DocumentCode :
248354
Title :
Drowsiness Detection Using Photoplethysmography Signal
Author :
Kurian, Deepu ; Johnson Joseph, P.L. ; Radhakrishnan, Krishnaja ; Balakrishnan, Arun A.
Author_Institution :
Dept. of Appl. Electron. & Instrum., Rajagiri Sch. of Eng. & Technol., Ernakulam, India
fYear :
2014
fDate :
27-29 Aug. 2014
Firstpage :
73
Lastpage :
76
Abstract :
This study presents an innovative approach to detect drowsiness by using photoplethysmography signals which is easily acquirable with non-invasive techniques. Drowsiness detection based on biological signals is being employed in precautionary personal safety. Autonomous Nervous System (ANS) activity can be measured non-invasively from the Pulse Rate Variability (PRV) signal obtained from photoplethysmography signal (PPG), that comprises alterations during, relaxation, extreme fatigue and drowsiness episodes. Our hypothesis is that these variations manifest on PRV. In this work we develop an on-line detector of drowsiness based on PRV analysis. The databases have been collected with the aid of an external observer who decides upon each minute of the recordings as drowsy or awake, and constitutes our data base.
Keywords :
medical signal detection; medical signal processing; neurophysiology; photoplethysmography; ANS activity; PPG; PRV analysis; PRV signal; autonomous nervous system; biological signals; drowsiness detection; noninvasive techniques; on-line detector; photoplethysmography signal; precautionary personal safety; pulse rate variability; Blood; Fatigue; Noise; Photoplethysmography; Safety; Support vector machines; Vehicles; Drowsiness detection; PPG signal; peak detection; wavelet denoising;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Computing and Communications (ICACC), 2014 Fourth International Conference on
Conference_Location :
Cochin
Print_ISBN :
978-1-4799-4364-7
Type :
conf
DOI :
10.1109/ICACC.2014.23
Filename :
6905992
Link To Document :
بازگشت