SeNic: An Open Source Dataset for sEMG-Based Gesture Recognition in Non-Ideal Conditions

In order to reduce the gap between the laboratory environment and actual use in daily life of human-machine interaction based on surface electromyogram (sEMG) intent recognition, this paper presents a benchmark dataset of sEMG in non-ideal conditions (<italic>SeNic</italic>). The dataset...

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Bibliographic Details

Published in:	IEEE Transactions on Neural Systems and Rehabilitation Engineering
Main Authors:	Bo Zhu, Daohui Zhang, Yaqi Chu, Yalun Gu, Xingang Zhao
Format:	Article
Language:	English
Published:	IEEE 2022-01-01
Subjects:	Surface electromyogram (sEMG) benchmark dataset gesture recognition non-ideal conditions
Online Access:	https://ieeexplore.ieee.org/document/9771219/