Novel non-Euclidean adaptive descriptor for limb motion intent decoding in EMG-pattern recognition system

Conference paper

Kulwa, F., Sarwatt, D. S., Pengrui, T., Asogbon, M., Khushaba, R. N., Fang, P., Li, H., Samuel, O., Li, G. and Li, Y. 2025. Novel non-Euclidean adaptive descriptor for limb motion intent decoding in EMG-pattern recognition system. 47th Annual International Conference of the IEEE, Engineering in Medicine and Biology Society. IEEE.
AuthorsKulwa, F., Sarwatt, D. S., Pengrui, T., Asogbon, M., Khushaba, R. N., Fang, P., Li, H., Samuel, O., Li, G. and Li, Y.
TypeConference paper
Abstract

The feature extraction technique is a crucial stage in the electromyogram (EMG) based pattern recognition (PR) motor intent decoding system. Despite numerous proposed techniques for feature extraction, their decoding performances remain relatively low, often tested without considering the drift between the training and test sets, and the influence of inevitable factors such as white Gaussian noise (WGN). In this study, we propose a feature extraction scheme that works in an unsupervised manner between the training and testing phases. This involves reducing the drift between the training and test sets using the feature adaptation approach based on Riemann operations. Further drift minimization is achieved by projecting the test data to align the distribution of the training set. The obtained results show that the proposed feature extraction technique exhibits higher performance in motor intent decoding of 13 hand and finger movements with an average accuracy of 93.17±2.07%. Additional investigation on the feature robustness against WGN indicated that the proposed method had stable and better decoding performance compared to other state-of-the-art techniques. The study findings revealed that the proposed feature scheme could be utilized to improve the overall robustness of myoelectric systems in both commercial and clinical applications.

Year2025
Conference47th Annual International Conference of the IEEE, Engineering in Medicine and Biology Society
PublisherIEEE
Web address (URL)https://embc.embs.org/2025/
Accepted author manuscript
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Publisher's version
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Open
Output statusIn press
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Deposited31 Oct 2025
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