showed that 22% of GPs reported no direct involvement in cancer care roles, while 19% reported heavy involvement, and rural practice location was not associated with greater GP involvement in cancer care [79]. There is a gradual move toward shared care models with GPs playing a central role alongside other healthcare providers. In this context, it will be important to understand the factors influencing the involvement of GPs in cancer care and how to maximize their involvement throughout the spectrum of cancer care [80]. The studies also confirm that the great majority of GPs are familiar with the modern management of pain control problems commonly encountered in practice, but are less aware of the drug options available for less common situations, particularly the use of syringe drivers [81]. Fortunately, there is no evidence of a reluctance to start strong opioids for severe pain, as identified in previous works [82]. However, it is of concern that only minority of GPs still are suggesting immediate-release opioids for breakthrough pain, and laxatives or antiemetics when starting strong opioids, which is a recommended practice in community palliative care [83].
\nMost common mistakes in the treatment of cancer pain are as following:
monotherapy (NSAIDs or opioid analgesics only);
a prescription of slow release(SR)-form opioids for intake regime “as needed”;
improper treatment of side effects caused by medicines;
medicine for breakthrough pain is added in the situation where basic pain is not controlled sufficiently;
pain breakthrough is not treated at all;
adjuvants (antidepressants, anticonvulsants) and related medicine are not used; and
with the prescription of opioids, behavioral aspects of patients are not evaluated.
A general practitioner, who has diagnosed pain in a cancer patient, starts treatment with analgesics. A ladder analgesia scheme is used. Opioids may even be prescribed for moderate pain, and if the pain is severe and unbearable, the opioid analgesic is the main remedy for pain relief. A sufficient daily dose for baseline (basic) analgesia should be achieved by increasing the dose (titration) of the product [84]. When titrating the product, the following rules should be used: (a) pain is controlled and there are no side effects—treatment to continue the current dose, (b) pain is controlled, but there are side effects—reduce the dose of the product, (c) pain is uncontrolled and there are no side effects—increase the dose of the preparation, and (d) pain is uncontrolled, in case of side effects, change the medicine [85].
\nIt goes without saying that controlling such a complex syndrome as cancer pain can lead to other problems that require the help and advice of the pain physician. Therefore, GP should refer the cancer patient to a pain clinic for a clear indication of the following cases (indications):
when initiating opioid analgesics, basic pain control is not achieved and there is an unadjusted side effect of the drug;
failure to achieve control over cancer breakthrough pain in cases where basic pain is well controlled;
the control of basic pain by an opioid analgesic becomes ineffective, a tolerance to the preparation is suspected, and it needs to be changed to another opioid analgesic (opioid rotation);
pain must be controlled by combining the pharmaceutical treatment and invasive procedures (patient controlled analgesia, pain relief block);
inappropriate behavior with opioid analgesics is identified or developing of psychological dependence on them is suspected;
repeated multidisciplinary pain assessment and specialized control (specialists’ meeting) is necessary; and
if a cancer patient is given a palliative care nursing home or nursing home and cannot physically access the pain clinic, according to the above indications, the pain clinic staff can consult on arrival at the place of destination.
Following the International Association for the Study of Pain cancer pain is “unpleasant sensory and emotional experience associate with actual or potential tissue damage resulting either from the treatment of cancer or the cancer itself.” Due to the complexity of symptoms and multimodality of treatments, cancer pain is built in the most sophisticated field of medicine, where each patient’s stage of disease and diagnosis will require an individualized pain treatment plan to optimize the quality of life. Such tasks can only be carried out using multidisciplinary approach. That is why basic knowledge about cancer pain is essential for every healthcare professional. We believe that the text you have just read will help you to be an active practitioner giving the patients the cancer pain relief.
\nThe authors acknowledge Lithuanian Pain Society for text support.
\nMaterials from “Cancer induced pain,”(Lithuanian Pain Society’s guidelines) 2nd ed., 2018, are used in the text.
\nAudio signal processing is an important subfield of signal processing that is concerned with the electronic manipulation of audio signals [1, 2, 3, 4, 5, 6]. The problem of discriminating music from audio has increasingly become very important as automatic audio signal recognition (ASR) systems and it has been increasingly applied in the domain of real-world multimedia [7]. Human’s ear can easily distinguish audio without any influence of the mixed music [8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23]. Due to the new methods of the analysis and the synthesis processing of audio signals, the processing of musical signals has gained particular weight [16, 24], and therefore, the classical sound analysis methods may be used in the processing of musical signals [25, 26, 27, 28]. Many types of musical signals such as Rock music, Pop music, Classical music, Country music, Latin music, Arabic music, Disco and Jazz, Electronic music, etc. are existed [29]. The sound type signals hierarchy is shown in Figure 1 [30].
Types of audio signals.
Audio signal changes randomly and continuously through time. As an example, music and audio signals have strong energy content in the low frequencies and weaker energy content in the high frequencies [31, 32]. Figure 2 depicts a generalized time and frequency spectra of audio signals [33]. The maximum frequency
Generalized frequency spectrum for audio signal [
Acoustically speaking, the audio signals can be classified into the following classes:
Single talker in specific time [34].
Singing without music.
Mixture of background music and single talker audio.
Songs that are a mixture of music with a singer voice.
May completely be music signal without any audio component.
Complex sound mixture like multi-singers or multi-speakers with multi-music sources.
Non-music and non-audio signals: like fan, motor, car, jet sounds, etc.
Audio signal that is a mixture of more than one speakers talking simultaneously at the same time [8].
Abnormal music can be single word cadence, human whistle sound, or opposite reverberation [4, 34, 35, 36, 37, 38].
The letters symbols used for writing are not adequate, as the way they are pronounced varies; for example, the letter “o” in English, is pronounced differently in words “pot” most“ and “one”. It is almost impossible to tackle the audio classification problem without first establishing some way of representing the spoken utterances by some group of symbols representing the sounds produced [39, 40, 41, 42, 43]. The phonemes in Table 1 are divided into groups based on the way they are produced [44], forming a set of
Vowels | Diphthongs | Fricatives | Plosives | Semivowels | Nasals | Affricates |
---|---|---|---|---|---|---|
h | b | a | ||||
h | b | a | ||||
h | b | sa | ||||
h | b | |||||
h | b | |||||
h | d | |||||
h | b | a | ||||
h | b | |||||
wh | b | |||||
h | ||||||
h | ||||||
th |
Phoneme categories of British English and examples of words in which they are used [44].
Since the range of sounds that can be produced by any system is limited [39, 40, 41, 42, 43, 44], the pressure in the lungs is increased by the reverse process. They push the air up the
A sonogram for the sentence “What can I have for dinner tonight?” [
The way that humans recognize and interpret audio signal has been considered by many researchers [1, 25, 39]. To produce a complete set of English vowels, many researchers have depicted that the two lowest formants are necessary, as well as that the three lowest formants in frequency are necessary for good audio intelligibility. As the number of formants increased, sounds that are more natural are produced. However, when we deal with continues audio, the problem becomes more complex. The history of audio signal identification can be found in [1, 25, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48].
There are two kinds of tone structures in music signal. The first one is a simple tone formed of single sinusoidal waveform, however, the second one is a more complex tone consisting of more than one harmonic [31, 49, 50, 51, 52]. The spectrum of music signal has twice the bandwidth of audio spectrum, and most of the power of audio signal is concentrated at lower frequencies. Melodists and musicians divide musical minor to eight parts and each part named octave, where each octave is divided into seven parts called tones [30]. For different instrument, a tempered scale is shown in Table 2. These tones, shown in Table 2, are named (Do, Re, Me, Fa, So, La and Se) or simply (A, B, C, D, E, F, and G). The tone (A1) at the first octave has the fundamental frequency of the first tone in each octave, i.e., every first tone in each octave takes the reduplicate frequency of the first tone of previous one, (i.e., A
A Hz | B Hz | C Hz | D Hz | E Hz | F Hz | G Hz |
---|---|---|---|---|---|---|
A1 27.5 | B1 30.863 | C1 32.703 | D1 36.708 | E1 41.203 | F1 43.654 | G1 48.99 |
A2 55 | B2 61.735 | C2 65.406 | D2 73.416 | E2 82.407 | F2 87.307 | G2 97.99 |
A3 110 | B3 123.47 | C3 130.81 | D3 146.83 | E3 164.81 | F3 174.61 | G3 196 |
A4 220 | B4 246.94 | C4 261.63 | D4 293.66 | E4 329.63 | F4 349.23 | G4 392 |
A5 440 | B5 493.88 | C5 523.25 | D5 587.33 | E5 659.26 | F5 698.46 | G5 783.9 |
A6 880 | B6 987.77 | C6 1046.5 | D6 1174.7 | E6 1318.5 | F6 1396.9 | G6 1568 |
A7 176 | B7 1975.5 | C7 2093 | D7 2349.3 | E7 2637 | F7 2793 | G7 3136 |
A8 352 | B8 3951.1 | C8 4186 |
Frequencies of notes in the tempered scale [3].
From Table 2, the highest tone C8 occurs at the frequency of 4186 Hz, which is the highest frequency produced by human sound system, which leads musical instrument manufactures to try their best to bound music frequency to human’s sound system limits to achieve strong concord [35, 53, 54]. In the real world, musical instruments cover more frequencies than audible band, which is limited to 20 kHz).
The concept of tone quality that is most common depends on the subjective acoustic properties, regardless of partials or formants and the production of music depends mainly on the kind of musical instruments [53, 54]. These instruments can be summarized as follows:
String instruments.
Brass instruments.
Woodwind instruments.
Percussion instruments.
Electronic organ.
The audio signal is a slowly time varying signal in the sense that, when examined over a sufficiently short period of time “between 5 and l00
An example of audio signal of specking the two-second long phrase “
Figure 10 is a typical example of music portion. It is very clear from the two spectrums in Figures 9 and 10 that we can distinguish between the two types of signals.
A 2-second long music signal: (a) time domain. (b) Spectrum. (c) Phase.
Figures 11 and 12 depict the evolutionary spectrum of two different types of signals, audio and music.
The spectrum of an average of 500 specimens: (a) audio, (b) music.
Evolutionary spectrum of an average of 500 specimens: (a) audio, (b) music.
Now, let us discuss some of the main similarity and differences between the two types of signals.
In the frequency domain, there is a strong overlapping between audio and music signals, so no ordinary filter can separate them. As mentioned before, audio signal may cover spectrum between 0 and 4 kHz with a dominant frequency of an average = 1.8747 kHz. However, the lowest fundamental frequency (A1) of a music signal is about 27.5 Hz and the highest frequency of the tone C8 is around 4186 Hz. The reason behind this is that musical instrument manufacturers try to bound music frequency to human’s sound limits in order to achieve a strong consonant and a strong frequency overlap. Moreover, music may propagate over the audible spectrum to cover more than the audible band of 20 kHz, with a dominant frequency of an average = 1.9271 kHz [25].
Table 3 summarizes the main similarity and differences between music and audio signals.
Key Difference | Audio | Music |
---|---|---|
|
| |
|
| |
|
|
The main differences between audio and music signals.
The main classification approaches will be discussed in this section. They can be categorized into three different approaches: (1) time domain approaches, (2) frequency domain approaches, and (3) time-frequency domain approaches. A two-level music and audio classifier was developed by El-Maleh [61, 62]. He used a combination of long-term features such as the variance, the differential parameters, the zero crossing rate (ZCR), and the time-averages of spectral parameters. Saunders [60] proposed another two-level classifier. His approach was based on the short-time energy (STE) and the average ZCR features. In addition, Matityaho and Furst [63] have developed a neural network based model for classifying music signals. Their model was designed based on human cochlea functional performance.
For audio detection, Hoyt and Wecheler [64] have developed a neural network base model using Fourier transform, Hamming filtering, and a logarithmic function as pre-processing then they applied a simple threshold algorithm for detecting audio, music, wind, traffic or any interfering sound. In addition, to improve the performance, they suggested wavelet transform feature for pre-processing. Their work is much similar to the work done by Matityaho and Furst’s [63, 64]. 13 features were examined by Scheirer and Slaney [65]. Some of these features were simple modification of each other’s. They also tried combining them in several multidimensional classification forms. From these previous works, the most powerful discrimination features were the STE and the ZCR. Therefore, the STE and the ZCR will be discussed thoroughly. Finally, the common classifiers of the audio and the music signals can be divided into the following approaches:
The ZCR algorithm [1, 34, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77]:
The standard deviation of first order difference of the ZCR.
The 3rd central moment of the mean of ZCR.
The total number of zero crossings exceeding a specific threshold.
The ANN (Artificial neural networks) [12, 49, 58, 63, 79, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120].
The Spectral Centroid.
The Spectral Flux Variance.
The Spectral Centroid Mean and Variance.
The Spectral Flux Mean and Variance.
The Spectrum Roll-Off.
The Signal Bandwidth.
The Spectrum Amplitude.
The Delta Amplitude.
The Cepstrum [122]:
The ZCR algorithm can be defined as the number of crossing the signal the zero axis within a specific window. It is widely used because its simplicity and robustness [34]. We may define the ZCR as in the following equation.
where
The ZCR properties can be summarized as follow.
The dominant frequency of a pure sinusoid is the only value in the spectrum. This value of frequency is equal to the ZCR of the signal in one period. If we have a non-sinusoidal periodic signal, its dominant frequency is frequency with the largest amplitude. The dominant frequency (
where
Since
where
Assuming that the time period between any two samples is normalized to unity, the derivative
Now, let us define the ZCR of the
A signal is said to be purely periodic if and only if.
Using Eq. (6), it was found that music is more periodic or than audio [44, 45, 46, 47, 55, 56, 57, 130].
It was found that the variation of the ZCR is more discriminative than the exact ZCR, so the RHZCR can be considered as one feature [78]. The RHZCR is defined as the ratio of the number of frames whose ZCR are above 1 over the average ZCR in one-window, and can be defined as follow.
where
Music and audio sharing some values [
The amplitude of the audio signal varies appreciably with time. In particular, the amplitude of unvoiced segments is generally much lower than the amplitude of voiced segments. The STE of the audio signal provides a convenient representation that reflects these amplitude variations. Unlike the audio signal, since the music signal does not contain unvoiced segments, the STE of the music signal is usually bigger than that of audio [60]. The STE of a discrete-time signal
where STEs in Eq. (9) is the total energy of the signal. The average power of
Signals can be classified into three types, in general: an energy signal, which has a non-zero and finite energy, a power signal, which has a non-zero and finite energy, and the third type is neither energy nor power signal, see Table 4. Now, let us define another sequence {
0 < | Transient | |
Finite Sequence | ||
0 < | Constant | |
Periodic | ||
Stochastic | ||
Zero | ||
Blow up |
Types of signals.
where
The silence and unvoiced period in audios can be considered a stochastic background noise. Now, let us define
The long-term feature of {
The long-term average, when applied to energy signals, will have zero values, however, it is appropriate for power signals. Eq. (13) can be re-written as follow.
Resulting a family of mappings. If each member of the family is selected to be a
where
Define a frame as in Eq. (11).
Apply the long-term feature transformation to the frame sequence as in Eq. (16).
As done in the ZCR, the variation is selected [33]. Here, the LSTER is used to represent the variation of the STE. LSTER is defined as the ratio of the number of frames whose STE are less than 0.5 times of the average STE in a one-second window, as in Eq. (17).
where.
Figure 14 shows the preprocessing flow on
The preprocessing using the +ve derivative before evaluating the ZCR.
This pre-processing increased the ZCR of music and reduced the ZCR of the audio with the expenses of some delay. The averages of the ZCR in speech, mixture, and music are shown in Figure 15, after applying the +ve derivative of order 50.
The average ZCR of speech, mixture, and music, after pre-processing with the +ve derivative [
The ANN approach is a multipurpose technique that was used for implementing many algorithms [14, 36, 63, 79, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 110, 125], especially in classification issues [16, 49, 107, 108, 109, 110, 111, 119, 120, 131, 132]. A multi-layer ANN approach was used in many classification tools since it can represent nonlinear decision support systems.
This feature characterizes the change in the shape of the spectrum so it measures frame-to-frame spectral difference. Audio signals go through less frame-to-frame changes than music. The spectral flux values in audio signal is lower than that of music.
The spectral flux, sometimes called the
where
where
and
3D histogram normalized features (the mean and the variance of spectral flux) of: (a) music signal, (b) audio signal [
Rossignol and others [133] have tested three classification approaches to classify the segments. They used the k-nearest-neighbors (kNN) with
Training | Testing | Cross-validation | |
---|---|---|---|
GMM | 8.0% | 8.1% | 8.2% |
kNN | X | 6.0% | 8.9% |
ANN | 6.7% | 6.9% | 11.6% |
Percentage of misclassified segments [133].
In the frequency domain, the mean and variance of the spectral centroid feature describes the center of frequency at which most of the power in the signal is found. In audio signals, the pitches of the signals are concentrated in narrow range of low frequencies. In contrast, music signals have higher frequencies that result higher spectral means, i.e., higher spectral centroids. For a frame at time
where
Training | Testing | Cross-validation | |
---|---|---|---|
GMM | 7.9% | 7.3% | 22.9% |
kNN | X | 2.2% | 5.8% |
ANN | 4.7% | 4.6% | 9.1% |
Percentage of misclassified segments [133].
Audio signal has an energy peak centered on the 4 Hz syllabic rate. Therefore, a 2nd order band pass filter is used, with center frequency of 4 Hz. Although audio signals have higher energy at that 4 Hz, some music bass instruments was found to have modulation energy around this frequency [65, 133].
In the frequency domain, the roll-off point feature is the value of the frequency that has 95% of the power of the signal. The value of the roll-off point can be found as follow [65, 133].
where the left hand side of Eq. (23) is the sum of the power at the frequency value
The cepstrum of a signal can be defined as the inverse of the DFT of the logarithm of the spectrum of a signal. Music signals have higher cepstrum values than that of speech ones. The complex cepstrum is defined in the following Equation [122, 123, 124].
and then.
where
Table 7 summarizes the percentage error of a simulation done per each feature. Latency refers to the amount of past input data required to calculate the feature.
Features | The 4 Hz Mod Energy | The Low Energy | The Roll off | The Roll off Var | Spec Centroid | Spec Centroid Var | The Spec Flux | Spec Flux Var | The ZCR | The Var of the ZC Rate | The Cepstrum Resid | Cepstrum Res Var | The Pulse Metric |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 sec | 1 sec | 1 frame | 1 sec | 1 frame | 1 sec | 1 frame | 1 sec | 1 frame | 1 sec | 1 frame | 1 sec | 5 sec | |
12 +/−1.7% | 14 +/−3.6% | 46 +/− 2.9% | 20 +/− 6.4% | 39 +/− 8.0% | 14 +/− 3.7% | 39 +/− 1.1% | 5.9 +/− 1.9% | 38 +/− 4.6% | 18 +/− 4.8% | 37 +/− 7.5% | 22 +/− %5.7 | 18 +/− %2.9 |
Latency and univariate discrimination performance for each feature [65].
Scheirer and Slaney [65] have evaluated their models using 20 minutes long data sets of music and audio. Their data set consists of 80 samples, each with 15-second-long audio. They collected their samples using a 16-bit monophonic FM tuner with a sampling rate of 22.05 kHz, from a variety of stations, with different content styles and different noise levels, over a period of three days in the San Francisco Bay Area. They also claimed that they have audios from both male and female.
They also recorded samples of many types of music, like pop, jazz, salsa, country, classical, reggae, various sorts of rock, various non-Western styles [29, 65]. They also used several features in a spatial partitioning classifier. Table 8 summarizes their results.
Subset | All features | Best 8 | Best 3 | VS Flux only | Fast 5 |
---|---|---|---|---|---|
Audio % Error | 5.8 +/− 2.1 | 6.2 +/− 2.2 | 6.7 +/− 1.9 | 12 +/− 2.2 | 33 +/− 4.7 |
Music % Error | 7.8 +/− 6.4 | 7.3 +/− 6.1 | 4.9 +/− 3.7 | 15 +/− 6.4 | 21 +/− 6.6 |
Total % Error | 6.8 +/− 3.5 | 6.7 +/− 3.3 | 5.8 +/− 2.1 | 13 +/− 3.5 | 27 +/− 4.6 |
Performance for various subsets of features.
The features used in Best 8 are the plus the 4 Hz modulation, the variance features, the pulse metric, and the low-energy frame [80, 134]. In the Best 3, they used the pulse metric, the 4 Hz energy, and the variance of spectral flux. In the Fast 5, they used the 5 basic features. From results shown in Table 8, we conclude that it is not necessary to use all features in order to have a good classification, so in real time a good performance system may be found using only few features. A more detailed discussion can be found in [29, 65, 80, 134].
The spectrogram is an example of time-frequency distribution and this method was found to be a good classical tool for analyzing audio signal [13, 19, 86, 127]. The spectrogram (or sonogram) of a signal
where
The method of spectrogram can be used in discriminating audio from music signal, however, it may have a high percentage error. That is because it depends on the strength of the frequency in the tested samples. Figure 17 depicts two examples of spectrograms of audio and music signals.
(a) Audio spectrogram, (b) music Spectrum.
The spectral representation of a stationary signal may be viewed as an infinite sum of sinusoids with random amplitudes and phases as described in Eq. (27).
where
and
where
where
and the instantaneous power of
and then, the Wold-Cramer ES is defined as
The ES
(a) The ES of a music signal, (b) the ES of an audio signal [
Since the separation of audio and music signals is more complicated than classification, in this section we will introduce only two approaches [7, 8, 9, 10, 11, 12, 13, 22, 76, 77, 86, 135]. The first approach is the approach of independent component analysis (ICA) with ANN. The second classifier is the pitch cancelation approach. A block diagram of a classifier integrated with a separator is depicted in Figure 19.
A block diagram of a classifier integrated with a separator.
In [13, 20, 21, 127, 136], Wang and Brown proposed a model for audio segregation algorithm. His model consists of preprocessing using cochlear filtering, gammatone filtering, and correlogram forming autocorrelation function and feature extraction. The impulse response of the gammatone filters is represented as.
where
4th order impulse response Gammatone system: (a) In time domain when
A block diagram of Wang and Brown model.
Wang and Brown model has some drawbacks. The first drawback is its complexity. Their model needs a high specification hardware to perform the calculations. In [20], Andre reported that Wang and Brown model needs to be improved. The ICA method can be used for separation if two sources of mixture are available assuming that the two signals from the two different sources are statistically independent [66, 74, 75, 121, 137]. In [19], Takigawa tried to improve the performance of W & B model. He used the short time Fourier transform (STFT
The pitch cancelation method is widely used in noise reduction. A good try to separate two talkers speaking simultaneously at similar intensities in a single channel, or by other words, separation of two talkers without any restriction was introduced by Stubbs [8]. For a certain person, the letters A and R have lot of consonant. These consonants, in the frequency domain, have low amplitudes, however, they appear as long pitch peak in the cepstrum domain. If these consonants are deleted by replacing the five-cepstral samples centered at the pitch peak by zeros, the audio segment may be attenuated or distorted completely. A typical example of the cepstrum of two audio and music signals is depicted in Figure 22 for 5 seconds signals. The logarithmic effect will increase low amplitude reduce high one, and the values near zero will be very large after the logarithm.
(a) A typical 5 seconds audio signal in cepstrum domain, the pitch peak appears near zero. (b) a typical 5 seconds music signal in cepstrum domain.
In this chapter, a general review of the common classification and separation algorithms used for speech and music was presented and some were introduced and discussed thoroughly. The approaches dealt with classification were divided into three categories. The first category included most of the real-time approaches. In the real-time approaches, we introduced the ZCR, the STE, the ZCR and the STE with positive derivative, with some of their modified versions, and the neural networks. The second category included most of the frequency domain approaches such as the spectral centroid and its variance, the spectral flux and its variance, the roll-off of the spectrum, the cepstral residual, and the delta pitch. However, the last category introduced two time-frequency approaches, mainly the spectrogram and the evolutionary spectrum. It has been noticed that the time-frequency classifiers provided an excellent and a robust discrimination result in discriminating speech from music signals in digital audio. Depending on the application, the decision of which feature should be chosen is selected. The algorithms of the first category are faster since the processing is made in the real time; however, those of the second one are more precise. The time-frequency approaches has not been discussed thoroughly in literature and they still need more research and elaboration. Lastly, we may conclude that many classification algorithms were proposed in literature, however, few ones were proposed for separation. The algorithms introduced in this chapter can be summarized in Table 9.
Approaches | Time domain | Frequency domain (Spectrum) | (Cepstrum) | Time-Frequency domain | |
---|---|---|---|---|
ZCR | Spectral Centroid | Cepstral Residual | Spectrogram (Sonogram) | |
STE | Spectral Flux | Variance of the Cepstral Residual | Evolutionary Spectrum | |
Roll-Off Variance | Spectrum Roll-Off | Cepstral feature | Evolutionary Bispectrum | |
Pulse Metric | Signal Bandwidth | Pitch | ||
Number of Silence | Spectrum Amplitude | Delta Pitch | ||
HMM | Delta Amplitude | |||
ANN |
Summary of the classification and separation algorithms.
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He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"414880",title:"Dr.",name:"Maryam",middleName:null,surname:"Vatankhah",slug:"maryam-vatankhah",fullName:"Maryam Vatankhah",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Borough of Manhattan Community College",country:{name:"United States of America"}}},{id:"414879",title:"Prof.",name:"Mohammad-Reza",middleName:null,surname:"Akbarzadeh-Totonchi",slug:"mohammad-reza-akbarzadeh-totonchi",fullName:"Mohammad-Reza Akbarzadeh-Totonchi",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Ferdowsi University of Mashhad",country:{name:"Iran"}}},{id:"414878",title:"Prof.",name:"Reza",middleName:null,surname:"Fazel-Rezai",slug:"reza-fazel-rezai",fullName:"Reza Fazel-Rezai",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"American Public University System",country:{name:"United States of America"}}},{id:"302698",title:"Dr.",name:"Yao",middleName:null,surname:"Shan",slug:"yao-shan",fullName:"Yao Shan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Dalian University of Technology",country:{name:"China"}}},{id:"125911",title:"Prof.",name:"Jia-Ching",middleName:null,surname:"Wang",slug:"jia-ching-wang",fullName:"Jia-Ching Wang",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"National Central University",country:{name:"Taiwan"}}},{id:"357085",title:"Mr.",name:"P. Mohan",middleName:null,surname:"Anand",slug:"p.-mohan-anand",fullName:"P. Mohan Anand",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"356696",title:"Ph.D. Student",name:"P.V.",middleName:null,surname:"Sai Charan",slug:"p.v.-sai-charan",fullName:"P.V. Sai Charan",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Indian Institute of Technology Kanpur",country:{name:"India"}}},{id:"357086",title:"Prof.",name:"Sandeep K.",middleName:null,surname:"Shukla",slug:"sandeep-k.-shukla",fullName:"Sandeep K. 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