In the intricate world of bike fitting, where every adjustment can make a significant difference in performance and comfort, one technology stands out for its ability to unveil the secrets of muscle activation: Surface Electromyography (sEMG or later in the text just EMG). As cyclists pedal towards peak performance, understanding the role of muscle activity becomes paramount, and EMG emerges as a game-changer in this pursuit.
Bike Italia presenting the use of Mbody in their bike fitting protocol.
Unveiling Muscle Dynamics: The Essence of EMG in Bike Fitting
EMG offers a unique window into the dynamic interplay of muscles during cycling. By capturing electrical signals that initiate muscle contractions, EMG reveals the intricate patterns of muscle activation throughout the pedal stroke. This real-time insight into muscle dynamics provides invaluable feedback for optimizing pedalling efficiency and preventing overuse injuries.
Myontec Mbody could provide comparable muscle excitation information and reproducibility to traditional laboratory systems during dynamic tasks such as cycling and does not require skin preparation.
Identifying Imbalances and Weaknesses
One of the most significant advantages of EMG lies in its ability to uncover imbalances and weaknesses in muscle recruitment patterns. By analyzing muscle activity levels and activation timing, EMG highlights asymmetries and deficiencies that may go unnoticed by other biomechanical analyses. These insights empower bike-fitting professionals to tailor adjustments that address individual cyclists' specific needs, fostering optimal muscle engagement and performance.
EMG sensors can be used to measure the activity of the muscles recruited during pedalling. Above 10 most important muscles to measure when improving pedalling performance. Picture by Millour et al.
From Lab to Track: Wearable Solutions for On-the-Go Monitoring
Traditionally, EMG measurements required complex laboratory setups, limiting their practicality in real-world cycling environments. However, recent advancements have led to the development of wearable EMG systems integrated into cycling apparel, Myontec Mbody. This innovative solutions offer cyclists the ability to monitor muscle activity seamlessly during training and competition, providing immediate feedback for refining technique and maximizing performance. Additionally to Mbody shorts, Myontec has products to cover calf muscles and upper body. Myontec products have IMU sensors embedded in the datalogger. This gives essential information of the pelvis rotation, torso ankle or range of motion in legs.
The use of IMU reducing pelvis rotation in the medio-lateral axis was associated with a decreased rate of perceived exertion during road tests.
Enhancing Efficiency and Comfort
By leveraging EMG data, bike fitters can fine-tune saddle and handlebar positions to optimize muscle engagement and reduce fatigue. Identifying muscles under excessive strain or experiencing asymmetrical activation allows for targeted adjustments that enhance comfort and prevent injuries. Whether it's reducing quadriceps fatigue during climbs or promoting balanced muscle recruitment across the pedal stroke, EMG-guided bike fitting unlocks new possibilities for cyclists striving for peak performance.
Pioneering the Future of Bike Fitting
As technology continues to evolve, the integration of EMG into bike fitting holds immense promise for the future. From personalized training programs to real-time performance monitoring, EMG stands at the forefront of innovation in cycling biomechanics. By harnessing the power of muscle data, cyclists and bike fitters alike can embark on a journey towards optimal performance, powered by the insights revealed through surface electromyography.
Blog article is based on the study:
A literature overview of modern biomechanical-based technologies for bike-fitting professionals and coaches by Geoffrey Millour, Andrés Torres Velásquez, and Frédéric Domingue in Sage Journals, International Journal of Sports Science & Coaching, Volume 18, Issu October, 2022.
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