Affordable Access

Publisher Website

Consistent control information driven musculoskeletal model for multiday myoelectric control

Authors
  • Zhao, Jiamin
  • Yu, Yang
  • Sheng, Xinjun
  • Zhu, Xiangyang
Type
Published Article
Journal
Journal of Neural Engineering
Publisher
IOP Publishing
Publication Date
Sep 15, 2023
Volume
20
Issue
5
Identifiers
DOI: 10.1088/1741-2552/acef93
Source
ioppublishing
Keywords
Disciplines
  • Paper
License
Unknown

Abstract

Objective. Musculoskeletal model (MM)-based myoelectric interface has aroused great interest in human-machine interaction. However, the performance of electromyography (EMG)-driven MM in long-term use would be degraded owing to the inherent non-stationary characteristics of EMG signals. Here, to improve the estimation performance without retraining, we proposed a consistent muscle excitation extraction approach based on an improved non-negative matrix factorization (NMF) algorithm for MM when applied to simultaneous hand and wrist movement prediction. Approach. We added constraints and L 2-norm regularization terms to the objective function of classic NMF regarding muscle weighting matrix and time-varying profiles, through which stable muscle synergies across days were identified. The resultant profiles of these synergies were then used to drive the MM. Both offline and online experiments were conducted to evaluate the performance of the proposed method in inter-day scenarios. Main results. The results demonstrated significantly better and more robust performance over several competitive methods in inter-day experiments, including machine learning methods, EMG envelope-driven MM, and classic NMF-based MM. Furthermore, the analysis of control information on different days revealed the effectiveness of the proposed method in obtaining consistent muscle excitations. Significance. The outcomes potentially provide a novel and promising pathway for the robust and zero-retraining control of myoelectric interfaces.

Report this publication

Statistics

Seen <100 times