Transfer Learning Framework for Early Detection of Fatigue Using Non-invasive Surface Electromyogram Signals (SEMG)
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چکیده
Amulti source domain adaptation based learning for addressing subject based variability in myoelectric signals (SEMG), enabling generalized framework for detecting
منابع مشابه
A Multi-Source Domain Adaptation and Its Application to Early Detection of Fatigue
We consider the characterization of muscle fatigue through noninvasive sensing mechanism such as surface electromyography (SEMG). While changes in the properties of SEMG signals with respect to muscle fatigue have been reported in the literature, the large variation in these signals across different individuals makes the task of modeling and classification of SEMG signals challenging. Indeed, t...
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تاریخ انتشار 2011