Stress Detection using Facial Image for Elderly
Anupriya1, Ashika Gupta2, Mayank Singhania3, Sakchi4, Sudha B5
1Anupriya, Department of Electronics and Telecommunication Engineering, Bangalore Institute of Technology, Visvesvaraya Technological University, Belagavi (Karnataka), India.
2Ashika Gupta, Department of Electronics and Telecommunication Engineering, Bangalore Institute of Technology, Visvesvaraya Technological University, Belagavi (Karnataka), India.
3Mayank Singhania, Department of Electronics and Telecommunication Engineering, Bangalore Institute of Technology, Visvesvaraya Technological University, Belagavi (Karnataka), India.
4Sakchi, Department of Electronics and Telecommunication Engineering, Bangalore Institute of Technology, Visvesvaraya Technological University, Belagavi (Karnataka), India.
5Prof. Sudha B, Assistant Professor, Department of Electronics and Telecommunication Engineering, Bangalore Institute of Technology, Visvesvaraya Technological University, Belagavi (Karnataka), India.
Manuscript received on 26 June 2022 | Revised Manuscript received on 03 July 2022 | Manuscript Accepted on 15 July 2022 | Manuscript published on 30 July 2022 | PP: 75-77 | Volume-11 Issue-8, July 2022 | Retrieval Number: 100.1/ijitee.H91650711822 | DOI: 10.35940/ijitee.H9165.0711822
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Abstract: Stress plays an important role in late-life depression. It is a natural reaction to various factors which can lead to physiological and behavioural changes in human behaviour and performance. Dependence, ill health, loss of social role and recognition, and a lack of opportunity for creative use of leisure are some of the most common medical and psychological difficulties among the elderly. Automatic stress monitoring reduces the likelihood of health problems and promotes society’s well-being. Our project’s major goal is to use machine learning and image processing techniques to detect stress in the elderly population. Our system is an improved version of previous stress detection systems that did not include live detection, personal counselling, or stress level notification via a mobile device application. Instead, this system includes live detection and periodic analysis of the person in question, as well as detecting mental stress levels and notifying the person’s emergency contact. Our system is primarily targeted at the elderly, but it may also be used by students and IT professionals to manage stress and create a healthy, spontaneous work environment for employees, allowing them to give their best during working hours.
Keywords: Facial Image, Emotions, Encryption, Stress, Image-Processing.
Scope of the Article: Image Processing and Pattern Recognition