Floor-Vibration Fall Detection for Older People Living Alone: A Detection Budget for a System with No Wearables and No Cameras

SIMULATED, NOT MEASURED. A design study computing a detection budget for floor-vibration fall detection for older people living alone, with no wearables and no cameras. From stated physical assumptions, the vibration signature of a hard fall is modelled against footsteps, dropped objects, door slams, chair moves and a cat jumping down, as a function of trigger threshold, sensor count and floor type (joisted timber vs concrete slab). With a classifier rejecting 90% of confusers, no configuration meets both a 0.80 hard-fall detection floor and a 0.01 false-alarms-per-day keep-on ceiling; with 99% rejection exactly one does (timber, four sensors). Soft falls are essentially undetectable at every usable operating point.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-10
DOI
https://doi.org/10.5281/zenodo.24109851
Primary Topic
Context-Aware Activity Recognition Systems
Type
preprint
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preprint

Floor-Vibration Fall Detection for Older People Living Alone: A Detection Budget for a System with No Wearables and No Cameras

William Alexander Aldred
Zenodo (CERN European Organization for Nuclear Research)
Context-Aware Activity Recognition Systems
preprint

Floor-Vibration Fall Detection for Older People Living Alone: A Detection Budget for a System with No Wearables and No Cameras

William Alexander Aldred
preprint en

Abstract

SIMULATED, NOT MEASURED. A design study computing a detection budget for floor-vibration fall detection for older people living alone, with no wearables and no cameras. From stated physical assumptions, the vibration signature of a hard fall is modelled against footsteps, dropped objects, door slams, chair moves and a cat jumping down, as a function of trigger threshold, sensor count and floor type (joisted timber vs concrete slab). With a classifier rejecting 90% of confusers, no configuration meets both a 0.80 hard-fall detection floor and a 0.01 false-alarms-per-day keep-on ceiling; with 99% rejection exactly one does (timber, four sensors). Soft falls are essentially undetectable at every usable operating point.

Zenodo (CERN European Organization for Nuclear Research)
Context-Aware Activity Recognition Systems
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