Non invasive stress detection method based on discrete wavelet transform and machine learning algorithms

Altaf, Hunain and Ibrahim, Siti Noorjannah and Funke Olanrewaju, Rashidah (2021) Non invasive stress detection method based on discrete wavelet transform and machine learning algorithms. In: 2021 IEEE 11th IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE), 3 - 4 April 2021, Virtual.

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Abstract

Stress can lead to many serious health problems as it can cause long-term chemical changes if our body is exposed to it for a lengthened period. Thus, it is important to develop a stress detection system to provide early warning for individuals. This is a study about the stress detection in students during their real time activities using the more convenient wearable smartwatch (Raqib) with the complete access to the raw ECG data. We have proposed a Discrete Wavelet Transform (DWT) method to preprocess the raw data along with the use of symlet4 filter to generate 4 levels of Daubechies coefficients. This study identifies 9 different time as well frequency-based features that show significant dependence on stress or simply directly related to stress. We have applied 7 different classifiers to our ECG data features obtained from 30 students and Naïve Bayes classifier produces the highest accuracy of 96.67% under 10-fold cross validation procedure.

Item Type:	Conference or Workshop Item (Plenary Papers)
Uncontrolled Keywords:	noninvasive stress detection method machine learning algorithms serious health problems long-term chemical changes lengthened period stress detection system early warning time activities complete access raw ECG data Discrete Wavelet Transform method raw data symlet4 filter 9 different time frequency-based features ECG data features
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101 Telecommunication. Including telegraphy, radio, radar, television T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User:	Siti Noorjannah Ibrahim
Date Deposited:	18 Jul 2022 08:42
Last Modified:	18 Jul 2022 08:55
URI:	http://irep.iium.edu.my/id/eprint/98793

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