Upper Limb Prosthesis Using EMG Signal: Review

Abstract

frequently been investigated for use in controlling upper-limb prostheses. We propose the use of EMG signal whitening as a pre-processing step in EMG-based motion classification. Whitening decor relates the EMG signal and has been shown to be advantageous in other EMG applications including EMG amplitude estimation and EMG-force processing. Drawbacks of using whitening include its substantial added computation and memory requirements, the need to collect calibration data, and possible robustness issues in the presence of high frequency noise. This draw backs can be overcome by the degrees of freedom (DOFs). DOFs implements pattern recognition algorithms that use surface electromyography (EMG) signals show great promise as multi-DOF controllers. Unfortunately, current pattern recognition systems are limited to activate only one

DOF at a time. This study introduces a novel classifier based on Bayesian theory to provide classification of simultaneous movements. This approach and two other classification strategies for simultaneous movements were evaluated using non amputee and amputee subjects classifying up to three DOFs, where any two DOFs could be classified simultaneously. Similar results were found for non-amputee and amputee subjects. The new approach, based on a set of conditional parallel classifiers was the most promising with errors significantly less than a single linear discriminant analysis (LDA) classifier or a parallel approach. The low error rates demonstrated suggest than pattern recognition techniques on surface EMG can be extended to identify simultaneous movements, which could provide more life-like motions for amputees compared to exclusively classifying sequential movements. The current statistics includes average of 18,496 upper-extremity amputations every year, compared to 113,702 of the lower extremity.  Of those, only 1900 are above the wrist. Among upper-limb amputees, typically fewer than half wear prosthetic arms.  An estimated number of 541,000 Americans were living with some form of upper limb loss in 2005 and this number is projected to more than double with an aging and growing population by 2050.