A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Analog versus digital: extrapolating from electronics to neurobiology
Neural Computation
Theoretical and practical limits of dynamic voltage scaling
Proceedings of the 41st annual Design Automation Conference
Computers in Biology and Medicine
Digital Integrated Circuits
| Hi-index | 0.00 |
Remote wireless monitoring of physiological signals has emerged as a key enabler for biotelemetry and can significantly improve the delivery of healthcare. Improving the energy efficiency and battery lifetime of the monitoring units without sacrificing the acquired signal quality is a key challenge in large-scale deployment of bioelectronic systems for remote wireless monitoring. In this article, we present a design methodology for accuracy aware, energy efficient wireless monitoring of electroencephalography (EEG) data. The proposed design performs a real-time accuracy energy trade-off by controlling the volume of transmitted data based on the information content in the EEG signal. We consider the effect of different system parameters in order to design an optimal system. We analyze the impact of noise of the wireless channel. Our analysis shows that the proposed system design approach can provide up to 10X energy savings in a 32 channel wireless EEG system with minimal impact on the monitored EEG signal accuracy.