Electromyographic signals processing for robotic assistance tools in the rural population
This paper presents an algorithm to process the electromyography signal (EMG). It requires low computational power which allows it to be implemented in embedded, low cost platforms. The proposed algorithm uses the Short-Time Fourier Transform (STFT) and the feature extraction methods, namely, modifi...
- Autores:
-
A. Ramirez, D. Andres
Jiménez Hernández, Mario Fernando
Arevalo, Miguel F.
- Tipo de recurso:
- https://purl.org/coar/resource_type/c_6501
- Fecha de publicación:
- 2020
- Institución:
- Universidad El Bosque
- Repositorio:
- Repositorio U. El Bosque
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.unbosque.edu.co:20.500.12495/4614
- Acceso en línea:
- https://hdl.handle.net/20.500.12495/4614
https://doi.org/10.1109/BIOROB.2014.6913869
- Palabra clave:
- Rights
- License
- Acceso abierto
| Summary: | This paper presents an algorithm to process the electromyography signal (EMG). It requires low computational power which allows it to be implemented in embedded, low cost platforms. The proposed algorithm uses the Short-Time Fourier Transform (STFT) and the feature extraction methods, namely, modified mean frequency, and the first spectral moment (SM1). This algorithms is able to identify four different movements of one upper limb, allowing to control a robotic assistance tool with four degrees of freedom. Thanks to the properties of this algorithm, rural populations can have access to this type of technologies. |
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