Abstract / truncated to 115 words (read the full abstract)

This thesis focuses on wearables for health status monitoring, covering applications aimed at emergency solutions to the COVID-19 pandemic and aging society. The methods of ambient assisted living (AAL) are presented for the neurodegenerative disease Parkinson’s disease (PD), facilitating ’aging in place’ thanks to machine learning and around wearables - solutions of mHealth. Furthermore, the approaches using machine learning and wearables are discussed for early-stage COVID-19 detection, with encouraging accuracy. Firstly, a publicly available dataset containing COVID-19, influenza, and healthy control data was reused for research purposes. The solution presented in this thesis is considering the classification problem and outperformed the state-of-the-art methods, whereas the original paper introduced just anomaly detection and not shown the ... toggle 7 keywords

aging society artificial intelligence COVID-19 machine learning parkinson’s disease signal processing wearables

Information

Author
Justyna Skibińska
Institution
Brno University of Technology & Tampere University
Supervisors
Publication Year
2023
Upload Date
July 31, 2024

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