Training device for determining timing of next training session

Abstract

A device helps a user to plan the proper timing for setting a next training session based on the intensity of a training stimulus of a previous session. The user is shown when there will have been enough recovery time since the last training session to suggest the best time for starting the next training session. The timing recommendations are based on a supercompensation time curve that depends on a user dependent factor that includes at least the training load of the last training session and preferably also depends on the training status of the user. Further parameters like age and gender and variables like behavior affecting recovery, as there are for example tiredness from lack of sleep, dehydration from insufficient drinking, insufficient calories, protein, mineral or vitamin intake, consumption of alcohol and other drugs, can additionally be used to influence the recovery timing calculations.

Description

BACKGROUND OF THE INVENTION[0001]The present invention relates to a device and a method providing a technical aid for physical exercise which instructs the user on proper timing for setting the next training session on account of the intensity of the training stimulus of the previous training session. The best time for performing the next training session is a time window, which only starts after a proper recovery time after the previous training session and is based on the training principle of recovery and supercompensation.[0002]Training is effective because the body is seeking to adapt to the stress from its environment. A training stimulus is the application of stress (the training load) and a training effect is the body's subsequent adaptation to that stress. In training, the desired adaptive response, i.e., the ability of the body to better cope with similar stress situations in future, is described by a process called supercompensation.[0003]The supercompensation model illus...

AI Technical Summary

Benefits of technology

[0027]Characteristics influencing the joint load, such as the suitability of a user's shoes for the individual running style of the user, the amount of wear of the shoes, the underground structure, and running speed are thereby monitored. The accumulated joint load during a training session or for several training sessions can be used to give a warning feedback (alert) to avoid overload, for example by suggesting to reduce the load. These suggestions could be, for example, to return home when 50% of the individually set load maximum is reached, to reduce speed, or to discontinue high training load. In a preferred embodiment, the individually set load maximum is derived by a standardized training status protocol, as known to persons skilled in the art and which can be facilitated by evaluating the measurements. In a more preferred embodiment, said load maximum is automatically derived and / or adjusted during the training session, e.g., by evaluating measurements for signs of fatigue, like reduced step length or step height, or increased stance time (as fraction of total step time) or decreased impacts or increased pronation velocities or similar evaluations of the measurements.

Problems solved by technology

The latter systems can detect changes in height above sea level on a limited accuracy, therefore often air pressure sensors are used to give more accurate information on height changes.

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