A proposal that uses inverted-pendulum physics to generate synthetic falling data for training a GRU-based fall detection and forecasting network, without quantitative validation on real sensor data or human subjects.
Edge- ai in lora-based health monitoring: Fall detection system w ith fog computing and lstm recurrent neural networks,
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Real-time Fall Prevention system for the Next-generation of Workers
A proposal that uses inverted-pendulum physics to generate synthetic falling data for training a GRU-based fall detection and forecasting network, without quantitative validation on real sensor data or human subjects.