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Big Data Cogn. Comput. 2018, 2(3), 21; https://doi.org/10.3390/bdcc2030021

EMG Pattern Recognition in the Era of Big Data and Deep Learning

Institute of Biomedical Engineering, University of New Brunswick, Fredericton, NB E3B 5A3, Canada
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Received: 3 July 2018 / Revised: 20 July 2018 / Accepted: 20 July 2018 / Published: 1 August 2018
(This article belongs to the Special Issue Big Data and Cognitive Computing: Feature Papers 2018)
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Abstract

The increasing amount of data in electromyographic (EMG) signal research has greatly increased the importance of developing advanced data analysis and machine learning techniques which are better able to handle “big data”. Consequently, more advanced applications of EMG pattern recognition have been developed. This paper begins with a brief introduction to the main factors that expand EMG data resources into the era of big data, followed by the recent progress of existing shared EMG data sets. Next, we provide a review of recent research and development in EMG pattern recognition methods that can be applied to big data analytics. These modern EMG signal analysis methods can be divided into two main categories: (1) methods based on feature engineering involving a promising big data exploration tool called topological data analysis; and (2) methods based on feature learning with a special emphasis on “deep learning”. Finally, directions for future research in EMG pattern recognition are outlined and discussed. View Full-Text
Keywords: big data; deep learning; electromyogram; EMG; emotion recognition; feature extraction; myoelectric control; pattern recognition; wearable sensor big data; deep learning; electromyogram; EMG; emotion recognition; feature extraction; myoelectric control; pattern recognition; wearable sensor
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Phinyomark, A.; Scheme, E. EMG Pattern Recognition in the Era of Big Data and Deep Learning. Big Data Cogn. Comput. 2018, 2, 21.

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