Advanced Myoelectric Control for Improved Prosthetic Function

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Human movement is a complex process and as the number of movements increase, the processes involved become even more complicated. Surface electromyography (sEMG) is one method of monitoring the electrical activity that results from muscle contraction muscle behaviour and gaining further insight into neuromuscular function. The long-term goal of my research program is to use new technologies to better understand neuromuscular function and voluntary movement and to develop more robust dynamic muscle models. The short-term objectives of my research are to examine the variety of factors that affect neuromuscular function using advanced techniques including sEMG and dynamic force measures. One method to observe neuromuscular function is through the use of surface electrodes to record myoelectric signals (MES) from contracting muscles. The MES measures the result of the neural commands sent to the muscle and can provide information regarding the neural mechanisms responsible for deficiencies and function. Traditionally, surface electrodes record activity and the number of available channels on a data acquisition system limits the number of muscles measured. Recently, advances in MES processing have resulted in new techniques, which are more robust. High-density electromyography (HD-EMG) allows the acquisition of significantly greater numbers of signal channels and therefore greater information. These new systems allow for the development of topographical maps, which can then be used to further study muscle activation patterns. The data obtained from HD-EMG systems will allow researchers to better investigate interlimb coordination (i.e. the coordination of more than one limb) and neuromuscular function in movement efficiency and to develop better models of human movement. This has applications in a number of different fields and occupational settings from industrial ergonomics to biomechanics. The advancement of this technology to newer, wireless HD-EMG systems has enabled researchers to investigate function without restriction and in practical settings. This research will also help to develop better prosthesis control systems and advance robotics (e.g. external dermoskeletons). The development of new signal processing techniques, including novel methods of utilizing the data collected from HDEMG will help to advance research.