All capabilities
Healthcare & Hospitals Shared-family mapped

Predictive bed-exit alerting

Bed-exit and unassisted-egress prediction for high fall-risk patients

Pilot target for bed-exit motion; lead time, false alerts, and staff workflow require site validation.

Readiness Shared-family mapped

Mapped to a shared offline runtime family and usable with a recording or compatible ESP32 CSI stream.

Evidence Strong theory Supported hypothesis

Published physics or adjacent results support the hypothesis; capability-specific product and site validation are still required.

Runtime family Fall event

Rapid field-change event followed by low motion, using the shared fall-event state machine.

When no ESP32 is connected

No compatible ESP32 stream is connected. Use the bundled Healthcare recording; it demonstrates the shared Fall event runtime, not independent proof of this capability.

Intended capability

Evaluate the sensing evidence for “Bed-exit and unassisted-egress prediction for high fall-risk patients” in a consented, ground-truthed study. This is not a medical device, clinical monitor, diagnosis, or emergency alert.

This describes the intended outcome. Readiness is shared-family mapped, evidence is class B, and a catalog mapping or recording is not proof of this outcome at a real site.

Solution blueprint

See the environment before installing it.

This exact kit is one of 191 first-class designs. It includes geometry, objects, nodes, wording, scenarios, installation, limitations, and catalog-bound readiness.

Shared-family mapped

No rendered revision is available yet.

Bundled recording

A related Healthcare scene

This is one recorded vertical scenario. It is not separate validation of every capability in the catalog.

01 The physics

The patient's dominant reflection centroid translates from the horizontal bed plane toward a vertical seated/standing posture and the RTI energy migrates from bed cell to floor/edge cells; postural micro-Doppler signature of weight-shift precedes egress.

02 Shared processing path

RTI differential imaging tracks body centroid vs. learned bed footprint -> Doppler posture-transition features -> compartment Kalman dynamics predicts trajectory -> threshold on egress-intent state

This is a capability design path. Components may be shared with other catalog entries; it is not presented as a unique algorithm.

03 Validation plan

Presence/occupancy (r=0.9) and localization proven; validate on WiMANS multi-position activities + own-hardware bed-egress scripted trials against a pressure-sensitive bed mat.

04 Commercial hypothesis

'Predictive bed-exit alerting' — replaces high-false-alarm pressure pads for fall-prevention program managers.