Real-Time Freezing of Gait (FoG) Detection in Parkinson's Disease via Motion Telemetry

Freezing of Gait (FoG) is one of the most debilitating symptoms of advanced Parkinson's disease, frequently causing falls, injuries, and severe loss of mobility. FoG episodes are episodic and difficult to capture during brief hospital examinations.

Predictive FoG Analytics Pipeline

Petanux develops non-invasive computer vision and wearable sensor fusion algorithms that monitor stride cadence, acceleration decay, and freezing onset in real time.

Key Breakthroughs:

• Real-Time Episode Flagging: Detects gait hesitation and high-frequency leg trembling characteristic of FoG within milliseconds.
• Fall-Risk Telemetry: Generates spatial heatmaps of doorway and turn-induced freezing triggers in patient home environments.
• Cueing Cue Integration: Triggers rhythmic auditory or visual laser cueing to assist patients in overcoming gait freezing instantly.