Kristof T'Jonck, Chandrakanth R. Kancharla, Jens Vankeirsbilck, Hans Hallez, Jeroen Boydens, Bozheng Pang,
Real-Time Activity Tracking using TinyML to Support Elderly Care,
In: 2021 XXX International Scientific Conference Electronics (ET), pp. 1--6, September 2021.
Abstract: A vast majority of nursing home residents suffer from health issues such as incontinence, night wandering and pressure ulcers. The workload of nurses is noticeably increasing because of these problems. Previous research has shown that many of these complaints can be associated with specific movements in bed. This paper proposes the usage of accelerometer sensors in a non-invasive manner to detect these movements. Using deep learning on the edge, the discussed method provides immediate feedback to nurses to assist them with their care tasks.
Keywords: Accelerometers, Bluetooth Low Energy, Convolutional Neural Network, Data models, Edge Computing, Edge Impulse, Image edge detection, Medical services, Real-time systems, Senior citizens, TinyML, Tracking
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