Transform continuous wearable sensor data into interpretable movement events, behavioral evidence, and longitudinal summaries.
✓ Built to support clinical review — never to replace it.
Reduced mobility and several short episodes of repetitive lower-limb movement were observed during stationary periods.
Statistical features are useful, but they still leave a person to work out what happened. SenseMind adds context-aware, common-sense reasoning to produce a fuller account.
?What this meansThe product summarizes the shape of the sensor signal — its average, strongest rhythm, and amount of variation. A specialist must still infer what the person was doing.
“A short period of rhythmic lower-limb movement occurred while the patient was otherwise stationary. The event lasted 6.2 seconds and was followed by normal walking.”
Common sense, made reviewable The system connects signal patterns with body location, activity, timing, and surrounding events — then shows the evidence behind its description.
Surface meaningful events instead of asking specialists to scan hours of raw signals.
Use longitudinal evidence to identify which monitoring periods need closer human review.
Support monitoring, research, and rehabilitation workflows through a shared sensor-intelligence API.
Give care teams evidence from between visits, not just a patient's brief time in clinic.
Support remote review when clinically appropriate, saving time and transport costs.
Spend visit time discussing meaningful changes rather than reconstructing what happened.
Actual savings depend on the care pathway, deployment model, and clinical governance. SenseMind supports—not replaces—professional review and clinician-led decisions.
Motor patterns can fluctuate throughout the day. Wearable sensors capture that missing context; our system makes long periods of IMU data reviewable.
Rhythmic lower-limb movement was detected during a predominantly stationary period.
Walking was characterized by short, repetitive lower-limb movements with reduced movement amplitude.
Several brief movement attempts occurred before sustained walking began.
Thousands of windows become a coherent timeline of movement events, changes, and context.
Most active periods showed stable walking. Reduced mobility appeared in the late morning and afternoon. Three short repetitive lower-limb movement events occurred during stationary periods, alongside two delayed transitions to sustained walking.
Send continuous IMU windows. Receive structured events, human-readable evidence, and longitudinal summaries for clinical review, rehabilitation, or research.
POST /v1/movement/analyze { "sensor": "imu", "device_location": "ankle", "sampling_rate": 100, "data": "..." }
{ "movement_pattern": "rhythmic_lower_limb_motion",
"context": "stationary", "confidence": 0.87 }
Build monitoring and research systems that understand what patients are physically doing between visits.
For research and clinical review support. Not a diagnostic device.