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Role of Advanced Technologies in Gait Analysis and Its Importance in Healthcare
Published in Teena Bagga, Kamal Upreti, Nishant Kumar, Amirul Hasan Ansari, Danish Nadeem, Designing Intelligent Healthcare Systems, Products, and Services Using Disruptive Technologies and Health Informatics, 2023
Neha P. Sathe, Anil Hiwale, Archana Ranade
A force plate works on the princip;e of ground reaction force. The force plates are embedded in a rigid platform and analog to digital converted signals are recorded on a computer. Placement of a force plate beneath the walking area matters a lot. While recording the walk position of both legs on the force plate is essential for accurate data recovery, inappropriate placement of force plates may lead to collection of unsuitable data. To overcome the limitation of the motion capturing method, force plated or electromyography techniques are used. A combination of force plate technique and kinematic information retrieved through an optical motion capture system may provide kinetic information using inverse dynamics. Electromyography (EMG) is used to record the electrical activity generated by muscles and to study it. With development of a wireless EMG system, the involvement of EMG signal along with other sensors are providing complete system setup for gait recording.
Key human anatomy and physiology principles as they relate to rehabilitation engineering
Published in Alex Mihailidis, Roger Smith, Rehabilitation Engineering, 2023
Qussai Obiedat, Bhagwant S. Sindhu, Ying-Chih Wang
When a person attempts to move their body and muscles contract, an electromyography (EMG) measurement can be used to detect and record the electrical activity in muscles as a byproduct of contraction. An EMG is the summation of action potentials from the muscle fibers under the electrodes placed on the skin. The more muscles that contract, the greater the amount of action potentials recorded and the greater the EMG reading. Rehabilitation engineers developing an EMG-based orthosis system or exoskeleton technology for neuromotor rehabilitation now use such signals. For example, Yoshiyuki Sankai, professor of the Graduate School of Systems & Information Engineering at the University of Tsukuba, has developed the Hybrid Assistive Limb (HAL) powered exoskeleton in helping disabled and elderly people walk and is further modified for construction and other uses. Cyberdyne's HAL robot suit registers these EMG biosignals through a sensor attached to the skin of the wearer. Based on the signals obtained, the Cybernic Voluntary Control (CVC) analyzes the data, and the power unit moves the joint to support and amplify the wearer's motion (Sankai 2010). Alternatively, other devices were developed to apply artificial electrical stimulation in a precise sequence to activate the muscles. The NESS H200 Wireless Hand Rehabilitation System (Bioness Inc.) stimulates the appropriate nerves and muscles of the forearm and hand and helps the muscles to relearn, to respond to signals for movement (Mikołajewska and Mikołajewski 2012).
Smart Textile-Based Interactive, Stretchable and Wearable Sensors for Healthcare
Published in Suresh Kaushik, Vijay Soni, Efstathia Skotti, Nanosensors for Futuristic Smart and Intelligent Healthcare Systems, 2022
Abbas Ahmed, Bapan Adak, Samrat Mukhopadhyay
Electromyography (EMG) provides muscle function assessment by examining the electrical signals driven by the central nervous system to the muscles. By this technique, the electrical signals that occur during the contraction and relaxation of muscle cycles can be measured. Moreover, in clinical system, EMG is also utilized as a diagnostic tool for nerve and muscle injury. EMG analyzes electrical signals within the muscle with two electrodes (Acar et al. 2019). Importantly, myoelectric signals are found to be entirely localized on the skin surface over the muscle of interest. Generally, EMG electrode is smaller in size but creates higher skin-electrode impedance. Smart textile enabled EMG electrode can acquire data in a more realistic way, thus providing the proof-of-concept, facilitating the way of embedding new textile electrode. The wearable EMG acquisition with textile electrode has found many applications including muscle status tracking (Pino et al. 2018), rehabilitation (Guo et al. 2018), prosthetics (Farina et al. 2010), and running leggings for muscle fatigue detection (Shafti et al. 2017). Notably, two companies, namely Athos (Mad Apparel Inc., CA, US) and Myontec (Myontec Ltd., Kuopio, Finland), have already brought textile integrated EMG electrodes in markets focusing on athlete training.
A novel sEMG data augmentation based on WGAN-GP
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2023
Fabrício Coelho, Milena F. Pinto, Aurélio G. Melo, Gabryel S. Ramos, André L. M. Marcato
Over the years, several researchers and industries have developed techniques and equipment for assisting people with some level of amputation (Farina and Aszmann 2014), (Sun et al. 2021) and (Mendez et al. 2021). For instance, prostheses that detect electromyography signals (EMG) are one of the current solutions available in the market (Krasoulis et al. 2020). According to (Donati et al. 2019), EMG signals are defined as electric potential measured from cell interactions on the muscles when the limb is electrically or neurologically activated. Therefore, EMG signal recognition systems have become an important research topic, as shown in the works of (Naik et al. 2017) and (Shi et al. 2018). It is possible to detect electromyographic signals by including needles (nEMG) inside the muscles. This technique is considered invasive and requires medical procedures for signal extraction. A non-invasive way to detect an EMG signal is from electrode sensors located on the skin surface. Therefore, this technique was named sEMG (Fattah et al. 2017).
Classification of forearm EMG signals for 10 motions using optimum feature-channel combinations
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2021
Muhammad Shahzaib, Sadia Shakil, Sajid Ghuffar, Moazam Maqsood, Farrukh A. Bhatti
Electromyography (EMG) is the evaluation of electrical activity of muscles. The EMG signal was first recorded by Raez et al. (2006) in 1890, who also introduced the term “Electromyography”. EMG signal is a very good indicator of the neuromuscular function of the body. EMG-based techniques are widely used in several medical applications (Elamvazuthi et al. 2015), such as, for controlling prosthetic limbs (Krasoulis et al. 2020) and for studying muscular functions, for example, muscular dystrophy. EMG recordings are typically made with electrodes attached to the skin over a muscle. An electrode covers hundreds of Motor Units (MU), where each MU is composed of hundreds of muscle fibres (Konrad 2005). The MU fires pulses due to the polarization and repolarization in the muscle fibre membrane (caused due to its contraction or activation) known as Action Potential (AP). Consequently, an EMG signal is the combination of many overlapping Motor Unit Action Potentials (MUAP) of different frequencies.
A Functional BCI Model by the P2731 working group: Physiology
Published in Brain-Computer Interfaces, 2021
Ali Hossaini, Davide Valeriani, Chang S. Nam, Raffaele Ferrante, Mufti Mahmud
Before discussing direct stimulation of the central nervous system we should note that the brain is not the only region of the body that can be electrically modulated. Direct electrical stimulation can induce sensations in peripheral nerves, and, by the same token, neural impulses can be detected in peripheral nerves located under the skin and within skeletal muscles. Electromyography (EMG) sensors are readily available for noninvasive detection of neuromuscular activity, and they have been used in the muscles of amputees and intact individuals to control external actuators such as prosthetic arms. Microelectrodes implanted in the same area can generate sensations in the phantom limb that has been replaced with a prosthesis [145] Moving closer to the brain, cochlear implants have substantially restored hearing [146], and retinal implants have imperfectly restored vision [147–149]. Restoring vision presents paradigmatic challenges in neuroprosthetic design because it requires biocompatible materials and high-density arrays to replace retinal fields [150,151]. For some applications, interfacing with the peripheral nervous system is safer, more convenient and less expensive than BCI.