Interactive Demonstrations
Experience live AI-powered biomechanics analysis with real research data showcasing constrained gait patterns and multi-sensor fusion capabilities.
Development Preview
Multi-Sensor Fusion: Constrained Gait Analysis
This demonstration uses actual research data from a constrained gait study (left leg locked in extension) to showcase the challenges of traditional detection methods with pathological movement patterns.
Dataset Information
- ▸ Trial: T5 (Subject 1, Session 2)
- ▸ Constraint: Left leg locked in extension
- ▸ Duration: 20-second analysis window
- ▸ Sensors: Force plates (1000Hz), EMG (2000Hz), Kinematics (100Hz)
Clinical Significance
- ▸ Compensation Patterns: Observable adaptations in right leg
- ▸ Force Asymmetry: Significant left-right differences
- ▸ Traditional Challenges: Threshold-based methods struggle
- ▸ AI Advantage: Pattern recognition adapts to constraints
Enhanced Features in Development
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Multi-Algorithm Comparison
Traditional (60%) → Basic Fusion (75%) → AI Fusion (92%)
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Ground Truth Validation
Scientific annotation tool for accuracy measurement
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Performance Metrics
Real-time accuracy comparison and confidence scoring
Technical Implementation
Data Processing Pipeline
- ▸ Multi-rate sensor synchronization (1000Hz master timeline)
- ▸ Real-time Chart.js visualization (60fps optimized)
- ▸ Smart caching system (10-20x development speed boost)
- ▸ Interactive threshold controls with live detection updates
Algorithm Architecture
- ▸ Traditional: Force plate threshold detection (currently active)
- ▸ Basic Fusion: EMG + Force rule-based combination (in development)
- ▸ AI Fusion: Multi-modal pattern recognition (in development)
- ▸ Comprehensive gait analysis with force metrics integration