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Updated: Aug 8, 2025

Movement Retraining using Real-time Feedback of Performance
Published on: January 17, 2013
Continuous estimation of multi-DOF movement from sEMG based on non-negative matrix factorization and L2 regulation
Ming Meng1, Guangqian Zhou2, Yuliang Ma2
1Inst Intelligent Control & Robot, Hangzhou Dianzi Univ, Hangzhou, 310018, Zhejiang, People's Republic of China. mnming@hdu.edu.cn.
Abstract:
Accurate continuous estimation of multi-DOF movement is crucial for simultaneous control of advanced myoelectric prosthetic. The decoupling of multi-DOF is a challenge for continuous estimation. In this paper, we propose a model combined non-negative matrix factorization (NMF) with Hadamard product and L2 regulation to suppress the non-active DOF and achieve the multi-DOF movement continuous estimation. The L2 regulation of non-active DOF activation coefficient was added to the object function of NMF with the benefit of Hadamard product. The angles were estimated by a linear combination of the activation coefficients. We performed a set of continuous estimation experiments for single-DOF and multi-DOF movements of wrist flexion/extend and hand open/close. The results illustrated that the novel model could suppress non-active DOF in single-DOF movement better than other methods based on muscle synergy theory. Moreover, we investigated the robustness of suppression effect and the similarity of synergy matrices at different speeds for NMF-based methods, and the results showed that the proposed method had a superior performance.
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