EMG Pattern Recognition in the Era of Big Data and Deep Learning
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 r...
Main Authors: | Angkoon Phinyomark, Erik Scheme |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2018-08-01
|
Series: | Big Data and Cognitive Computing |
Subjects: | |
Online Access: | http://www.mdpi.com/2504-2289/2/3/21 |
Similar Items
-
LibEMG: An Open Source Library to Facilitate the Exploration of Myoelectric Control
by: Ethan Eddy, et al.
Published: (2023-01-01) -
Feature Extraction and Selection for Pain Recognition Using Peripheral Physiological Signals
by: Evan Campbell, et al.
Published: (2019-05-01) -
Day-to-Day Stability of Wrist EMG for Wearable-Based Hand Gesture Recognition
by: Fady S. Botros, et al.
Published: (2022-01-01) -
Regulating Grip Forces through EMG-Controlled Protheses for Transradial Amputees
by: Irati Rasines, et al.
Published: (2021-11-01) -
Handwritten Digits Recognition From sEMG: Electrodes Location and Feature Selection
by: Andrea Tigrini, et al.
Published: (2023-01-01)