This is BandMyo Dataset for sEMG based gesture recognition.
BandMyo is a sEMG based gesture recognition dataset recorded with one Myo armband worn on the forearm. It consists of 15 static gestures, as shown in Fig gesture_definition.png. Six subjects are recruited to data collection, including four males (age: 21-26) and two females (age: 23-25). During the data collection process, subject performs all 15 gestures following video guidance, and the sEMG signal is recorded at the same time. When all 15 gestures are finished, subject takes off equipment and takes a short rest. Subsequently, he/she takes on the equipment again and repeats the previous procedure. Finally, this procedure repeats 8 times and every repetition is contributed by subject in different scenarios.
To use this dataset, please cite:
@article{zhang2021feature, title={A Feature Adaptive Learning Method for High-Density sEMG-Based Gesture Recognition}, author={Zhang, Yingwei and Chen, Yiqiang and Yu, Hanchao and Yang, Xiaodong and Sun, Ruizhe and Zeng, Bixiao}, journal={Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies}, volume={5}, number={1}, pages={1--26}, year={2021}, publisher={ACM New York, NY, USA} }
@article{zhang2020learning, title={Learning Effective Spatial--Temporal Features for sEMG Armband-Based Gesture Recognition}, author={Zhang, Yingwei and Chen, Yiqiang and Yu, Hanchao and Yang, Xiaodong and Lu, Wang}, journal={IEEE Internet of Things Journal}, volume={7}, number={8}, pages={6979--6992}, year={2020}, publisher={IEEE} }