ArticleSensors (Basel, Switzerland)2026
Sensor Modality Versus Pretraining for Recognising Bed-Exit-Relevant Postural Transitions: A Gyroscope-Focused Feasibility Study on Public Wearable-IMU Data.
Article in Sensors (Basel, Switzerland), 2026. 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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Abstract
Wearable ward monitoring must eventually detect when a patient leaves the bed, yet the brief postural transitions that begin a bed exit are under-examined relative to dynamic activities. As a feasibility study, we used a public waist-worn six-axis inertial dataset (30 healthy subjects) to ask which sensor axes carry these transitions and whether a pretrained foundation model helps. We defined a ten-class task of four basic activities and six directional transitions, treating the two lie-to-upright transitions as the bed-exit-relevant classes, evaluated with subject-grouped cross-validation. Postural transitions were the weakest classes, and the weakest of these was a bed-exit transition. Removing the gyroscope reduced macro-F1 from 0.822 to 0.647 and bed-exit F1 from 0.657 to 0.351 (
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