Cargando…
Classification of Walking Environments Using Deep Learning Approach Based on Surface EMG Sensors Only
Classification of terrain is a vital component in giving suitable control to a walking assistive device for the various walking conditions. Although surface electromyography (sEMG) signals have been combined with inputs from other sensors to detect walking intention, no study has yet classified walk...
Autores principales: | Kim, Pankwon, Lee, Jinkyu, Shin, Choongsoo S. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8233830/ https://www.ncbi.nlm.nih.gov/pubmed/34207448 http://dx.doi.org/10.3390/s21124204 |
Ejemplares similares
-
Design and investigation of the effectiveness of a metatarsophalangeal assistive device on the muscle activities of the lower extremity
por: Kim, Jiyoun, et al.
Publicado: (2022) -
Transition versus Continuous Slope Walking: Adaptation to Change Center of Mass Velocity in Young Men
por: Hong, Yoon No Gregory, et al.
Publicado: (2018) -
Sex difference in effect of ankle landing biomechanics in sagittal plane on knee valgus moment during single-leg landing
por: Lee, Jinkyu, et al.
Publicado: (2022) -
Antenna Impedance Matching Using Deep Learning
por: Kim, Jae Hee, et al.
Publicado: (2021) -
Multiday EMG-Based Classification of Hand Motions with Deep Learning Techniques
por: Zia ur Rehman, Muhammad, et al.
Publicado: (2018)