A Single-Layer Flat-Coil-Oscillator-Based Technology as a Highly Sensitive Promising Detector for State-of-the-Art “Cognitive Radio Systems”

Abstract

A low-power stable self-oscillator with a single-layer flat coil was proposed by us in the late 1990s as a sensitive measurement method. It soon became a technological platform called a single-layer flat-coil-oscillator technology (SFCO technology). Two classes of sensors were designed based on SFCO platform: with and without the mechanical vibrating system. Both of them have already demonstrated their capabilities to solve problems of low-temperature experimental physics. This method also helped to increase the resolution of detectors in seismology/geophysics and develop diagnostic techniques for use in physiology and biophysics. We also showed the feasibility of using these novel SFCO sensors for noncontact far-field nondestructive scanning of various structures and media. SFCO sensors are characterized by high sensitivity and the ability to detect mechanical vibration signals in an unprecedentedly wide frequency range – from quasi-stationary movements to ultrasonic frequencies. Physical principles of operation of SFCO sensors are based on the change in frequency and/or amplitude of the measuring oscillator. In this Chapter, we discuss the principles of operation of SFCO sensors and numerous measurement data obtained by these sensors in different fields of science and technology. The wide potential of the novel SFCO sensors for medical diagnostics will also be discussed.

1. Introduction

A stable low-power radiofrequency (RF) self-oscillator with an unusual single-layer flat pick-up coil activated by a tunnel diode (TD) was proposed by us in the late 1990s in Armenia as a highly sensitive advanced measuring method [1]. Low-temperature meters based on this method have helped us to solve topical problems of experimental physics and engineering. Particularly, they made it possible to discover and study some subtle physical properties [2, 3, 4, 5] and refine the “magnetic-phase” diagram [6], as well as the mechanism of superconductivity [7] in high-T_c superconductors. Soon this method was developed into a powerful technology platform called a single-layer flat-coil-oscillator (SFCO) technology. It helped to increase the resolution of detectors in seismology/geophysics [8, 9, 10, 11] and develop research and diagnostic techniques for use in physiology and biophysics [12, 13, 14, 15]. We have also recently shown the feasibility of using SFCO method-based sensors for noncontact far-field nondestructive scanning of various structures and media [16].

2. A single-layer flat-coil-oscillator sensors and their classification

All the varieties of SFCO sensors which have been created so far can be divided into two main classes (Figure 1). Their basic difference is the presence in the sensors of the first class, the mechanical vibrating system with a normal-conducting plate attached to it, suspended above the flat surface of the measuring (pick-up) coil.

Figure 1.

Classes of the SFCO sensors and their main varieties.

The class I is the sensors with a mechanical vibrating system [8, 9, 10, 11, 12, 13, 15] and includes several types: the position sensor (position, speed, and acceleration sensors), vibration sensor (vibraphone and seismic sensor), the acoustic sensor (microphone and hydrophone) and the vibroacoustic SFCO magnetometer. The class II involves the sensors without the vibrating system and currently is presented by four types: the radiofrequency ‘magnetic field’ probe (MF probe) [14, 16], the noninertial (due to low mass) thermal sensor (with ∼1 μK extremely-high resolution) [2, 4], the nano-watt absorption meter (quality-factor meter – Q-meter) [5, 6], and the MF probe-based SFCO magnetometer [3, 7].

3. Physical principles of operation of SFCO sensors: Their advantages

Physical principles of operation of the SFCO sensors are based on changes in frequency and/or amplitude of the measuring oscillator. In sensors with the mechanical vibration system, the main measured quantity is the frequency shift (see Figure 3 in Ref. [10] or Figure 1 in Refs. [3, 4]) caused by deformation of the RF electromagnetic field lines (F ∼ 10–50 MHz) near the flat surface of the measuring oscillator coil (in response to the approach/removal of the normal-metallic (e.g., copper) plate of the vibrating system [8, 9, 10, 11, 12, 13, 15]) due to shielding Eddy currents induced by the same RF field in the plate (see Figure 2A and B). Note that the sensitivity (or resolution) of SFCO sensors exponentially drops from the rising distance between the coil plane and the metallic plate of the vibrating system [3] (Figure 2C).

Figure 2.

Principle of operation of SFCO sensors with mechanical vibration system (Class I sensors): A – Deformation of RF magnetic field lines around the coil when metallic plate approaches/moves away; B – Schematic graph of the frequency shift of the self-oscillator as distance, d, between the coil and metallic plate changes; C – Dependence of the sensitivity of Class I SFCO sensors on the distance between the coil and the metallic plate of the vibrating system (more info see in [3]).

In order to simplify the understanding of drawings in the further presentation, it is just the right moment to note that, as a rule, the SFCO technology-based devices consist of two self-oscillators (Figure 3 in Ref. [10], or Figure 1 in Refs. [3, 4]). One of them is the measuring oscillator (at the flat-coil surface of which an object under study is located), and the other − the reference one. Such a design of the sensors “avoids” device effects and correlated noises and simplifies the electronics, increasing the measurement accuracy. Based on the above, the ordinates of the Figures here and below will show not the frequency shift of the measuring oscillator but the shift in the difference between the frequencies of the reference and measuring oscillators, namely δ(ΔF) = δ(F_ref − F_meas). At the same time, the parameters of the reference oscillator remain unchanged during all measurements.

Figure 3.

Changes in frequency of the measuring oscillator for the I-st and II-nd class SFCO sensors: A – Demonstration of the principle of operation of the I-st class SFCO sensors. Copper plate approaches the coil, then moves away, being in its RF magnetic field; B – Demonstration of the principle of operation of the II-nd class SFCO sensors (e.g., “magnetic field” probe). Placing/removal of the empty spectrophotometric plastic cuvette into/from the RF magnetic field of the coil (solid red curve), and the same experiment with distilled water (dashed blue curve).

For the SFCO sensors of the II-nd class (e.g., the MF probe, the Q-meter, the MF probe-based SFCO magnetometer, etc.), the measured values can be both the frequency and amplitude of the measuring oscillator. However, the reasons for changing the frequency and/or amplitude of the oscillator may differ from the case of the I-st class sensors. In studies of dielectric media (Figure 3), one of the most probable mechanisms should be considered absorption of detecting coil’s RF field’s power by the medium under the study due to the ‘imposed’ reorientation of the dipole structures of the medium by the RF magnetic field of the oscillator. Another reason is the absorption of the energy of the measuring RF field of the coil by induced Eddy currents due to setting in motion even the small amount of free charges in a dielectric media. Other factors also can result in changes in the frequency/amplitude of the oscillator, noticeable by so much sensitive technique. And, what is important, even weak absorption of the coil’s RF power can be detected not only in the “amplitude” curves but also at “frequency” measurements (although with a noticeably lower resolution). An experimental confirmation of this (with nano-watt resolution) can be found in Figures 3 and 4 of Ref. [5]. The peculiarities detected there on the “frequency” curves are due to known dependence of the radio-technical circuit’s resonant frequency on its Q-factor value by F = 1/(2π√LC)⋅[1-ω₀L / (Q ⋅ |R_n|) + ···] [17]. Here R_n is the tunnel diode’s negative-differential resistance and ω₀ = 1/√LC.

Figure 4.

Comparison of the SFCO sensors (the blue and yellow curves) with contemporary microphones (gray and magenta curves). This figure demonstrates the huge advantage (in terms of detection bandwidth) of class II SFCO sensors (e.g., RF MF probes) over class I SFCO sensors and the modern microphones.

With a sufficient approaching of the copper plate (with a thickness greater than the depth of the “skin” layer of this material at room temperatures ∼30–50 μm), oriented parallel to the surface of the MF probe, a frequency shift of the measuring oscillator is registered relative to the initial level (that corresponds to the fragment a–b in Figure 3A). At the very beginning of the approach of the copper plate to the surface of the probe (so far, the plate is at a distance greater than some critical distance), the shielding power of Eddy currents induced by the RF field of the probe in the plate is still insufficient to deform force lines of the testing field of the probe [3, 14, 16]. Although the Eddy currents form from the very beginning, their density increases as the metallic plate approach the probe, resulting in an inevitable increase in the energy required for their formation, which is absorbed from the RF power of the measuring field of the probe. As a result, the frequency of the measuring oscillator (F_meas) decreases in this phase [3] (the b–c fragment in Figure 3A). Then, starting from a certain distance from the probe’s surface, a further approach of the metallic plate results in a much stronger effect, in a growing shielding of the flat-coil-based MF probe’s RF field by the rising Eddy currents, resulting in a steep increase in the frequency (F_meas) of the measuring oscillator (the c–d fragment in Figure 3A). When the copper plate vertically moves away from the probe surface, the frequency shifts in the reverse sequence (fragments e–f and f–g in Figure 3A). The steepness of described changes depends on the speed of the approaching and removal of the plate. The stated laws underlie the principle of operation of the I-st class SFCO sensors [3], in which the metallic plate is a part of the vibrating system and is located at a close distance from the surface of the pick-up coil (Figure 2A) (as a rule vibrating in a relatively narrow corridor not exceeding tens of micrometers). When the metallic plate is stationary, the measuring oscillator frequency (F_meas) is fixed at a certain value (d–e section in Figure 3A), determined by the distance between the metallic plate and the surface of the measuring flat coil. The described features allow us to consider the SFCO sensor of the I-st class as a position sensor. And therefore, high-resolution velocity meters and accelerometers can also be successfully created on their basis.

To clarify the possibility of recording the dielectric characteristics of objects and media, the experiments were performed using the plastic cuvettes of spectrophotometers. When an empty cuvette was placed near the surface of the measuring coil (the probe), a certain shift of the frequency was registered upward by ∼6.7 kHz (Figure 3B, the solid red curve). In the magnetic field of the probe, a same cuvette filled with water for injection resulted in a more than sevenfold increase (∼ 57 kHz) in the frequency (Figure 3B, dashed blue curve). In fact, the RF magnetic field of the MF probe passing through the plastic walls of the empty cuvette, which is a dielectric, results in the reorientations of its dipoles. This process proceeds under conditions of absorption of a certain energy, which determines the frequency shift. A cuvette filled with water absorbs a much larger fraction of the power of the RF magnetic field of the probe because there are a huge number of reorienting dipoles in the water column (each water molecule is an elementary dipole). The total absorbed power of the RF magnetic field is the sum of the energies needed to reorient the dipole structures of the water molecules on the one hand, and the walls of the cell, on the other. As a result, the greater the absorbed energy of the RF field, the greater the shift in the frequency. Conventional measurements of dielectric properties of water, aqueous solutions, and body fluids in vitro (outside a living organism) are known as a dielectrometry [18], or a dielcometry [19], and are performed using C- and L-cells. Our method of registration of signals by the use of a RF SFCO probe strongly differs from the above-mentioned methods (the difference was discussed in detail in [14]). In an SFCO measuring method frequency of the oscillator (probe) dynamically changes in accordance with a relation F = A ⋅ [1-B /Q + ···] (A and B are constants defined in the above formula). These changes are due to the absorption of the part of coil’s electromagnetic field’s probing energy as a result of dynamic processes occurring in the probed medium/structure (leading to changes in the coil’s loaded Q-factor value), accompanied by the changes in dielectric and/or conductive properties of the object under study.

Summarizing the above, it should be emphasized that the highly sensitive SFCO measurement technology is based on a position sensor designed on the base of a low-power stable self-oscillator of the radiofrequency range (F ∼ 10–50 MHz) with an unusual single-layer flat receiving coil activated by a TD. Just this circumstance determines the potential ability to detect processes in an ultra-wide frequency range (from quasi-stationary to ultrasonic frequencies). However, this statement is true for the SFCO sensors of the II-nd class only (the yellow curve in Figure 4) that do not have a mechanical vibrating system. In contrast to this, the sensitive range (frequency bandwidth) of the I-st class sensor is limited by the characteristics of the vibrating system, which is an integral part of this class of sensors (see Figure 2).

To assess the ratio of the recorded signals and the level of intrinsic noise of the SFCO sensor (Figure 5), the power spectra of useful signals and background curves obtained using the Fourier transform were compared. The power of the background recording spectrum is negligibly small as compared with the power spectrum of the useful signal recorded at the carotid artery projection point (the ratio is approximately 1:500 for frequencies below 0.2 Hz, and ∼ 1:5000 for frequencies above 1 Hz). Peaks of respiration activity with subcomponents, as well as 1–4 harmonics of cardiac activity with subcomponents, are clearly distinguished in the presented fragment of the useful signal’s power spectrum.

Figure 5.

Power spectra of the SFCO vibration (or seismic) sensor: A – The spectrum of background activity, B – The signal spectrum from the carotid artery (the spectrum of sphygmogram). On the spectrum of the sphygmogram: A green square mark is the peak of the respiratory activity, and the blue round marks are four harmonics of the heart’s rhythm.

4. SFCO sensors with a mechanical vibration system

An important feature of SFCO sensors is the ability to combine several detectors in one case, which provides, for example, the detection of microseismic vibrations in three mutually perpendicular planes practically from the “same” point. In this regard, electro-motive force (EMF)-based sensors (“geophones”) have significant limitations that exclude the development of small-size 3D models in the same housing. Our previous works and related publications have evidently demonstrated the perspectives of using the first class SFCO sensors in various fields of science and technology. Below, in this section, we present and discuss the most important applications of the class I vibration and vibroacoustic SFCO sensors [8, 9, 10, 11, 12, 13, 15].

4.1 Human “foot-steps” detection by SFCO seismic sensors

One of the most promising applications of SFCO seismic sensors is the protection of borders, objects, and territories, as well as localization of the sources of the microseismic signals. Recently, we have published data on the dependence of the currently achieved maximum detection range of human “foot-steps” on the ground level of the environmental activity (GLEA) [11]. These results were achieved by the today’s SFCO seismic sensors. Future improvements may enhance the detection range even more. As seen in Figure 6, at enough low GLEA levels, both our 3D and 1D seismic SFCO sensors could reliably detect human “foot-steps” starting at a distance of 440 meters from the location of the sensors. Since the X-axis corresponds to the direction of movement and the Y-axis is perpendicular to it, the difference in measurement data for these axes of the 3D sensor becomes clear. The X-axis clearly reflects the steps (28 steps correspond to ∼20 meters of movement) and jumps of a person, while the Y-axis carries information regarding the GLEA. The Z-axes of both 3D and 1D sensors are the most sensitive for reliable detection of human “foot-steps” activity.

Figure 6.

Human steps and jumps registered by the 3D and 1D SFCO sensors: A – RAW signals of steps at different distances from the sensors’ location. B – Jumps and steps registered at distances of 340–440 m from the sensors’ location and ground level of environmental activity (GLEA) (green tracks). The X-axis is the time in seconds. The Y-axis is the frequency shift of the measuring oscillators in kilohertz.

Figure 7A shows car movement signals. The high sensitivity of our SFCO seismic sensors also ensured the detection of the soil micro-vibrations (indicated by arrows in Figure 7B) caused by a helicopter flying at a height of ∼50–70 meters. The closest distance in a straight line from the sensors’ location was ∼200 meters. The possibility of detecting soil anisotropy by the SFCO sensors was also convincingly demonstrated [11], which confirms the feasibility of their worldwide use in geology, geophysics, oil and gas exploration, etc.

Figure 7.

Signals registered by the SFCO seismic sensors during driving a car (A) and flying a helicopter (B). The X-axis is the time in seconds. The Y-axis is the frequency shift of the measuring oscillator in kilohertz.

4.2 Vibration sensors in biomedical investigations

Vibration sensors can also be effectively used in studying various problems in biology and medicine. Determination of the stiffness of the vascular wall or the so-called “biological age of the blood vessels” is of them. Currently, a number of methods are available to determine the state of the arterial wall: augmentation index evaluation, measurement of the pulse wave velocity, etc. [20, 21, 22, 23, 24]. Evaluation of the stiffness/elasticity of the walls of blood vessels and carotid pulse wave analysis is important in predicting possible problems in the cardiovascular system [25, 26, 27, 28, 29]. One of the most frequently used methods for assessing the features of the pulse wave is the curve fitting method by three Gaussians [30, 31]. Figure 8 shows the results of fitting of the carotid artery pulse curve (recorded by the SFCO vibration sensor) in norm (P1), in the presence of mild (P2) and more pronounced (P3) age-related changes in the vascular wall. As is seen, the normal pattern (P1) of the ratio of amplitudes and half-widths of the Gaussians changes with age, sex, and other anthropometric data. Both the amplitude and half-width ratios of all Gaussians of the P2 type pulse wave are changed due to the dominance of the second Gaussian, the reduction of the amplitude of the first, and an increase in the half-width of the third. However, in case of P2, we are still dealing with preclinical changes. The last case (P3) has a complicated medical history of hypertension, type II diabetes mellitus, and myocardial infarction followed by coronary stenting of the vessels. Only this case is distinguished by the most pronounced changes in the form of a reversal ratio of the amplitudes of the first and second Gaussians due to a decrease in the first and an increase in the second, a decrease in the half-width of the first and an increase in the half-widths of the second and third Gaussians.

Figure 8.

The results of the left carotid artery pulse wave fitting by three Gaussians registered by the new SFCO vibration sensor. P1–P3 – Pulse waves of three persons with different age, sex, and anthropometric data. The ratio of the amplitudes and half-widths of the Gaussians clearly reflects the elastic properties of the vascular wall reflecting the “biological age of the vessels”. P1 – Normal pattern and P2 – Abnormal pattern: Reversed ratio of the first and second Gaussians and/or increased half-width of the second and/or third Gaussian. Person 3 (P3) had a complicated medical history of hypertension, diabetes mellitus, and myocardial infarction. The X-axis is the time in seconds. The Y-axis is the frequency shift in kilohertz.

4.3 Vibroacoustic sensors in biomedical investigations

The imposition of a vibration sensor on the projection area of the common carotid artery makes it possible to register not only the arterial sphygmogram but also vibrations associated with the activity of the vocal cords during vocalization [13]. Such a possibility is also preserved when signals are detected by the SFCO vibroacoustic sensor (SFCO microphone). Since the frequency limits of these signals do not overlap (blue curves on the left and in the center of Figure 9), it becomes easy to separate them using digital filtering methods. Combined recording of voice parameters and cardiovascular activity may be of interest to specialists in human bio-identification. Due to the fact that a “stethophonendoscope” is not a precision measuring device (since its acoustic characteristics are not standardized and significantly depend on the manufacturer), the study of the features of conduction of endogenous sound vibrations to the surface of certain areas of the body are no less topical. For example, investigation of the conduction of vibrations to the surface of the chest may give us a more reasonable approach to vibroacoustic phenomena in lung and heart diseases [32, 33]. It should be emphasized that the signals associated with vocalization mainly reflect the fundamental frequency, which reflects the vibrations of the vocal cords and, accordingly, can serve as a tool for studying laryngeal problems in ENT practice for correction of certain disorders of sound production (vocalization) function and for objective classification of voice data, etc.

Figure 9.

Voice spectra of the letters “A”, “B”, “C”, and “D” were obtained by the SFCO vibroacoustic sensor (SFCO microphone) for two persons. Signals were detected from the projection area of the left common carotid artery. There are clear differences in the characteristics of the spectra. The example on the left also shows the presence in the low-frequency range of the spectrum (up to 2.5 Hz) of both the peak of respiratory activity and the harmonics of cardiac activity. The X-axis is the frequency in Hertz. The Y-axis represents counts.

The reproducibility of patterns during the verbalization of the first letters of the English alphabet is shown in the curves on the left side of Figure 10. At the same time, the patterns (“images”) of certain letters are quite specific (A and C), while the patterns of other letters (B and D) show similarity (see Figure 10, right column).

Figure 10.

Reproducibility of the “A”, “B”, “C”, and “D” letters pronunciation signals obtained by the vibroacoustic SFCO sensor (SFCO microphone) (left side) and the patterns (“images”) corresponding to each letter (right side).

The parameters of the sphygmogram of the common carotid artery detected by the SFCO vibroacoustic sensor (SFCOmicrophone) show a high sensitivity of the method to certain factors. Figure 11 clearly demonstrates the changes in the “Amplitude” of characteristic peaks after a five-minute load (the stress test) (Figure 11A, right) compared with the initial (baseline) parameters (Figure 11A, left). The red circles correspond to the rapid ejection phase and reflect ejection volume, while the blue circles correspond to the closure of the aortic valve at the end of the systolic phase and the beginning of diastole [34, 35]. If at rest, the range of vascular wall vibrations during one contraction was ∼10 kHz, then in 30 s after the stress test, this parameter was almost three times more (∼ 29 kHz). In this case, as expected, the increase in a swing is associated with the first component of the pulse wave corresponding to the phase of rapid blood ejection at the beginning of systole. At the same time, a remarkable increase in heart rate also takes place.

Figure 11.

Carotid pulse waves correlate with the functional state of the circulation system. A – The carotid pulse wave morphology (“Amplitude” and timing) at rest (left graph) and 30 s after the stress test (right graph). The X-axis is the time in seconds. The Y-axis is the frequency shift in kilohertz. B – Correlation between the data obtained by the SFCO vibroacoustic sensor (SFCOmicrophone) from the left carotid artery and ECG recorded simultaneously in case of a ventricular extrasystole. Upper graph – Carotid pulse wave registered by the SFCO vibroacoustic sensor. Bottom graph – The ECG. On both graphs, green marks correspond to normal contraction, red marks – To the extrasystole and blue marks – To the activity after “compensatory pause” (black lines under data curves on both graphs). Green lines under the upper data curve correspond to the normal diastolic phase after overloaded systolic volume. The X-axis is the time in seconds. The Y-axis is the frequency shift in kilohertz (upper graph) and the amplitude in microvolts (bottom graph).

Figure 11B shows regular changes in the amplitude-time parameters of the carotid artery sphygmogram in extrasystolic heart rhythm disturbances registered by the SFCO vibroacoustic sensor (upper curve). The electrocardiogram (bottom curve) is also presented to demonstrate the correlation of the data. For a better understanding of the specific changes in the recorded data, let us briefly dwell on the features of the physiology of such a state. Ventricular extrasystole (heart contraction outside the normal rhythm) is a type of cardiac arrhythmia with premature contractions of the heart ventricles [36]. The trigger for extrasystole is an ectopic focus of excitation in any area of the myocardium, which leads to an abnormal spread of this excitement and, accordingly, to a desynchronous, more or less ineffective involvement of the muscle fibers of the heart ventricles in the contraction process. As a result, the efficiency of blood ejection from the ventricles into the vascular bed sharply decreases, which is expressed in the “Amplitude” decrease of the first peak of the carotid artery pulsogram recorded by the vibroacoustic SFCO sensor (red circular marks in Figure 11B). In comparison with the “Amplitude” registered at normal systolic volume (green marks on upper graph), extrasystole on the ECG corresponds to a pulse wave with reduced amplitude due to the premature systolic volume (red marks on upper graph), while the pulse wave after extrasystole has a higher “Amplitude” (compare to normal), which reflects the overloaded systolic volume (blue marks on upper graph) due to so-called “compensatory pause” (black lines under data curves on both graphs) after extrasystole. The green lines under data curves correspond to a pause after normal systole.

Taking into account that the “Amplitude” of pulse curves reflects the pulse pressure in the vessel, the above-mentioned results allow us to state that long-term monitoring of carotid artery pulse activity by the vibroacoustic SFCO sensor (SFCOmicrophone), with appropriate signal processing, can effectively reflect the dynamics of central arterial pressure in relative units, the assessment of which is of great importance in cardiology practice [37, 38, 39]. In fact, these data serve as the basis for the development of the “cuff-less blood pressure monitor”.

5. Radiofrequency far-field “magnetic field” (MF) probe as a typical example of the SFCO sensor without the mechanical vibration system

As stated above, the uniqueness of SFCO RF MF probes is in the absence of the mechanical vibrating system in their design. This allows far-field, nondestructive, noncontact, noninvasive probing of structures and media [14, 16]. Probes created to date detect the presence of dielectric structures and/or media already at a distance of 15–20 cm, and there are many opportunities for their further improvement. Another advantage of SFCO MF probes is that they do not limit the frequency range of the sensor. Therefore, the spectral characteristics of SFCO probe signals reflect the real physical features of the studied structures and media.

5.1 Two components of the signals registered by the RF far-field MF probe

The signals recorded by the SFCO “magnetic field” probe have two components (Figure 12). As the probe approaches the surface of the body, a pronounced frequency shift of the measuring oscillator is observed due to the absorption of the energy of the field of the pick-up coil. From a certain level (value) of frequency, further changes are associated with physiological processes occurring in the probed area of the organ and/or tissue (blood circulation, pulsation of the tissue under study, etc.). Thus, by the use of the SFCO MF probe, the constant (a) and pulsatile (b) components of the signal are separated. The first mainly reflects the biophysical characteristics, while the second is associated with the functional features of the object under study.

Figure 12.

Two main components of the signal are registered by the SFCO “magnetic field” probe. The steady component (a) mainly reflects the biophysical properties of the tissue and/or structure under study, while the pulsatile components (b) are associated with physiological processes occurring in the scanning organ/region. The X-axis is the time in seconds. The Y-axis is the frequency shift in kilohertz.

5.2 Radiofrequency far-field MF probes for biomedical investigations

5.2.1 Study of dielectric properties of different tissue and media

A typical example of how much informative the constant (steady) component of MF probe’s signal is shown in Figure 13. It demonstrates the results of measuring the energy absorption of the probe magnetic field when various media are placed in front of the pick-up coil of the probe: an empty plastic spectrophotometric cuvette, a cuvette filled with distilled water and injection solutions of vitamins B12 (0.5 mg/ml) and C (1 ml of its 5% solution contains 50 mg ascorbic acid, 23.85 mg sodium bicarbonate, and 2 mg anhydrous sodium sulfite). Each tested material has its own magnitude of MF probe’s power absorption. The above data indicate the possibility of studying the dielectric and shielding characteristics of biological media “in vitro”.

Figure 13.

Steady part of the SFCO MF probe’s signal as a tool for “in vitro” study of the probe’s electromagnetic field’s power absorption by the distilled water and some vitamin solutions (B12 – 0.5 mg/ml, C – 5% solution). The first column shows the energy absorption level by the empty spectrophotometric plastic cuvette. At the top of each column, the values of mean and standard deviation of the power absorption are indicated. The Y-axis is the frequency shift in kilohertz.

Another example is shown in Figure 14. It relates to the detection of various pathological processes “in vivo”. Normally, there should be a symmetrical absorption of the testing electromagnetic field’s power on both sides of the probing (Figure 14A). In case of volumetric formations (3D lesions), an asymmetry in absorption levels of the testing RF field’s energy is revealed (Figure 14B). In a particular case, hearing impairment of the type of sensorineural hearing loss and right-sided acoustic neuroma were clinically verified by audiometry & subsequent MRI examination (red arrows). Histograms (bottom left) clearly show the asymmetry in pathology and its absence in the normal case. It is important to emphasize that with this method of examination, the asymmetry of the absorption of the RF testing field’s energy itself is more important than the value of the frequency shift. However, as enough data become available, the value of the frequency shift can also be important parameter, as the limit values of frequency shift for specific verified pathological processes (inflammatory processes, cysts, hematomas, abscesses, bone and glial tumors, etc.) will be clarified. Taking into account the short duration of the examination by SFCO MF probes, the safety, and informativeness of results, we can talk about a new valuable method for screening and assessing the condition of patients with craniocerebral injuries, volumetric processes (hematomas, tumors, abscesses, etc.).

Figure 14.

The constant (steady) part of the SFCO MF probe’s signal as a tool for “in vivo” screening of tissue and structure. The Probe’s RF field power absorption level in a healthy person (A) and in the case of right acoustic neuroma (B). On the middle top is the location of the probing zone (green square).On the bottom left is the diagram of probe electromagnetic field’s power absorption levels in norm (red columns) and right neuroma (blue columns). On the bottom right are MRI images. Red arrows show the location of acoustic neuroma.

5.2.2 Study of cardiovascular system

The informativeness of the pulsatile component of the SFCO MF probe signal is shown in Figure 15. It is important to emphasize that the registration of MF probe signals does not require careful preparation of the sensor application area (degreasing the surface, ensuring reliable contact, etc.). It is enough to fix the probe in the required area. In the simplest case, the subject can be seated on a chair with a mounted probe (lay on a mattress), and signals can be registered even through clothes (Figure 15). As can be seen from the Figure, three probes are placed in different areas: in the popliteal fossa (green mark and time and frequency tracks corresponding to it in color), on the back surface of the mid-thigh (blue mark and tracks) and in the buttock area (red mark and tracks). The signals registered in the first two areas by the MF probe with a flat-coil diameter of ∼8 mm correspond to the pulsation signals of the femoral artery, which can be seen both on the time curves (signal shape) and on the frequency spectrum of the signal (typical peaks of spectra corresponding to harmonics of heart contractions). Time graphs of signals from the buttocks area have a less clear pattern, although there is some regularity of fluctuations. This is due to the absence of large main vessels in this area and the presence of an extensive network of small vessels that provide blood supply to a sufficiently large muscle mass, as well as the use of an MF probe with a larger flat-coil diameter of ∼25 mm, covering a wider scan area with a corresponding moderate phase desynchronization of the signals. However, even with such a “degraded” signal pattern in the time domain, the frequency characteristics remain stable (all six harmonics of the heart beats are traced), and even a respiratory peak (0.2 Hz) appears in the signal spectrum. Moderate phase desynchronization is indicated by wider frequency ranges of half-widths of heart harmonics and their reduced power.

Figure 15.

Pulsatile component of the SFCO “magnetic field” probe signals registered from the thigh and buttock. A – Scheme of the sensor location and approximate diameter of the probes’ sensitive part (flat-coil size). B – Signals in the time domain and C – Signals in the frequency domain. The X-axis is the time in seconds (B) and frequency in Hz (C). The Y-axis is the frequency shift in kilohertz (B) and counts (C).

One of the most promising applications of SFCO RF MF probes is the ability to study the brain. For the electromagnetic field of a radiofrequency range, the bones of the skull are not an obstacle. They just absorb part of the testing field’s energy. Consequently, the perspectives of brain probing in any area of the convexital surface of the skull without the need for probing through the natural openings of the cranium are opening up – in contrast to ultrasound research methods. Registration of SFCO probe signals by a probe with a sensitive element diameter of ∼35 mm located in the area of the left auricle is shown in Figure 16A. For comparison, synchronous recordings of signals from the ipsilateral and contralateral carotid arteries by vibration and vibroacoustic SFCO sensors, respectively, as well as an electrocardiogram in the standard lead are presented. The shape of the probe signal correlates with the shape of the left common carotid artery signal recorded by the vibration SFCO sensor, differing only in a regular time delay due to the registration of pulse oscillations of the walls of the internal carotid artery, which lies rather deep in the temporal bone pyramid. The significant role of the internal carotid artery in the formation of the probe signal is confirmed by its topography in the temporal bone pyramid, where the artery forms a knee (at a depth of ∼60–70 mm from the surface of the auricle) and enters the cranial cavity. The probe signal represents the total activity of the filled triangular zone on MRI images. The probable deepest zone of signal registration is indicated by a blue mark.

Figure 16.

Pulsatile activity registered by the SFCO MF probe with a large sensitive element (∅ ∼35 mm) from different areas of the head. A – Scanning from the external ear. The signal pattern (red trace) is very similar to the signal registered by the vibration SFCO sensor from the left carotid artery (green trace). For comparison, synchronously recorded signals from the right carotid artery (blue trace registered by the vibroacoustic SFCO sensor) and ECG (orange trace) are also presented. B – Scanning from vertex. The top 2 traces are RAW and smoothed signals registered by 35 mm MF probe. For comparison, the blue trace reflects the activity of the left common carotid artery registered by the vibroacoustic SFCO sensor.

In the second case, the native and filtered signals of the SFCO MF probe located on the vertex and probing quite deep brain structures are presented (Figure 16B). Since the diameter of the measuring probe (∅ ∼35 mm) covers a rather large scanning area with no large-caliber arteries, the signals have a flattened, smoothed shape due to the phase asynchrony of the recorded pulse waves in small arterial vessels. Volumetric pulsation of the brain tissue itself also contributes to the formation of such a signal pattern. For comparison, the sphygmogram of the left common carotid artery (blue track) registered by the vibroacoustic sensor is also shown.

For convincing demonstration of the possibility of recording processes occurring in the depth of the cranium, the signals obtained from vertex by SFCO “magnetic-field” probe with a smaller sensitive element (coil ∅ ∼ 8 mm) are presented (Figure 17). The upper row of curves represents the recorded signals and the corresponding spectra after removing the constant component. The next row shows Signals reconstructed by adding some Intrinsic Mode Functions (IMF) obtained after Empiric Mode Decomposition (EMD) [40, 41] and their corresponding spectra. The recorded curves reflect the state of blood flow in the region of the brain tissue covered by the far-field MF probe (Figure 17, Signals). The modulating effect of respiratory (Figure 17, IMF 13, 14) and slower (Figure 17, IMF15) waves on the recorded activity should be pointed out. Reconstruction of activity by summing the IMF7–IMF12 clearly highlights vascular activity (Figure 17, curves IMF 7–12), reflecting the state of blood flow in the area under study. The spectra of the IMFs (Figure 17, IMF 7–15) allow tracking the frequency peaks of activity and, as seen from the Figure, also include slow components below respiratory modulations (below 0.2 Hz). This fact gives grounds to expect that a prolonged (about 5–7 minutes) registration of activity can provide information regarding the average characteristics of microcirculation in the scanned area of the brain tissue.

Figure 17.

Transcranial registration of signals from the vertex during probing by the SFCO MF probe with a small measuring flat-coil diameter flat-coil (∅ ∼8 mm). The upper row of curves shows the recorded signals and their corresponding spectra (Signal). The next row shows the signals reconstructed by summing the intrinsic mode functions (IMF 7-12) obtained after the empirical mode decomposition and their corresponding spectra. Below are some informative IMFs (IMF 7-15) and their spectra. The X-axis is the time in seconds for time domain graphs and frequency in hertz for frequency domain graphs, respectively. The Y-axis is the frequency shift in kHz for time domain graphs and counts for frequency domain graphs, respectively.

5.2.3 Study of functional state

The SFCO “magnetic-field” probe also allows monitoring the human functional state (Figure 18). In a calm waking state, pulse waves are registered in the rhythm of heartbeats (“Wakefulness” mark on the green background). With the onset of drowsiness, the pattern of the signals changes, and high-amplitude peaked oscillations of longer duration appear on the curve (“Drowsiness” mark on the orange background). Finally, with the onset of the light sleep phase, the amplitude and duration of the recorded oscillations increase sharply (“Light Sleep” mark on the red background). Slow waves during the last two phases reflect a progressive weakening of the control of muscle tone from the central nervous system. It is easy to imagine what valuable information can be obtained when monitoring a person during the execution of responsible work (air traffic controllers, nuclear power plant operators, machine operators, drivers, etc.), in intensive care and resuscitation units, or when detecting the veracity of the information provided, etc. At the same time, the lack of preparation stage for monitoring (skin treatment and application of sensors) provides stability to the psychoemotional state and prevents frustration.

Figure 18.

Monitoring of the human (animals) functional state by the radiofrequency SFCO “magnetic-field” probe. The explanations are in the above text.

5.3 Radiofrequency far-field MF probes as a tool for nondestructive scanning of objects and structures

Scanning of research objects was carried out by the SFCO “magnetic-field” probe with receiving flat coil (∅ ∼3 mm) fixed on a stable tripod, which allowed to adjust the sensor position in three coordinates to ensure parallelism of planes of the pick-up coil and the surface of the scanned object, as well as set the required distance (h) between the scanned object and the sensor. The distance h from the plane of the MF probe coil to the surface of the scanned object was 3–7 mm (depending on the size of the scanned object). The scanned object was fixed on a two-coordinate stage driven by two stepper motors with program control. In fact, the assembled scanning setup provided the movement of the scanned object along the “X” and “Y” axes, while the scanning detector (SFCO MF probe) was fixed along the “Z” axis at the required height from the surface of the object under study (Figure 19). The movement speed of the object relative to the scanning probe along the scanning track was 2 mm/sec, which, taking into account the sampling rate (1000 Hz), provided a resolution of 500 measurements in one millimeter. The consecutive scanning tracks were soft-shifted by 0.2 mm, forming a resolution of the scanned structure/object along the transverse axis of five measurements per 1 mm. The signals from the probe were fed to a special high-speed eight-channel frequency meter (SFFM-8, “PSI” LLC, Armenia). Then the measured data were transferred to a PC and recorded by a virtual instrument (program) developed by PSI in the LabView environment (NI, USA).

Figure 19.

Experimental setup for scanning of research objects.

The scanning of a complex structure sample (Figure 20) shows the high spatial resolution of the method used. Since the scanning area exceeded the width of the object during the lateral scanning, there were some scanning areas of a much less dense medium (“air”) on both sides of the object, corresponding to lower levels of the testing RF field’s power absorption. The “zoom-in”/exit of the “needle-shaped” sensitive zone of the MF probe scanner on the test object is accompanied by a sharp increase/decrease in the level of testing field power absorption, respectively, forms the side walls of the “well” in the image of the initial scanning signals. The passage of the sensitive zone (“tip”) of the scanner over the surface of the test-object forms the “bottom of the well”. Against this background, the structural features of the scanned area of the test sample are clearly traced. Both a large through hole with a diameter of 10 mm and 4 through holes with a diameter of 3 mm are visualized, as well as nonthrough holes with a diameter of 2.5 mm located between them (Figure 20). As can be seen, the level of probing RF field energy absorption is different for different holes. It is minimal for a large through hole with a diameter of 10 mm, significantly more for four through holes with a diameter of 3 mm (large triangular marks), and maximum for three nonthrough holes with a diameter of 2.5 mm (small triangular marks), but less than the level of field power absorption in intact (untreated) areas of the test-object corresponding to the “bottom of the well”. It follows from these data that both the diameter of the holes and the presence of a certain inhomogeneity in the scanned structure of the test object (in the case of scanning three nonthrough holes with a diameter of 2.5 mm, there is a four-millimeter layer of composite plastic at the bottom of the holes) significantly affect the level of energy absorption of the MF probe’s RF field.

Figure 20.

Maps of values of absorption of testing electromagnetic field’s power of the SFCO MF probe when scanning a sample of complex structure. On the top – A sample of complex structure, side view. On the bottom right – View the upper surface of a sample of complex structure. On the bottom left – Maps of values of RF field energy absorption. Ring marks indicate the points of through holes, circular marks indicate places of nonthrough (blind) holes. The X-axis represents the sample number. The Y-axis is the track number. The Z-axis is the energy absorption levels in arbitrary units. The vertical bar on the left shows the energy absorption levels of the measuring field in arbitrary units.

In the previous work [14], the possibility of detecting the dielectric, magnetic, and conductive (shielding) properties of biological tissues and media by the SFCO MF probe was shown, and the prospects of using these probes for biomedical research were justified. Based on these results, we attempted to scan biological tissues and media. The convenient place for scanning was the terminal and middle phalanges of II-IV fingers. The results of scanning after the digital signal processing are shown in Figure 21. The passage of the MF probe over the bone structures of the fingers is accompanied by the maximum energy absorption of the probe testing electromagnetic field. On the other hand, scanning the interdigital zones, in which the thickness of the soft tissue layer is small even when the fingers are close to each other, shows a low level of power absorption of the measuring probe. These data allow to state, that scanning by the SFCO MF probe is a new method for visualization of biological media and structures, based on the assessment of their dielectric, magnetic, and conductive characteristics at each scanning point due to changes in a frequency and/or amplitude of the scanning self-oscillator caused by the specific level of the energy (power) absorption of the radiofrequency SFCO “magnetic-field” probe.

Figure 21.

The 3D display of the dynamics of absorption of testing electromagnetic field’s power (energy) of the measuring SFCO MF probe when scanning the terminal phalanges of II-IV fingers (“magneto-densitometry”). The X-axis represents sample number. The Y-axis is the track number. The Z-axis is the power absorption levels in relative units. The vertical bar on the right represents absorption levels of the probing field in arbitrary units.

6. Conclusion

A low-power stable self-oscillator with a single-layer flat coil was proposed by us in the late 1990s as a sensitive measurement method. It soon became a Technological Platform called a single-layer flat-coil-oscillator technology (SFCO technology). Two classes of sensors were designed based on the SFCO platform: with and without the mechanical vibrating system. Both of them have already demonstrated their capabilities to solve problems of experimental physics. Particularly, they allowed studying fine properties and clarifying the mechanism of superconductivity in high-T_c superconductors. This method also helped to increase the resolution of detectors in seismology/geophysics and develop diagnostic techniques for use in physiology and biophysics. We also showed the feasibility of using these novel SFCO sensors for noncontact far-field nondestructive scanning of various structures and media. SFCO sensors are characterized by high sensitivity and the ability to detect mechanical vibration signals in an unprecedentedly wide frequency range – from quasi-stationary movements to ultrasonic frequencies. Physical principles of operation of SFCO sensors are based on the change in frequency and/or amplitude of the measuring oscillator. In SFCO sensors with a mechanical vibrating system, the measured effect is determined by the distortion of the MHz-range testing field’s configuration near the coil plane, leading to changes in the oscillator frequency. For SFCO sensors without the vibrating system the measured values can be both the frequency and amplitude of the measuring self-oscillator.

The results and data presented and discussed in this Chapter suggest that

1. SFCO measurement technology makes it possible to create sensors with unprecedentedly high resolution due to the unusual flat shape of the pick-up coil and high stability of its low-power measuring self-oscillator.

2. SFCO seismic sensors have the ability to detect various signals generated both on the surface and under the ground, as well as in the air. The record range for detecting human “foot-steps” puts these sensors in the “Must Have” category in the tasks of protecting borders, objects, and territories. The sensitivity of these sensors opens up new opportunities in geophysics, geological exploration and other fields of science and technology.

3. Vibration and vibroacoustic SFCO sensors are promising in terms of their use in medicine for diagnostics and dynamic monitoring of physiological processes. The functional state of the heart and vessels, cuff-less monitoring of blood pressure, the diagnosis of arrhythmias, and the functional state of the vocalization apparatus is a far from the complete list of possible applications.

4. Radiofrequency “magnetic field” probes, having unique features (noncontact nondestructive far-field probing, absence of the mechanical vibrating system in the sensor design, which avoids limitations of the frequency range of sensitivity, etc.), make it possible to study dielectric and shielding properties of scanned media, materials and structures (“magnetic defectoscopy”).

5. Ability of the SFCO “magnetic-field” probes to simultaneously measure two characteristics of objects under study (absorption and shielding properties) makes it possible to assess the biophysical properties of tissues, structures, and organs (“magnetic densitometry”) of humans and other biological objects (“steady component”), as well as the characteristics of the functioning of the cardiovascular system, microcirculatory, nervous and other body systems (“pulsatile component”).

6. Particularly attractive may be the possibility of scanning nerve tissues in the future with the SFCO “magnetic-field” probe through the bone structures of the skull. In fact, prospects are opening up for the use of such sensors in emergency care, as well as rapid brain screening in a number of pathological conditions with a portable technique.

Finally, in summary, we would like to emphasize that the mentioned numerous advantages of the Single-layer Flat-Coil-Oscillator-based innovative measurement technology may permit to apply it as a highly sensitive promising detector for many state-of-the-art “cognitive radio systems” in the future.

Acknowledgments

The authors express their deep gratitude to the management of PSI”(Precision Sensors & Instruments, LLC, Armenia — https://psi.am/) for providing SFCO sensors, counting and signal processing units with the appropriate software for the implementation of measurements and experiments presented in this Chapter.