Systems and methods for electronically creating and modifying a fitness plan are disclosed. The method may include receiving electronic user data, collecting electronic fitness data, and displaying a suggestion for a fitness activity based on the electronic user data and the electronic fitness data.

A walking training system includes a treadmill configured to prompt a trainee to walk, a display device installed such that the trainee views the display device while walking on the treadmill, a camera configured to image the trainee at an angle of view at which a gait of the trainee is recognizable, a calculation unit configured to calculate a tilt of a body core of the walking trainee based on an image captured by the camera, and a display control unit configured to control the display device to display a body core line associated with the tilt, and an index indicating at least an end of a permissible range of a deflection of the body core line.

A portable apparatus includes an exercise-measurement circuitry that measures exercise-related measurement data related to a user carrying out an exercise, a communication circuitry configured to provide the portable apparatus with wireless communication capability, and a processing circuitry configured to a perform operations. The operations include receiving the exercise-related measurement data from the exercise-measurement circuitry, receiving configuration data from an external user interface apparatus over a bidirectional wireless communication connection established through the communication circuitry and capable of transferring payload data to both directions, processing the exercise-related measurement data according to the received exercise-related parameters in order to obtain advanced exercise-related data, and communicating the advanced exercise-related measurement data to the user interface apparatus over the bidirectional wireless communication connection.

A motion device for a virtual reality interaction includes a core, a running belt carried by the core and a frame. The running belt is configured to wrap the core and capable of sliding on the outer surface of the core. The running belt includes a number of running belt units. A surface of each running belt unit facing the core is provided with a number of grooves, and each groove of each running belt unit is connected with a corresponding groove of an adjacent running belt unit through an elastic strap. The frame is located at a periphery of the running belt and is configured to carry the running belt and the core. A number of first balls are arranged between the frame and the running belt.

A treadmill includes a frame. A running belt is coupled to the frame so that the running belt is adapted for rotation relative to the frame. At least one sensor is adapted for collecting parameter information regarding the experience of a user of the treadmill. The parameter information is selected from the group consisting of the user's heart rate, total expended calories, stride length, stride force, cadence, pace, distance, resistance level, incline level, carver count, carver cadence, step count, ground contact time, relative position within a race, and relative position on the treadmill. The treadmill also includes at least one light source that is adapted to selectively communicate information to an instructor relating to the parameter.

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.

An elliptical exercise machine may include a base, one or more upright stanchions coupled to the base and extending upward from the base and supporting first and second cranks. The first crank may support a first crank arm. The first crank arm may support a first pedal leg hanging downward from the first crank arm. The first pedal leg may support a right pedal. The right pedal may be configured to swing forward and rearward and to raise upward and lower downward. The second crank may support a second crank arm. The second crank arm may support a second pedal leg hanging downward from the second crank arm. The second pedal leg may support a left pedal. The left pedal may be configured to swing forward and rearward and to raise upward and lower downward.

A treadmill includes a frame and a running belt coupled to the frame. The running belt is configured to rotate relative to the frame. The treadmill includes at least one sensor configured to collect information regarding a rotation of the running belt and a use of the treadmill by a user of the treadmill. The treadmill also includes a light source coupled to the frame and configured to emit a light at least partly away from a front of the treadmill to at least partly illuminate a rear of the treadmill.

A system, method and computer program product for determining mechanical running power. A plurality of sensor readings is acquired from a plurality of force sensors positioned underfoot. Force values are determined for a plurality of strides using aggregate force data. The slope, a stance time and running speed are determined for each stride. The mechanical running power associated with the plurality of sensor readings is determined by inputting the force values, the slope, the stance time and the running speed to a machine learning model trained to predict the mechanical running power. The mechanical running power can then be provided to the user as feedback or stored for purposes such as later review and analysis. The inputs to the machine learning model can be determined entirely based off of sensor data received from a wearable device worn by the user.

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.