Emg-based system for basic hand movement recognition
This paper presents a system for the automatic identification of six basic hand movements in healthy subjects based on a steady-state of electromyographic signals. The following basic hand motions were detected: opening, closing, flexion, extension, pronation, and supination, as well as the rest con...
- Autores:
-
Camacho Navarro, Jhonatan
León Vargas, Fabian
Barrero Pérez, Jaime
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2012
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/40593
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/40593
http://bdigital.unal.edu.co/30690/
- Palabra clave:
- Electromyography
hand-prosthesis
pattern recognition
principal component analysis
discrete wavelet transform
support vector machines
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
| Summary: | This paper presents a system for the automatic identification of six basic hand movements in healthy subjects based on a steady-state of electromyographic signals. The following basic hand motions were detected: opening, closing, flexion, extension, pronation, and supination, as well as the rest condition. A modular approach of pattern recognition with discrete wavelet transform, principal component analysis, and support vector machines was used to discriminate each movement. Identification was completed off-line every 256 ms with a hardware-software interface composed of a signal acquisition system with two electromyographic differential channels using Matlab® and LabVIEW® software. The system was trained and tested using five subjects of different gender, age, and physical complexion, with identification rates of up to 99.25 %. |
|---|