Integrated Measurements of Stress, Motion Capture and Environmental Parameters for Ambient Assisted Living Scenarios

Zanetti, Matteo (2019) Integrated Measurements of Stress, Motion Capture and Environmental Parameters for Ambient Assisted Living Scenarios. PhD thesis, University of Trento.

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Chronic diseases and their consequent impairment of the cognitive and motor functions are becoming considerable problems for modern societies that are undergoing rapid demographic changes. Advanced technologies are supposed to be determinant to enable new services and provide assistive devices for patient home care. However, the real-life applicability of these technologies needs to be proved in real settings and their efficacy needs to be tested as regards the environment and patient. In this context, accurate measurement of stress and effort (performed at any level, i.e., muscular, cardiovascular, or cerebral) combined with the subject behaviour (motion of the subject while interacting with the assistive device) and the environment status is determinant for assessing the cost/benefit ratio of each specific assistive technology. The final goal of this project was the implementation of a multi-sensorial platform able to collect multivariate biological signals, motion capture, and environment-related interaction parameters and to elaborate them to provide physicians with a measurable indicator of the user point of view and performances achievable. Operating in the context of integrated system physiology, evaluation of effort and adaptation to a task are assessed as whole on the entire body response thus providing a holistic estimation of potential improvement of life condition. Part of the work presented in this thesis was developed inside the AUSILIA project financed by Provincia Autonoma di Trento and partially developed with the support of the IEEE Smart Cities Initiative - Student Grant Program.

Item Type:Doctoral Thesis (PhD)
Doctoral School:Materials, Mechatronics and Systems Engineering
PhD Cycle:31
Subjects:Area 09 - Ingegneria industriale e dell'informazione
Repository Staff approval on:16 Jul 2019 10:33

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