Browsing by Author "Kamavuako, Ernest N."

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    Combined surface and intramuscular EMG for improved real-time myoelectric control performance
    (Elsevier, 2014-03) Kamavuako, Ernest N.; Scheme, Erik J.; Englehart, Kevin B.
    The four main functions that are available in current clinical prostheses (e.g. Otto Bock DMC Plus®) are power grasp, hand open, wrist pronation and wrist supination. Improving the control of these two DoFs is therefore of great clinical and commercial interest. This study investigates whether control performance can be improved by targeting wrist rotator muscles by means of intramuscular EMG. Nine able-bodied subjects were evaluated using offline metrics and during a real-time control task. Two intramuscular (targeted) and four surface EMG channels were recorded concurrently from the right forearm. The control was derived either from the four surface sources or by combining two surface channels combined with two intramuscular channels located in the pronator and supinator muscles (combined EMG). Five metrics (Throughput, Path efficiency, Average Speed, Overshoot and Completion Rate) were used to quantify real-time performance. A significant improvement of 20% in Throughput was obtained with combined EMG (0.90 ± 0.12 bit/s) compared to surface EMG alone (0.75 ± 0.10 bit/s). Furthermore, combined EMG performed significantly better than surface EMG in terms of Overshoot, Path Efficiency and offline classification error. No significant difference was found for Completion Rate and Average Speed. The results obtained in this study imply that targeting muscles that are involved in the rotation of the forearm could improve the performance of myoelectric control systems that include both wrist rotation and opening/closing of a terminal device. Keywords: Fitts’ Law test, targeted EMG, pattern recognition, intramuscular EMG, real-time control, wrist rotator
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    On the usability of intramuscular EMG for prosthetic control: A Fitts’ Law approach
    (Elsevier, 2014-10) Kamavuako, Ernest N.; Scheme, Erik J.; Kevin B., Englehart
    Previous studies on intramuscular EMG based control used offline data analysis. The current study investigates the usability of intramuscular EMG in two degree-of-freedom using a Fitts’ Law approach by combining classification and proportional control to perform a task, with real time feedback of user performance. Nine able-bodied subjects participated in the study. Intramuscular and surface EMG signals were recorded concurrently from the right forearm. Five performance metrics (Throughput, Path efficiency, Average Speed, Overshoot and Completion Rate) were used for quantification of usability. Intramuscular EMG based control performed significantly better than surface EMG for Path Efficiency (80.5 ± 2.4% vs. 71.5 ± 3.8%, P = 0.004) and Overshoot (22.0 ± 3.0% vs. 45.1 ± 6.6%, P = 0.01). No difference was found between Throughput and Completion Rate. However the Average Speed was significantly higher for surface (51.8 ± 5.5%) than for intramuscular EMG (35.7 ± 2.7%). The results obtained in this study imply that intramuscular EMG has great potential as control source for advanced myoelectric prosthetic devices.