Inexpensive and Portable System for Dexterous High-Density Myoelectric Control of Multiarticulate Prostheses

Jacob A. George, The University of Utah
Sridharan Radhakrishnan, The University of Utah
Mark Brinton, Elizabethtown College
Gregory A. Clark, The University of Utah

Abstract

Multiarticulate bionic arms are now capable of mimicking the endogenous movements of the human hand. 3D-printing has reduced the cost of prosthetic hands themselves, but there is currently no low-cost alternative to dexterous electromyographic (EMG) control systems. To address this need, we developed an inexpensive (~675) and portable EMG control system by integrating low-cost microcontrollers with a six-channel surface EMG (sEMG) acquisition device. Using this low-cost control system, we quantify, in a pilot study, the performance of a common EMG-based control algorithm-the modified Kalman filter (MKF)-when computational resources and electrode count are limited. We also demonstrate the ability to provide proportional and independent control of various six-degree-of-freedom prosthetic hands in real-time using the MKF. We found no significant differences in the signal-to-noise ratio (SNR) of the low-cost control system and that of a high-end research-grade system (paired t-tests). We also found no significant difference in the Root Mean Squared Errors (RMSEs) of predicted hand movements for the low-cost control system and that of the research-grade system when using only six sEMG electrodes. We then demonstrate that the SNR of the low-cost control system is statistically no worse than 44% of the SNR of the research-grade system (equivalence tests). Likewise, we demonstrate that RMSEs were typically a few percent better than, and statistically not more than 6% worse than, RMSEs of a research-grade system. This held true even when controlling up to six degrees of freedom on a prosthetic hand. Despite minimal computational resources and only six sEMG electrodes, the system performs satisfactorily and highlights the practicality and efficiency of the modified Kalman filter for dexterous EMG-based control. Successful deployment of this low-cost control system constitutes an important step towards the commercialization and wide-spread availability of dexterous bionic hands.