| Pub. Date | : Oct, 2021 |
|---|---|
| Product Name | : The IUP Journal of Electrical and Electronics Engineering |
| Product Type | : Article |
| Product Code | : IJEEE11021 |
| Author Name | : V Rama Raju, D Anji Reddy, B K Rani, K Srinivas, M Varaprasad Rao, Raj Kumar Patra, G Madhukar and G Devadas |
| Availability | : YES |
| Subject/Domain | : Engineering |
| Download Format | : PDF Format |
| No. of Pages | : 12 |
Electromyography (EMG) is the study of a muscle function through the inquiry of the electrical signal the muscles emanate. Although it was invented by Luigi Galvin way back in 1791, it has come into use only in recent times. EMG was largely used during the Second World War on wounded soldiers, and since then, it has got widespread use in almost all the clinical hospitals, academic medical schools and multinational multispecial superspecialized corporate hospitals. Therefore, in this study, we set up a multi-channel real-time power amplifier set for effective medical diagnostics. The amplifier is designed in such a way that it captures the EMG signals with special reference to the physiology of the upper limb and anatomical structure, and flexor aspect of forearm muscles of the subject having an input impedance more than 300 W (Mega Ohms). The technical specifications and performance of the instrumentation influence the accuracy of measurement so that meaningful recording of electrical activity can be performed with properly designed equipment.
Over the last four decades (1980-2020), and with the convergence of electrical-biomedical engineering and medicine, Newbold Hounsfield, in 1979, became the first engineer to receive the Nobel Prize for Physiology or Medicine for converging electrical engineering and medicine for the invention of CT scan. With the invention of MRI and newer cutting edge technologies like functional MRI, the medical and engineering science (Clinical/Medical, Biomedical, Electrical-Computer, and Mathematical) community has displayed a reawakening of interest in the concept of extracting as many Motor Unit Action Potentials (MUAPs) as possible from an Electromyography (EMG) signal detected with various electrodes,
Electromyography (EMG), Action potentials, Motor unit action potentials, Computed axial tomography, Magnetic resonance imaging, Instrumentation amplifier, Op amp, Differential amplifier