Cargando…
Biometric From Surface Electromyogram (sEMG): Feasibility of User Verification and Identification Based on Gesture Recognition
Electrical biosignals are favored as biometric traits due to their hidden nature and allowing for liveness detection. This study explored the feasibility of surface electromyogram (sEMG), the electrical manifestation of muscle activities, as a biometric trait. The accurate gesture recognition from s...
Autores principales: | He, Jiayuan, Jiang, Ning |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7033497/ https://www.ncbi.nlm.nih.gov/pubmed/32117937 http://dx.doi.org/10.3389/fbioe.2020.00058 |
Ejemplares similares
-
Improved Multi-Stream Convolutional Block Attention Module for sEMG-Based Gesture Recognition
por: Wang, Shudi, et al.
Publicado: (2022) -
Multi-day dataset of forearm and wrist electromyogram for hand gesture recognition and biometrics
por: Pradhan, Ashirbad, et al.
Publicado: (2022) -
Dynamic Gesture Recognition Using Surface EMG Signals Based on Multi-Stream Residual Network
por: Yang, Zhiwen, et al.
Publicado: (2021) -
Deep learning and session-specific rapid recalibration for dynamic hand gesture recognition from EMG
por: Karrenbach, Maxim, et al.
Publicado: (2022) -
Multi-Category Gesture Recognition Modeling Based on sEMG and IMU Signals
por: Jiang, Yujian, et al.
Publicado: (2022)