Slyde Analytics LLC

Frederic Lamon

Patrick Flaction

Christophe Ramstein

Cyrille Gindre

A method and system for optimizing an athlete's performance during a race using a wearable device. The method involves determining the athlete's performance level from past races or trainings, and collecting race data through a wearable sensor. This data helps retrieve a tailored race profile from several options, each a non-linear function of time over distance, optimized for the athlete's level. The selected profile is applied to the sensor data to compute a projected race time, which is then displayed on the device. The system also measures and displays other race parameters such as stride length, cadence, and physiological metrics. It adjusts recommendations for pace in real-time based on these inputs. Advanced features include neural networks for enhancing race profile accuracy using data from multiple athletes. The device's processor and memory manage these functions effectively, providing dynamic feedback and strategic adjustments during the race, aiming to significantly improve athletic performance.

Method and apparatus for predicting a race time

A method for providing at least one of the following information to an athlete during a race such as a running or a cycling race: a race time prediction; a probability to achieve a target time at the end of the race; and/or an indication whether the pace followed by the athlete is too fast, adequate or too slow in order to achieve a target time. The method includes measuring during the race a plurality of intermediate times with an inertial sensor and/or a positional sensor in a wearable device; causing a processing unit in the wearable device to retrieve, based on the intermediate time and on previous races of other athletes, a race profile as non-linear function of time over distance (t=f(d)); and using the retrieved race profile for determining the information.

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Corin-De-La-Crête, Switzerland

Frederic Lamon