ArticleScientific reports2024
Tag-free indoor fall detection using transformer network encoder and data fusion.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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7 authors.
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Abstract
This work presents a radio frequency identification (RFID)-based technique to detect falls in the elderly. The proposed RFID-based approach offers a practical and efficient alternative to wearables, which can be uncomfortable to wear and may negatively impact user experience. The system utilises strategically positioned passive ultra-high frequency (UHF) tag array, enabling unobtrusive monitoring of elderly individuals. This contactless solution queries battery-less tag and processes the received signal strength indicator (RSSI) and phase data. Leveraging the powerful data-fitting capabilities of a transformer model to take raw RSSI and phase data as input with minimal preprocessing, combined with data fusion, it significantly improves activity recognition and fall detection accuracy, achieving an average rate exceeding
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Registered trials
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