Linked adaptive neuro-fuzzy inference system for biosignal distortion detection system

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초록

This paper proposes a biosignal distortion detection algorithm for a driver healthcare system based on a contact biosensor and a linked adaptive neuro-fuzzy inference system (ANFIS), and demonstrate its superiority using actual vehicle experiments. Contact biosensors are highly sensitive to vehicle vibration and turning. Although vehicle suspension contributes significantly to ride quality, vibration transfers to the driver and contact between the driver and biosensor can become unstable when executing a turn, causing the driver's biosignal to not be measured well. This study estimated the driver's biosignal state using acceleration, angular velocity, and slip ratio measurements obtained from sensor fusion. When the measurement exceeded a defined threshold, the driver healthcare system removed unreliable biosignal data. We adopted ANFIS to improve the proposed sensor fusion algorithm estimate accuracy for the driver's biosignal state and improved the healthcare system robustness to road conditions. The effectiveness of the proposed algorithm was demonstrated experimentally by comparing the system using sensor fusion and linked ANFIS.

키워드

Linked adaptive neuro fuzzy inference systembiosignal distortion detectiondriver healthcare systemsensor fusionIDENTIFICATIONCLASSIFICATION
제목
Linked adaptive neuro-fuzzy inference system for biosignal distortion detection system
저자
Park, Jun YongKim, Dong W.Kang, Tae-KooLim, Myo Taeg
DOI
10.3233/JIFS-182532
발행일
2019
유형
Article
저널명
Journal of Intelligent and Fuzzy Systems
37
6
페이지
7725 ~ 7735