Framework for Stress Detection Using Thermal Signature

Framework for Stress Detection Using Thermal Signature

S. Vasavi (VR Siddhartha Engineering College, Vijayawada, India), P. Neeharica (VR Siddhartha Engineering College, Vijayawada, India), M. Poojitha (VR Siddhartha Engineering College, Vijayawada, India) and T. Harika (VR Siddhartha Engineering College, Vijayawada, India)
Copyright: © 2018 |Pages: 25
DOI: 10.4018/IJVAR.2018070101


Autonomic nervous system (ANS) activity requires usage of contact sensors with patients' body. Computational psychophysiology based on thermal imaging is suggested as an alternative. It is a non-invasive and non-contact method that can be used for medical applications such as stress detection, human psychology, geriatric medicine, autonomic nervous activity, medical diagnostics and psychophysiology. It is free from pain and radiations. Very few works are reported to identify stress states at individual level. This work presents a framework to detect stress based on heart rate variability (HRV). Methods were proposed for extracting thermal signatures such as cardiac pulse, breath rate, sudomotor response, and stress response from various regions. Psychophysiological disorders are categorized as bradycardia, tachycardia, stress, and no stress. The system enables monitoring of thermal features at four facial areas such as forehead, neck, periorbital, and nose. The proposed system is tested on bench mark datasets and proved with high confidence w.r.t existing works and ground truth values.
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1. Introduction

Stress is a feeling or cognitive process expressed by humans because of tension, mental state, emotions experienced by the external environmental factors (job pressure, insufficient sleep, money, relationships, health). Increase in stress may sometimes results to distress. Stress can be categorized as acute stress, chronic stress, eustress and distress. As per the statistics of Deidre McPhillips (2016), for many years, India suffered life lost because of disability or death caused by depression and anxiety. As per World Health Organization (WHO) statistics in 2016 year, India stands in first position for depression and anxiety disorders. WHO released disease estimates for 2000-2015 in the year 2017. As per that report, Stress incontinence is predicted in humans causing discharge of small amounts of urine without meaning to when coughing, sneezing, laughing or during physical exercise. Human stress detection methods are classified as visual features (such as features extracted from nose, mouth, eyebrows, lips), behavioural, thermal, physiological and multimodal. Thermal infrared imaging provides non-contact and non-invasive method for assessing psycho physiological states and human autonomic nervous activity. Cardiac pulse represents pulsatile propagation of blood in the circulatory system. During Inspiration and Expiration function, air flows in and out of the nostrils and generated signal patterns, from which breathing rate can be computed. Sudomotor response can be estimated by computing Galvanic Skin Response (GSR). Stress response can be estimated by computing Heart Rate (HR) and Heart Rate Variability (HRV). The present study is on extracting vital thermal signatures to classify the Psycho physiological disorders. This paper is organized as follows: Section 2 presents literature survey on existing works for stress detection using thermal imaging. Proposed system methodology is given in section 3 and results are discussed in section 4.

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