[133] Physiological signals monitoring in interaction with machines to address healthy ageing
R Haratian
Bournemouth University, UK
In this paper, the development of age-friendly services and settings in interaction with machines that are among the WHO recommended strategies is addressed. In healthy ageing, mental wellbeing plays an important role, while over 20% of people in the age group of 60 years and above are affected by mental wellbeing issues worldwide. Mental wellbeing problems have an impact on physical health and vice versa and could cause severe illness. Life stressors are among the main contributors for mental wellbeing problems. People in the mentioned age group are more exposed to life stressors, specifically during the pandemic. Early stress detection and mood swings could potentially help better mental wellbeing that is currently relying largely on self-reports, which can be biased and subjective. Also, traditionally the physiological measure of stress quantified by levels of cortisol requires laboratory settings. Therefore, the need for assistive technologies that address early detection and awareness of experienced stress, while providing suitable actions, is addressed in this paper for the purpose of detecting mental wellbeing issues caused by stress in everyday life without dependence on laboratory settings for the purpose of healthy ageing.
