Cargando…
Towards Integration of Domain Knowledge-Guided Feature Engineering and Deep Feature Learning in Surface Electromyography-Based Hand Movement Recognition
As a machine-learning-driven decision-making problem, the surface electromyography (sEMG)-based hand movement recognition is one of the key issues in robust control of noninvasive neural interfaces such as myoelectric prosthesis and rehabilitation robot. Despite the recent success in sEMG-based hand...
Autores principales: | Wei, Wentao, Hu, Xuhui, Liu, Hua, Zhou, Ming, Song, Yan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8731285/ https://www.ncbi.nlm.nih.gov/pubmed/35003244 http://dx.doi.org/10.1155/2021/4454648 |
Ejemplares similares
-
Finger Movement Recognition via High-Density Electromyography of Intrinsic and Extrinsic Hand Muscles
por: Hu, Xuhui, et al.
Publicado: (2022) -
Feature Extraction of Surface Electromyography Using Wavelet Weighted Permutation Entropy for Hand Movement Recognition
por: Liu, Xiaoyun, et al.
Publicado: (2020) -
Enhanced Recognition of Amputated Wrist and Hand Movements by Deep Learning Method Using Multimodal Fusion of Electromyography and Electroencephalography
por: Kim, Sehyeon, et al.
Publicado: (2022) -
Data Augmentation of Surface Electromyography for Hand Gesture Recognition
por: Tsinganos, Panagiotis, et al.
Publicado: (2020) -
Action Recognition of Lower Limbs Based on Surface Electromyography Weighted Feature Method
por: Wang, Jiashuai, et al.
Publicado: (2021)