| dc.description.abstract | With the rapid advancement of technology, an increasing number of healthcare systems are adopting digital healthcare and various sensing devices to assist patients in their treatment and rehabilitation. These sensing devices collect data, providing data analysis, health monitoring, and feedback. Simultaneously, the issues of declining birthrates and an aging population are exacerbating, leading to a substantial increase in healthcare demand, thereby putting immense pressure on existing healthcare systems. Traditional healthcare systems are struggling to cope with challenges such as uneven distribution of medical resources, workforce shortages, and rising medical costs. The diverse requirements of different medical conditions for specific sensing devices further complicate device management and data integration.
This thesis develops an intelligent healthcare IoT platform that integrates IoT technology to achieve efficient management and application of medical devices. The platform can monitor and manage various medical devices in real-time, collecting and analyzing data from multiple sensing devices (such as VR headsets and EEG sensors) to provide accurate patient physiological information. Utilizing IoT technology, the platform enables instant data transmission and processing, and through AI analysis modules, it performs deep learning and predictive analysis, generating visual reports for medical personnel reference and diagnosis. This enhances healthcare service efficiency and optimizes the allocation of medical resources. | en_US |