Drowsiness and fatigue are one of the most important causes of accidents on the road. Several methods have been investigated for early detection of drowsiness and fatigue to trigger the appropriate interaction between the driver and the vehicle. The physiological information, mainly the heart rate variability (HRV) demonstrate to be very effective for predicting the drowsiness and the fatigue that is oncoming to the car driver. A computational model has been developed in MATLAB to process data acquired in a non-invasive mode from the driver and to infer about the onset of the drowsiness and the fatigue. A prototype has been developed to test the model in field using the Texas Instruments highly integrated analog front-end ADS1298 for physiological data acquisition and the DSP TMS320C5515 for real-time execution of the signal processing algorithms and of the inference logic.

ACQUISITION AND PROCESSING OF THE PHYSIOLOGIC SIGNAL TO PREVENT DRIVING ACCIDENTS / M. Malcangi - In: Embedded Design in Education & research Conference (Ederc2014) Proceedings / [a cura di] J. J. Soraghan, G. Di Caterina, D. Marinkovich, N. Llin, D. Wicks. - [s.l] : Texas Instruments, 2014. - ISBN 9781479968411. - pp. 212-215 (( Intervento presentato al 6. convegno Embedded Design in Education & Research Conference EDERC2014 tenutosi a Milano nel 2014 [10.1109/EDERC.2014.6924390].

ACQUISITION AND PROCESSING OF THE PHYSIOLOGIC SIGNAL TO PREVENT DRIVING ACCIDENTS

M. Malcangi
2014

Abstract

Drowsiness and fatigue are one of the most important causes of accidents on the road. Several methods have been investigated for early detection of drowsiness and fatigue to trigger the appropriate interaction between the driver and the vehicle. The physiological information, mainly the heart rate variability (HRV) demonstrate to be very effective for predicting the drowsiness and the fatigue that is oncoming to the car driver. A computational model has been developed in MATLAB to process data acquired in a non-invasive mode from the driver and to infer about the onset of the drowsiness and the fatigue. A prototype has been developed to test the model in field using the Texas Instruments highly integrated analog front-end ADS1298 for physiological data acquisition and the DSP TMS320C5515 for real-time execution of the signal processing algorithms and of the inference logic.
drowsiness at the wheel, ANS, heart rate variability, analog front-end, digital signal processor, fast prototyping
Settore INF/01 - Informatica
IEEE
EURASIP
Book Part (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/240756
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