This research project explores the application of wearable sensor-based data fusion techniques for remote health monitoring of dementia patients. The project aims to address the limitations of current health monitoring systems, which often struggle with accuracy, time-consuming monitoring, and privacy concerns. By leveraging the capabilities of wearable sensors and data fusion algorithms, the project seeks to develop a more efficient and reliable system for monitoring the health of dementia patients. The project will investigate the use of personal sensor networks (PSN), body sensor networks (BSN), and multimedia devices (MD) to collect and analyze data related to patient health, medication adherence, and cognitive function. The research will focus on improving the accuracy and timeliness of data collection, while also addressing privacy concerns and ensuring user-friendliness for dementia patients. The project's findings will contribute to the development of innovative and accessible solutions for remote health monitoring of dementia patients, ultimately improving their quality of life and supporting their caregivers.
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