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remote-patient-monitoring

topic1 events
papersTODAY 04:00 UTC

Unsupervised Keypoint Method Detects Falls in Real Time Using Less Video Bandwidth

A new arXiv paper proposes an unsupervised approach to learning body keypoints for real-time fall detection, aimed at monitoring older adults in home and clinical settings. The authors compare their method against alternatives under realistic conditions and add predictive bandwidth reduction so that continuous video monitoring uses less data. The work targets a known gap: sustained in-person supervision is hard to maintain, while video streams must be practical to transmit.

fall-detection/computer-vision/video-monitoring/healthcare