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Using the Intact Human Hand to Benchmark Real-Time Myoelectric Control Performance for Robotic Interfaces by Nicole Kowalski; Xiaojuan Zhu; Dustin L. Crouch is a scholarly article available to read on EtoBox.

What is Using the Intact Human Hand to Benchmark Real-Time Myoelectric Control Performance for Robotic Interfaces about?

The objective of our study was to demonstrate how the intact human hand can be used as a benchmark for electromyogram (EMG)-based myoelectric control of robotic interfaces (e.g., myoelectric prostheses). Using the intact human hand as a gold standard for control algorithms is attractive because able-bodied participants are widely available, have stereotypical movements, and possess highly refined motor control. We compared within-subjects performance of a real-time virtual posture-matching task between a musculoskeletal model-based EMG controller (model trials) and the human hand (goniometer trials). Goniometer trials had lower (i.e., better) normalized path length (2.0±1.6) and task duration (3.3±3.4 sec) than model trials (4.1±4.3 and 12.3±10.7 sec, respectively; p<0.0001). Though, qualitatively, actual (measured by goniometers) and virtual joint angles assumed similar relative postures during model trials, there was a constant offset between them. Additionally, joint angles were more variable during model trials than goniometer trials. The results quantified the extent to which task performance and movement characteristics were not as good with the EMG controller (in this case,

Author

Nicole Kowalski; Xiaojuan Zhu; Dustin L. Crouch

Publisher

IEEE

Published

2021

Language

EN