MyBikeFitting

The second major feature group is the detailed, personalized recommendation engine that translates angle measurements into specific, actionable bike adjustments. Based on the analysis, users receive precise numerical recommendations for saddle height changes (e.g., "Saddle +2cm"), saddle setback adjustments, and handlebar positioning tailored to their individual body geometry and riding style. These recommendations are not generic; they are refined by a preliminary questionnaire that captures the user's practice type (road, MTB, gravel, etc.), pain points, cycling goals, and body type. This contextual information ensures that the suggested adjustments align with whether the rider prioritizes endurance comfort, aerodynamic performance, or off-road stability, making the advice relevant and practical for immediate implementation.

Additional capabilities include a comprehensive educational framework that explains the biomechanical principles behind each recommendation, fostering a deeper understanding of bike fit. The platform details the optimal ranges for each measured angle—knee extension at 140-150°, hip angle at 55-70°, back angle at 35-50°, and arm angle at 150-165°—and explains the consequences of deviations, such as how too low a saddle can cause knee pain while too high a saddle leads to pelvis rocking. It also provides meticulous capture guidelines to ensure analysis accuracy, instructing users on proper camera positioning (side view, perpendicular to the bike at saddle height), lighting conditions (natural or uniform, avoiding backlighting), and pedal placement (bottom dead center for knee extension measurement). Furthermore, the service maintains transparency by citing scientific references like the Holmes method and studies by Bini RR et al., grounding its methodology in established research.

The product works overall by combining a user-friendly interface with sophisticated backend AI that performs all processing locally on the user's device. The technical approach begins with a detailed questionnaire to profile the cyclist, followed by media capture where the AI detects key body joints from the provided image or video. Using computer vision algorithms, it calculates the four critical angles in real-time, compares them against a database of optimal ranges derived from sports medicine literature, and generates adjustment recommendations. This entire workflow is completed within approximately five minutes, with no data ever leaving the user's browser, ensuring both speed and privacy. The system is designed to be accessible without requiring sign-ups, accounts, or payments, leveraging modern web technologies to deliver a professional-grade analysis tool directly through a web browser.

Benefits and measurable outcomes for users include the elimination of cycling pain through targeted adjustments, leading to increased comfort and longer, more enjoyable rides. Cyclists can achieve a more efficient power transfer by optimizing their hip and knee angles, potentially improving performance and endurance. The service provides immediate, data-driven insights that replace weeks of trial-and-error adjustments, saving significant time and frustration. Users gain a foundational understanding of their bike fit, empowering them to make informed future adjustments as their fitness or goals evolve. The local processing ensures complete privacy, as personal images and videos are never uploaded to external servers, addressing common data security concerns. Ultimately, the platform offers a professional-level analysis at zero cost, removing financial barriers to proper bike fitting.

Concrete use cases include a road cyclist experiencing knee pain who uses the webcam analysis to discover their saddle is 3cm too low, follows the recommendation to raise it, and eliminates pain within a single ride. A gravel rider with back discomfort uploads a video, receives advice to increase saddle setback and adjust handlebar height, and achieves a more relaxed riding position suitable for long-distance adventures. A commuter using a city bike captures a photo, learns their arm angle is too straight causing hand numbness, and shortens their stem to absorb vibrations better. An indoor trainer athlete performs a live analysis during a session, fine-tunes their saddle height dynamically, and improves pedal stroke efficiency for virtual races. A triathlete optimizes their aggressive aerodynamic position by adjusting their back angle within the recommended range, balancing speed and sustainability. A mountain biker checks their hip angle to prevent iliac artery compression, ensuring comfort during technical descents and climbs.

Target users encompass all cyclists, from beginners to experienced enthusiasts, across disciplines like road, MTB, gravel, triathlon, city, and indoor training. The platform is particularly valuable for individuals experiencing pain, those new to cycling seeking a proper initial setup, and riders who have changed bikes or components and need re-fitting. It integrates seamlessly with any standard web browser on computers or mobile devices, requiring no special software installations. The tech stack leverages modern web technologies for computer vision and local data processing. Pricing plans are singularly free, with no tiers, subscriptions, or hidden costs, supported by the zero-infrastructure model where analysis runs entirely on the user's device. The service is available globally without geographical restrictions, requiring only internet access for the initial page load.

In summary, MyBikeFitting delivers a revolutionary, accessible solution to a pervasive problem in the cycling community by harnessing AI and biomechanical science. It provides cyclists with immediate, precise, and personalized bike fitting recommendations that address common pain points and optimize riding position, all within five minutes and at no cost. By processing data locally, it ensures user privacy and eliminates traditional barriers of expense and availability associated with professional fittings. This tool empowers every cyclist to achieve greater comfort, efficiency, and enjoyment on the bike, transforming complex fitting principles into an easy, automated process that democratizes expertise and enhances the overall cycling experience for riders worldwide.

Updated 2026-02-28