A low-rank matrix recovery approach for energy efficient EEG acquisition for a wireless body area network.
Sensors (Basel)
; 14(9): 15729-48, 2014 Aug 25.
Article
em En
| MEDLINE
| ID: mdl-25157551
ABSTRACT
We address the problem of acquiring and transmitting EEG signals in Wireless Body Area Networks (WBAN) in an energy efficient fashion. In WBANs, the energy is consumed by three operations sensing (sampling), processing and transmission. Previous studies only addressed the problem of reducing the transmission energy. For the first time, in this work, we propose a technique to reduce sensing and processing energy as well this is achieved by randomly under-sampling the EEG signal. We depart from previous Compressed Sensing based approaches and formulate signal recovery (from under-sampled measurements) as a matrix completion problem. A new algorithm to solve the matrix completion problem is derived here. We test our proposed method and find that the reconstruction accuracy of our method is significantly better than state-of-the-art techniques; and we achieve this while saving sensing, processing and transmission energy. Simple power analysis shows that our proposed methodology consumes considerably less power compared to previous CS based techniques.
Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Fontes de Energia Elétrica
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Algoritmos
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Redes de Comunicação de Computadores
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Monitorização Ambulatorial
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Compressão de Dados
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Eletroencefalografia
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Tecnologia sem Fio
Idioma:
En
Revista:
Sensors (Basel)
Ano de publicação:
2014
Tipo de documento:
Article
País de afiliação:
Índia