Methods and apparatuses for athletic performance and technique monitoring are disclosed. In one example, a sensor output is received associated with a movement of a user torso during a running motion. The sensor output is analyzed to identify an undesirable torso motion.

A human balance testing and training system may comprise: a mobile communication device comprising: (1) sensors; (2) a display unit; (3) an input unit; (4) an evaluation subsystem for evaluating balance capabilities of a human subject utilizing data collected when the human subject is performing one or more balance evaluation exercises, the data including data received from the sensors; (5) an expert subsystem for prescribing an exercise plan; and (6) a training subsystem for maintaining an exercise plan including one or more balance training exercises for the human subject; wherein the exercise plan is determined by at least one of a balance evaluation by the evaluation subsystem, performance data provided by the training subsystem, and input from a health professional; and wherein the sensors are configured to measure movement of the human subject during performance of one or more of an evaluation exercise and a training exercise.

Disclosed herein are examples of user-paced exercise equipment, as well as related circuitry, methods, and computer-readable media. For example, disclosed herein is a user-paced treadmill, including a belt, a motor coupled to the belt, and control circuitry communicatively coupled to the motor. The control circuitry may be configured to change a velocity of the belt based at least in part on a body velocity and a leg swing velocity of a user of the user-paced treadmill.

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.

A method for resistance training to arm and leg movement can include connecting a horizontally oriented raised weight base secured to a moveable sled in a spaced apart relationship, mounting a agility box, threading a first flexible and extendable one piece stretch cord through a plurality of aligned first upper rollers, securing a static non-extending stretch cord between the moveable sled and a subject, pulling on the first flexible and extendable one piece stretch cord connected to the moveable sled by the subject to receive a first load of resistance causing a physiological change to a targeted part of the subject and simultaneously receiving a second load of resistance to a targeted part of the subject while pulling the moveable sled with the static non-extendable stretch cord.

An exercise treadmill is disclosed. The treadmill can be constructed with no obstructing front rails, with one or more side rails, and/or with a structural flat or ramped surface at the front allowing the user to exercise with unconstrained motion. The treadmill can further include one or more accommodations to help the user stay safe, remain longitudinally centered, and/or adjust speed with controls built into the treadmill, or automatically based on body position relative to sensors built into the side rails. The treadmill belt may be motor driven, or be user driven and dynamically moderated by resistance. The treadmill configuration can be utilized to provide a virtualized exercise experience for the user.

One general aspect of technical solutions described herein includes a biomechanical assistive device that includes one or more sensors, a back-drivable motor system, and a controller. The controller, when the motor system is inactive, records measurements from the one or more sensors for user motion pattern analysis during a user activity being performed by a user. The controller, when the motor system is active, records the measurements from the one or more sensors, and generates an assist torque to assist the user to perform the user activity.

An exercise treadmill is disclosed. The treadmill can include one or more sensors to acquire input data. A computer system can trigger one or more actions based on the input data. The input data can correspond to a lengthwise position of the user along a length of a usable surface of the platform and/or a lateral position of the user on the belt. The action(s) can include providing feedback to the user and/or adjusting rotation of the belt and/or a resistance of rotation of the belt. The adjustment can be performed in response to input from a user control requesting the adjustment.

An electronic device may comprise audio processing circuitry, pace tracking circuitry, and positioning circuitry. The pace tracking circuitry may be operable to selects songs to be processed for playback, and/or control time stretching applied to such songs, by the audio processing circuitry based on position data generated by the positioning circuitry, a desired tempo, and whether the songs are stored locally or network-accessible. The position data may indicate the pace of a runner during a preceding, determined time interval. The pace tracking circuitry may control the song selection and/or time stretching based on a runner profile data stored in memory of the music device. The profile data may include runner's distance-per-stride data. The electronic device may include sensors operable to function as a pedometer. The pace tracking circuitry may update the distance-per-stride data based on the position data and based on data output by the one or more sensors.

A shoe can include a sole with a top surface and a bottom surface opposite the top surface, an upper member coupled to the top surface of the sole, and a sensor coupled to and surrounded by the sole. The sensor can include a processor an antenna in communication with the processor where the antenna is positioned proximate the bottom surface of the sole.