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ABSTRACT: Background
Advanced prostheses can restore function and improve quality of life for individuals with amputations. Unfortunately, most commercial control strategies do not fully utilize the rich control information from residual nerves and musculature. Continuous decoders can provide more intuitive prosthesis control using multi-channel neural or electromyographic recordings. Three components influence continuous decoder performance: the data used to train the algorithm, the algorithm, and smoothing filters on the algorithm's output. Individual groups often focus on a single decoder, so very few studies compare different decoders using otherwise similar experimental conditions.Methods
We completed a two-phase, head-to-head comparison of 12 continuous decoders using activitie
SUBMITTER: Paskett MD
PROVIDER: S-EPMC7908731 | biostudies-literature | 2021 Feb
REPOSITORIES: biostudies-literature