An efficient health monitoring system based on Sigfox IoT service and a watch-type wearable device for sensing elderly motion, location, and vital signs to predict risk situations designed to achieve at least 30-days of battery life is proposed.
The results demonstrate the feasibility of a stateful contactless sensing-to-action architecture for long-term home health monitoring and integrates sensing, temporal state, reasoning, and action into a unified and auditable loop.
Although further refinement is required to improve fall detection, the proposed approach provides a practical foundation for accessible elderly monitoring and has the potential to support caregivers, independent ageing, and community-oriented healthcare.
An edge-based wearable IoT framework for real-time fall detection based on the accelerometer and gyroscope signals provides a good base for the private, rapid fall detection but still needs to be validated in the real world, tested with hardware, put through with a variety of elderly participants and evaluated for usab...
A machine learning-based frailty detection system that enables continuous and remote monitoring of gait characteristics in indoor environments and is integrated with an Ultra-Wideband (UWB) indoor positioning system to provide precise localization.
Intensified population aging has continuously increased the pressure on community-based chronic disease management, home safety monitoring and mental health services for the elderly. Conventional public health services mainly rely on regular physical examinations and passive follow-up visits, which are plagued by delay...
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