A dual-task approach to the evaluation of the myokinemetric signal as an alternative to EMG

A multi-modal approach for hand motion classification using surface EMG and accelerometers

For decades, electromyography (EMG) has been used for diagnostics, upper-limb prosthesis control, and recently even for more general human-machine interfaces. Current commercial upper limb prostheses usually have only two electrode sites due to cost and space limitations, while researchers often experiment with multiple sites. Micro-machined inertial sensors are gaining popularity in many commercial and research applications where knowledge of the postures and movements of the body is desired. In the present study, we have investigated whether accelerometers, which are relatively cheap, small, robust to noise, and easily integrated in a prosthetic socket; can reduce the need for adding more electrode sites to the prosthesis control system. This was done by adding accelerometers to a multifunction system and also to a simplified system more similar to current commercially available prosthesis controllers, and assessing the resulting changes in classification accuracy. The accelerometer does not provide information on muscle force like EMG electrodes, but the results show that it provides useful supplementary information. Specifically, if one wants to improve a two-site EMG system, one should add an accelerometer affixed to the forearm rather than a third electrode.

Evaluation of sonomyography (SMG) for control compared with electromyography (EMG) in a discrete target tracking task

Most of the commercial upper-limb externally powered prosthetic devices are controlled by electromyography (EMG) signals. We previously proposed using the real-time change of muscle thickness detected using ultrasound, namely sonomyography (SMG), for the control of prostheses. In this study, we compared the performance of subjects using 1-D SMG signal and surface EMG signal, using a discrete target tracking protocol involving a series of letter cancellation tasks. Each task involved using grip force, EMG or SMG from a wrist extensor muscle to move a cursor to one of 5 locations on a computer screen, at the first four of which were located a letter and last of which was a word of "NEXT". The target was defined by the location showing the letter "E" and, once the subject reached this target, they were instructed to "cancel" the E from the screen, using a button operated by the contralateral hand. A paired t-test revealed that the percentage of letters correctly cancelled with force/angle and SMG signal in isometric force control, and with SMG in wrist extension were significantly higher than with EMG (P<0.05) for both isometric control and wrist extension. The results suggest that SMG signal has great potential as an alternative to EMG for prosthetic control.