Physical Activity Classification Meeting Daily Life Conditions for Older Subjects

Physical inactivity can lead to several age-related issues such as falls, movement disorders and loss of independence in older adults. Therefore, promoting physical activity in daily life and tracking daily life activities are essential components for healthy aging and wellbeing. Recent advances in the MEMS devices make it happen to wirelessly integrate miniature motion capturing devices and use them in personal health care and physical activity monitoring systems in daily life conditions. Consequently, various systems have been developed to classify the activities of daily living. However, the scope and implementation of such systems are limited to laboratory-based investigations and they are mainly developed utilizing the sample population of younger adults. Therefore, this dissertation aims to develop innovative solutions for physical activity classification, with a specific focus on the elderly population in free-living conditions.