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A Binary Bat Approach for Identification of Fatigue Condition from sEMG Signals.

, and . SEMCCO, volume 8947 of Lecture Notes in Computer Science, page 480-489. Springer, (2014)

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Spatial Intensity Map of HDEMG Based Classification of Muscle Fatigue., , , and . MIE, volume 281 of Studies in Health Technology and Informatics, page 508-509. IOS Press, (2021)Analysis of biceps brachii sEMG signal using Multiscale Fuzzy Approximate Entropy., , and . EMBC, page 7881-7884. IEEE, (2015)Multiscale feature based analysis of surface EMG signals under fatigue and non-fatigue conditions., and . EMBC, page 4627-4630. IEEE, (2014)Analysis of progression of fatigue conditions in biceps brachii muscles using surface electromyography signals and complexity based features., , and . EMBC, page 3276-3279. IEEE, (2014)Analysis of Sequential Visibility Motifs in Isometric Surface Electromyography Signals in Fatiguing Condition., and . EMBC, page 2659-2662. IEEE, (2018)Emotion Recognition Using Spectral Feature from Facial Electromygraphy Signals for Human-Machine Interface., , , and . MIE, volume 281 of Studies in Health Technology and Informatics, page 486-487. IOS Press, (2021)Analysis of Dynamic Contractions from Biceps Brachii Muscle using Surface Electromyography signals and Multiscale Visibility Graph Features., and . EMBC, page 2653-2656. IEEE, (2019)Analysis of Pre- and Post- Fatigue Thermal Profiles of the Dominant Hand Using Infrared Imaging., , , and . ICCBB, page 53-57. ACM, (2017)Classification of Biceps Brachii Muscle Fatigue Condition Using Phase Space Network Features., and . MIE, volume 270 of Studies in Health Technology and Informatics, page 1219-1220. IOS Press, (2020)A Binary Bat Approach for Identification of Fatigue Condition from sEMG Signals., and . SEMCCO, volume 8947 of Lecture Notes in Computer Science, page 480-489. Springer, (2014)