Assistive technologies have been proposed for the locomotion of people with spinal cord injury (SCI). One of them is the neuroprosthesis that arouses the interest of developers and health professionals bearing in mind the beneficial effects promoted in people with SCI. Thus, the first session of this chapter presents the principles of human motility and the impact that spinal cord injury causes on a person’s mobility. The second session presents functional electrical stimulation as a solution for the immobility of paralyzed muscles. It explains the working principles of constituent modules and main stimulatory parameters. The third session introduces the concepts and characteristics of neural prosthesis hybridization. The last two sessions present and discuss examples of hybrid neuroprostheses. Such systems employ hybrid assistive lower limb strategies to evoke functional movements in people with SCI, associating the motor effects of active and/or passive orthoses to a functional electrical stimulation (FES) system. Examples of typical applications of FES in rehabilitation are discussed.
Part of the book: Prosthesis
This chapter introduces the anatomy and physiology of the respiratory system, and the reasons for measuring breathing events, particularly, using wearable sensors. Respiratory monitoring is vital including detection of sleep apnea and measurement of respiratory rate. The automatic detection of breathing patterns is equally important in other respiratory rehabilitation therapies, for example, magnetic resonance exams for respiratory triggered imaging, and synchronized functional electrical stimulation. In this context, the goal of many research groups is to create wearable devices able to monitor breathing activity continuously, under natural physiological conditions in different environments. Therefore, wearable sensors that have been used recently as well as the main signal processing methods for breathing analysis are discussed. The following sensor technologies are presented: acoustic, resistive, inductive, humidity, acceleration, pressure, electromyography, impedance, and infrared. New technologies open the door to future methods of noninvasive breathing analysis using wearable sensors associated with machine learning techniques for pattern detection.
Part of the book: Wearable Devices