Abstract: A fitness tracking system includes a shoe, a monitoring device, and a controller. The monitoring device is mounted on the shoe and includes an accelerometer configured to generate acceleration data corresponding to acceleration of a foot received by the shoe. The controller is operably connected to the accelerometer and is configured to collect sampled acceleration data by sampling the generated acceleration data, to identify foot strike data of the sampled acceleration data, to identify a local minimum of the sampled acceleration data collected prior to the foot strike data, and to determine foot strike characteristic data corresponding to the foot strike data based on an acceleration value at the local minimum.

Abstract: A method of operating a fitness tracking system includes generating movement data corresponding to movement of a user, sampling the generated movement data at a first sampling rate as first sampled data when operating the fitness tracking system in an activity detection mode, and sampling the generated movement data at a second sampling rate as second sampled data when operating the fitness tracking system in a workout mode. The second sampling rate is greater than the first sampling rate.

Abstract: A fitness tracking system for generating movement variables corresponding to movement of a user includes a monitoring device, a personal electronic device, and a remote processing server. The monitoring device is configured to be worn or carried by the user and includes a movement sensor configured to collect movement data. The personal electronic device is operably connected to the monitoring device. At least one of the personal electronic device and the monitoring device is configured to calculate feature data by applying a set of rules to the movement data, to calculate raw speed data corresponding to a speed of the user from the subset of the movement data, and to calculate raw distance data corresponding to a distance moved by the user from the subset of the movement data. The remote processing server includes a machine learning model for processing at least the feature data.

Abstract: Systems and methods for improving athletic training, performance and rehabilitation. In one example, the system and method perform or include receiving, with an electronic processor, data associated with the subject; generating, with a parameter estimation algorithm, a parameter value for each of a plurality of parameters associated the subject; determining, with the electronic processor, an effect of training on a performance variable, p, associated with the subject; and determining an exercise routine based on optimizing the performance variable.