Drowsiness control center by photoplythesmogram

Author

Xu, Yichao Joy ; Ding, Fangjie ; Wu, Zhongjie ; Wang, Jun ; Ma, Quanquan ; Chon, Ki ; Clancy, Edward ; Qin, Michael ; Mendelson, Yitzhak ; Fu, Ningxin ; Assad, Sinan ; Jarvis, Susan ; Huang, Xinming

Author_Institution

Worcester Polytech. Inst., Worcester, MA, USA

fYear

2012

fDate

16-18 March 2012

Firstpage

430

Lastpage

431

Abstract

Daytime drowsiness and fatigue lead to decreased driving reliability, lower working efficiency and fatal accidents. According to recent research, heart rate variability (HRV) can be robustly calculated from the photoplethysmogram (PPG) to indicate parasympathetic nervous activity and classify drowsiness level. In this paper, a low power wireless PPG sensor has been designed. N-back M-pitch, a working memory cognitive test has been used to correlate HRV, extracted from the new sensor, with mental fatigue, indicated by lower accuracy in the test. Signal processing algorithms have been designed, which are being implemented into real time software running on Intel Tunnel Creek Atom board, to function as the drowsiness control center.

Keywords

cognition; medical signal processing; neurophysiology; photoplethysmography; HRV; N-back M-pitch; PPG; daytime drowsiness; drowsiness control center; fatigue; heart rate variability; low power wireless PPG sensor; mental fatigue; parasympathetic nervous activity; photoplythesmogram; signal processing; working memory cognitive test; Accuracy; Heart rate variability; Signal processing algorithms; Software; Wireless communication; Wireless sensor networks; Zigbee;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioengineering Conference (NEBEC), 2012 38th Annual Northeast

Conference_Location

Philadelphia, PA

ISSN

2160-7001

Print_ISBN

978-1-4673-1141-0

Type

conf

DOI

10.1109/NEBC.2012.6206925

Filename

6206925