MyBikeFitting is a free online AI bike fitting analysis tool that evaluates your cycling position using your webcam, video, or a simple photo. Designed for all cyclists—road, MTB, gravel, triathlon, city, or indoor trainer—it delivers data-driven recommendations to enhance comfort and performance without any cost or signup. The core value lies in making professional-grade bike fitting accessible to everyone, eliminating the need for expensive appointments or specialized equipment. By leveraging advanced computer vision and biomechanics research, MyBikeFitting provides a detailed analysis of your riding posture in just five minutes, directly from your browser.
Cycling pain—whether in the knee, back, neck, or hands—is a common issue that often stems from an incorrect bike fit. Studies suggest that 80% of such problems are related to improper saddle height, setback, or handlebar position. MyBikeFitting addresses this pain point by offering a quick, accurate assessment that identifies the root causes. Instead of relying on trial and error or expensive professional consultations, cyclists can now obtain precise, actionable insights to alleviate discomfort and prevent injury. This matters because unresolved pain can ruin the riding experience, limit performance, and even lead to chronic issues.
The first major feature group is the AI analysis of four key angles: knee extension, hip angle, back angle, and arm angle. The system uses computer vision to measure these angles from a side-view image or video, comparing them against scientifically established optimal ranges. For example, knee extension is measured at bottom dead center, with a target range of 140-150 degrees based on the Holmes method. This feature works by automatically detecting joint positions and calculating angles in real time. It is useful because it transforms subjective feelings of discomfort into objective, quantifiable data, allowing cyclists to pinpoint exactly where adjustments are needed.
The second major feature group is local processing and privacy preservation. All video and image analysis runs directly on the user's device, meaning no data is ever uploaded to servers. This zero-infrastructure approach not only protects user privacy but also eliminates hosting costs, which is why the service can be offered entirely for free. Before the analysis, a personalized questionnaire captures the rider's type, pain points, goals, and body dimensions. This ensures that the recommendations are tailored to individual profiles rather than generic values, increasing the relevance and effectiveness of the advice.
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The third feature group encompasses the capture methods and guidelines for accurate results. Users can choose between live webcam, video upload, or a standard photo—all from a side view with the pedal at bottom dead center. MyBikeFitting provides detailed tips: position the camera perpendicular at saddle height, use good lighting without backlight, wear fitted clothing, ensure the full bike and rider are visible with margin, and use a stable support like a turbo trainer. These guidelines are crucial because the precision of the AI analysis depends directly on input quality, enabling reliable angle measurements and recommendations.
The overall workflow is designed for simplicity and speed, consisting of three steps in five minutes. Step one is a brief questionnaire covering riding style, pain areas, and goals. Step two involves capturing the side view of the rider on the bike using the chosen method. Step three presents detailed adjustments with specific numerical values for saddle height, setback, and handlebar position. The AI processes the angles against its scientific database, which includes references from Holmes, Millour, Bini, and Ferrer-Roca. This methodology ensures that the output is grounded in proven sports medicine and biomechanics research.
Concrete use cases include a cyclist suffering from knee pain discovering that their saddle height is too low, leading to excessive knee extension beyond 150 degrees. The tool recommends raising the saddle by a precise amount. Another user with back pain might find that their handlebar position is too low, causing a overly closed hip angle and breathing restriction. Hand numbness from straight arms is corrected by adjusting back angle and stem length. Outcomes are immediate comfort improvements, reduced pain, and increased power efficiency. Riders can apply the changes and feel the difference on their next ride, with the knowledge that their position is now optimized based on data.
MyBikeFitting targets all cyclists—from beginners to experienced athletes—across disciplines like road, MTB, gravel, triathlon, city biking, and indoor training. It works on any device with a browser, including computers and phones, requiring no special software or account creation. The tool is and will remain free, supported by zero hosting costs due to on-device processing. The creator, Elouan, developed it after personally struggling with knee pain and expensive bike fitting appointments. This personal mission underscores the product's value: empowering every cyclist to achieve a comfortable, efficient, and pain-free ride through accessible AI technology.
Cyclists of all levels experiencing pain or seeking performance improvements—including road cyclists, mountain bikers, gravel riders, triathletes, city commuters, and indoor training enthusiasts. Also relevant for bike mechanics, fitters, and coaches who want a quick digital assessment tool. The product is ideal for anyone who wants a professional-grade bike fit without the cost or hassle of an appointment, especially those with limited access to certified fitters.