The Sole-arium platform is a four-layer biomechanical correction system.
This page documents how each layer works and how they connect.
The biomechanical pipeline
A structured system that captures, models, and delivers movement correction.
Capture
What
Video-based gait capture
Signals
- Gait cycle timing
- Load transfer patterns
- Postural deviation
Output
Structured movement signal set
passes to next layer ↓
Model
What
Biomechanical interpretation layer
Signals
- Arch profile inference
- Pressure distribution mapping
- Risk identification
Output
Personal biomechanical model
passes to next layer ↓
Design
What
Prescription generation
Signals
- Correction geometry
- Material mapping
- Pressure redistribution targets
Output
Manufacturing-ready prescription
passes to next layer ↓
Deliver
What
CNC manufacturing + outcome capture
Signals
- Fit accuracy
- Outcome feedback
Output
Real-world correction data
The system learns from every outcome
Outcome data from manufactured corrections flows back into the model layer, refining prediction accuracy and prescription precision with each cycle.
- Output data flows back into model layer
- Improves prediction accuracy
- Improves prescription precision over time
Built on Indian biomechanical data
Indian foot morphology presents distinct characteristics: wider forefoot patterns, different arch geometry, and gait shaped by climate, terrain, and footwear culture.
Western datasets are insufficient for Indian morphology. Most global orthotics training data is built on Western population samples, making it systematically misaligned with the Indian baseline.
The model layer is trained on Indian data. This is a technical requirement for clinical accuracy.
Signal differences
Forefoot width distribution
Wider ratio compared to Western population norms
Arch geometry variation
Different arch profiles by region, climate, and footwear history
Gait patterns by terrain
Floor surface, footwear culture, and activity context shape patterns
Pathology differences
Incidence and expression vary from Western epidemiological data
System design decisions
Vertical integration
Capture → model → design → manufacture in one system. Eliminates dependency gaps between layers.
Data ownership
First-party biomechanical dataset. Improves with every assessment.
Closed-loop feedback
Outcome data feeds model continuously. System improves over time.
Start with a movement assessment.