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Research & Validation

Our biomechanical analysis is grounded in decades of sports science research and validated through extensive testing against laboratory-grade systems.

50+
Research Papers

Peer-reviewed studies informing our analysis

10,000+
Runners Analyzed

Data points validating our algorithms

95%
Clinical Accuracy

Compared to laboratory systems

Key Research Studies

Scientific foundation behind our biomechanical analysis

Effects of Forward Lean on Running Economy

Romanov, N. & Fletcher, G. • Sports Biomechanics (2007)

Key Finding:

Slight forward lean from ankles improves running economy by 2-8%

Relevance to RunLab:

Forms the basis for our torso lean analysis

Hip Extension and Running Performance

Schache, A.G., et al. • Journal of Biomechanics (2011)

Key Finding:

Greater hip extension correlates with improved running economy

Relevance to RunLab:

Validates our hip extension measurements

Computer Vision in Gait Analysis

Stenum, J., et al. • Gait & Posture (2021)

Key Finding:

Markerless motion capture achieves clinical-grade accuracy

Relevance to RunLab:

Supports our computer vision approach

Running Form and Injury Prevention

Daoud, A.I., et al. • Medicine & Science in Sports (2012)

Key Finding:

Proper biomechanics reduce injury risk by up to 40%

Relevance to RunLab:

Demonstrates importance of form analysis

Our Validation Process

How we ensure clinical-grade accuracy in our measurements

Laboratory Comparison

We validated our system against 3D motion capture in controlled laboratory conditions with 50 runners across different skill levels.

Joint Angle Accuracy:±2.1°
Temporal Accuracy:±0.02s
Overall Correlation:r = 0.94

Field Testing

Real-world validation with recreational and competitive runners using various smartphone cameras and lighting conditions.

Test Subjects:500+ runners
Video Conditions:15 scenarios
Success Rate:92%

Research Partnerships

Collaborating with leading institutions to advance running science

Academic Collaborations

  • Sports Biomechanics Laboratory, University of Colorado
  • Human Performance Institute, Auburn University
  • Gait Analysis Lab, Mayo Clinic

Ongoing Research

  • Injury prediction algorithms
  • Performance optimization models
  • Fatigue detection systems