Wearable EEG via lossless compression
- Autor(es):
- Dufort, Guillermo ; Favaro, Federico ; Lecumberry, Federico ; Martín, Álvaro ; Oliver, Juan Pablo ; Oreggioni, Julián ; Ramírez, Ignacio ; Seroussi, Gadiel ; Steinfeld, Leonardo
- Tipo:
- Preprint
- Versión:
- Enviado
- Resumen:
-
This work presents a wearable multi-channel EEG recording system featuring a lossless compression algorithm. The algorithm, based in a previously reported algorithm by the authors, exploits the existing temporal correlation between samples at different sampling times, and the spatial correlation between different electrodes across the scalp. The low-power platform is able to compress, by a factor between 2.3 and 3.6, up to 300sps from 64 channels with a power consumption of 176μW/ch. The performance of the algorithm compares favorably with the best compression rates reported up to date in the literature.
- Año:
- 2016
- Temas:
- Electroencephalography
Random access memory
Compression algorithms
Power demand
Microcontrollers
Prediction algorithms
Correlation
Data compression
Humans
- Institución:
- Universidad de la República
- Repositorio:
- COLIBRI
- Enlace(s):
- https://hdl.handle.net/20.500.12008/23862
- Nivel de acceso:
- Acceso abierto
