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Drowsiness Control Center by Photoplythesmogram

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.

Published onSep 10, 2020
Drowsiness Control Center by Photoplythesmogram
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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.

Read the full article.

Y. J. Xu et al., "Drowsiness control center by photoplythesmogram," 2012 38th Annual Northeast Bioengineering Conference (NEBEC), Philadelphia, PA, 2012, pp. 430-431, doi: 10.1109/NEBC.2012.6206925.

*denotes a WPI undergraduate student author

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