Low-power electroencephalography sensing data RF transmission: hardware architecture and test

Authors:
Fei Hu;Qi Hao;Meikang Qiu;Yao Wu;John Frye;Daniel F. Pontillo;Jonathan Finamore;Ankit Bhutani;Zachary McGarvey;Daniel Phillips
Affiliations:
University of Alabama (main campus), Tuscaloosa, AL, USA;University of Alabama (main campus), Tuscaloosa, AL, USA;University of New Orleans, New Orleans, LA, USA;University of Alabama, Tuscaloosa, AL, USA;RIT, Rochester, NY, USA;RIT, Rochester, NY, USA;RIT, Rochester, NY, USA;RIT, Rochester, NY, USA;RIT, Rochester, NY, USA;RIT, Rochester, NY, USA
Venue:
Proceedings of the 1st ACM international workshop on Medical-grade wireless networks
Year:
2009

Citing 3
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Abstract

Electroencephalography (EEG) has been used as a method of diagnosis and observation for patients with seizure disorders. However, it is often difficult to collect reliable and accurate data due to the relatively sensitive nature of most EEG hardware. This research is to construct an EEG acquisition system and interface it with a Wireless Sensor Network. The analog EEG portion was designed, built and found to pass all of the required tests. The signal processing digital board and wireless EEG transmission software were verified as functionally sufficient. On the other hand, the patients' privacy needs to be protected. It is very challenging to develop an EEG transmission security mechanism in a battery-driven, tiny EEG sensor with very limited memory. We have built an extremely low-overhead EEG signal encryption/decryption protocol based on low-complex NTRU cryptography.