Elderly · Frontier
Walker & Cane Compliance Tracking (the 'Left It Behind' Alert)
Knows whether the walker is actually being used — or left behind in the corner.
Plausible physics, early work — shown honestly as an experiment.
How it works
A metal walker reflects WiFi waves strongly, like a small mirror. When it is in use, its reflection moves together with the person, in step with their walking rhythm. When it is abandoned, the reflection sits alone in one spot while the person walks elsewhere.
In the physics: An aluminum walker is an electrically large metallic scatterer at 2.4/5GHz: it produces strong, geometrically rigid specular returns. When used, its reflection track is spatially locked to the person's RTI track and its micro-Doppler shows the characteristic lift-place or rolling cadence phase-locked to gait; when abandoned, a strong static scatterer persists in the NeRF map at one location while an un-augmented (faster micro-Doppler limb signature, no rigid co-moving return) walking track appears elsewhere.
See it work
This is real pipeline output for Elderly, replayed. The exact reading depends on your room.
Go deeper
How the field becomes an answer
How we prove it
Machine-vs-human discrimination already proven (class A) shows rigid-body vs. biological Doppler separation works; own-hardware experiment: scripted walks with/without walker in a furnished room, target >90% bout-level accuracy; cross-check activity segments in OPERAnet.
Who it is for
For rehab/PT directors and fall-committee chairs: 'Your fall-prevention plan says walker, always — we tell you every time they leave it by the bed.'
runtime Runs today in LatentField 2.0 as fall_detect
The matching solution
Complete first-room estimateAging-in-Place Guardian3 nodes · ~$130 parts · 60 min Request kit, subscribe, or set up →Compatible DIY hardware options
15 min · beginner
60 min · intermediate