Continuous estimation of joint angle from electromyography using multiple time-delayed features and random forests

Research article (Biomedical Signal Processing and Control, 2017) · cited 55× · AI/ML
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Continuous estimation of joint angle from electromyography using multiple time-delayed features and random forests

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Continuous estimation of joint angle from electromyography using multiple time-delayed features and random forests is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Continuous estimation of joint angle from electromyography using multiple time-delayed features and random forests. Retrieved May 24, 2026, from https://4ort.xyz/entity/continuous-estimation-of-joint-angle-from-electromyography-using-multiple-time-delayed-features-and-random-forests
MLA “Continuous estimation of joint angle from electromyography using multiple time-delayed features and random forests.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/continuous-estimation-of-joint-angle-from-electromyography-using-multiple-time-delayed-features-and-random-forests.
BibTeX @misc{4ortxyz_continuous-estimation-of-joint-angle-from-electromyography-using-multiple-time-delayed-features-and-random-forests_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Continuous estimation of joint angle from electromyography using multiple time-delayed features and random forests}}, year = {2026}, url = {https://4ort.xyz/entity/continuous-estimation-of-joint-angle-from-electromyography-using-multiple-time-delayed-features-and-random-forests}, note = {Accessed: 2026-05-24}}
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