Publication Type : Conference Paper
Publisher : 2013 International Mutli-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s)
Source : 2013 International Mutli-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s) (2013)
Keywords : automobile driver, band-pass filters, breathing rate, correlation coefficient, driver stress, ECG, Electrocardiography, Feature extraction, feature signal extraction, heart rate, heart rate marker signal, medical signal processing, occupational stress, physiological signal, physiology, QRS power, QRS power spectrum, respiratory signal, Road condition, Stress, stress level, stress monitoring, Vehicles
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking
Department : Computer Science, Electronics and Communication
Year : 2013
Abstract : This paper gives an analysis of variation of the physiological signals of a person with respect to the stress developed within him/her. The analysis was done using ECG and respiratory signals acquired from the automobile drivers who were made to drive on different road conditions to get different stress levels. As a part of analysis, we extracted two feature signals from the above said physiological signals. QRS power spectrum and the breathing rate were the two feature signals that were extracted from the mentioned physiological signals. Heart rate was used as the marker signal for analyzing the variations in the extracted physiological feature signals. The variations in the feature signals with respect to the stress were expressed in terms of correlation coefficients and were tabulated. The analysis clearly showed the changes in the feature signals with respect to the stress of the driver. It showed a direct proportionate relation in the QRS power and the breathing rate with respect to the stress of the driver. The analysis also showed that QRS power signal is a better feature signal for analyzing the stress since it showed more correlation with the heart rate marker signal. The analysis points out the fact that the physiological signals can be used as a metric for monitoring the stress of a person.
Cite this Research Publication : Dr. Soman K. P., Alex, V., and Srinivas, C., “Analysis of Physiological Signals in Response to Stress using ECG and Respiratory Signals of Automobile Divers”, in 2013 International Mutli-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s), 2013.