Sensors | |
A Low-Rank Matrix Recovery Approach for Energy Efficient EEG Acquisition for a Wireless Body Area Network | |
Angshul Majumdar1  Anupriya Gogna1  | |
[1] Indraprastha Institute of Information Technology, Delhi 110020, India; E-Mail: | |
关键词: EEG; WBAN; compressed sensing; low-rank matrix recovery; | |
DOI : 10.3390/s140915729 | |
来源: mdpi | |
【 摘 要 】
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.
【 授权许可】
CC BY
© 2014 by the authors; licensee MDPI, Basel, Switzerland.
【 预 览 】
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