Compressed Sensing of EEG for Wireless Telemonitoring With Low Energy Consumption and Inexpensive Hardware

• Published in: IEEE transactions on biomedical engineering Vol. 60; no. 1; pp. 221 - 224
• Main Authors: Zhang, Zhilin, Jung, Tzyy-Ping, Makeig, Scott, Rao, Bhaskar D.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.01.2013
• Subjects: Algorithms; Bayes Theorem; Block sparse Bayesian learning (BSBL); Compressed sensing; compressed sensing (CS); Databases, Factual; Dictionaries; electroencephalogram (EEG); Electroencephalography; Electroencephalography - methods; Energy consumption; healthcare; Humans; Remote Sensing Technology - methods; Sensors; Signal Processing, Computer-Assisted; Sparse matrices; Telemedicine - methods; telemonitoring; Wavelet transforms; wireless body-area network (WBAN); Wireless Technology

Telemonitoring of electroencephalogram (EEG) through wireless body-area networks is an evolving direction in personalized medicine. Among various constraints in designing such a system, three important constraints are energy consumption, data compression, and device cost. Conventional data compressi...