Quantitative and Qualitative Running Gait Analysis through an Innovative Video-Based Approach

Area of Science:

• Biomechanics
• Sports Science
• Motion Analysis

Background:

• Running gait analysis is crucial for identifying and monitoring gait abnormalities linked to running injuries.
• Marker-less video sensor technology offers a potentially time- and cost-efficient alternative to traditional methods.
• The Graal system, previously validated for walking, was optimized for running gait analysis.

Purpose of the Study:

• To validate an improved version of the Graal video analysis software for quantitative and qualitative running gait analysis.
• To compare Graal's measurements against a gold-standard photosensor system (Optogait).

Main Methods:

• 33 healthy recreational runners performed treadmill running at a self-selected speed.
• Simultaneous data collection using the optimized Graal system and the Optogait photosensor system.
• Graal software analyzed pixel brightness variations to determine gait frequencies (F1, F2), step length, harmony, and synchrony.
• Optogait measured step length, cadence, and variability (vCAD).

Main Results:

• Graal's F2 measurement showed high correlation (r² = 0.81) and no significant difference with Optogait's cadence.
• Graal's step length measurement demonstrated a very high correlation (r² = 0.98) and no significant difference with Optogait's step length.
• Bland-Altman analysis confirmed minimal bias and imprecision between Graal and Optogait for quantitative measures.
• No significant correlation was found between Optogait's vCAD and Graal's harmony or synchrony indices.

Conclusions:

• The optimized Graal system is a valid and cost-efficient tool for quantitative running gait analysis.
• Graal accurately measures cadence and step length, comparable to the Optogait system.
• The validity of Graal for qualitative running gait analysis remains inconclusive and needs further investigation across various running intensities.