A method for cognitive brain training, psychological motivation, and recovery to be used in conjunction with physical exercise in order to reduce the effects of mental and physical fatigue and improve athletic performance. A plurality of input devices integrate ergonomically with different sports so as not to limit movement, eye-hand coordination or negatively impact physical training. Software, executable on a portable computing device is configured for a sport, enabling an athlete to perform physical and cognitive tasks at the same time. Metrics, formulas and algorithms combine the athlete's self-rated performance with real-time cognitive and physiological output metrics to provide reports of the athlete's performance for each workout and for all workouts overtime. Mental recovery and motivation protocols used to help athletes stay on task and recover from the physical training. Cognitive fatigue self-assessment tests used to help athletes determine their current level of mental fatigue and readiness to train.

Systems and methods for creating personalized exercise programs are disclosed. An image capture device and a computer device are used to capture images of a user while the user performs athletic movements. The images may then be evaluated to create a human movement screen score. The human movement screen score, goal and time commitment information may then be used to create a personalized exercise program tailored to the specific user.

A golf training device for use in a glove or under the ball of the foot or under the heel, which includes pressure sensors, a visual display which is flexibly connected to the sensors for adjusting the position to suit the wearer, and a controller programmed to provide visual feedback to indicate if the pressure is appropriate or not. For a glove the sensors are located on the palm at the junction with the first three fmgers. There are two or more sensors and for each sensor the controller can display by an appropriately coloured LED that the pressure detected by the sensor is too light, appropriate or too tight. For a shoe the sensors are located under the ball of the foot or the heel and the LEDs indicate whether the weight is appropriately on the ball of the foot or on the heel.

An exercise machine may include a tower enclosing, at least in part, a cable and pulley system, a base supporting the tower on a surface, and a plurality of handles operatively coupled to the cable and pulley system and configured to extend from the tower. The exercise machine may include a resistance motor operatively coupled to the cable and pulley system. The resistance motor may include a fan and a flywheel connected to a common shaft. The exercise machine may be operatively associated with a user interface which includes an exercise display area configured to activate one or more exercise indicators in a predetermined sequence and a control area including at least one mode control operable to change the sequence of activation of the one or more exercise indicators. The user interface may be provided on a console of the exercise machine.

Tracking and monitoring athletic activity offers individuals with additional motivation to continue such behavior. An individual may track his or her athletic activity by completing goals. These goals may be represented by real-world objects such as food items, landmarks, buildings, statues, other physical structures, toys and the like. Each object may correspond to an athletic activity goal and require an amount of athletic activity to complete the goal. For example, a donut goal object may correspond to an athletic activity goal of burning 350 calories. The user may progress from goal object to goal object. Goal objects may increase in difficulty (e.g., amount of athletic activity required) and might only be available for selection upon completing an immediately previous goal object, a number of goal objects, an amount of athletic activity and the like.

A performance monitoring device includes a storage section adapted to store information related to a location of a target on the move, a processing section adapted to update the information stored in the storage section, and a notification section adapted to make a notification of information related to a relative position between a user on the move and the target using the updated information related to the location of the target.

A method and an electronic apparatus is provided. A first UI indicating a start of an activity is displayed when first data indicating that the activity occurs is received from a first sensor. Information is displayed about a preset time or a preset intensity required for the activity to be converted into exercise. The preset time or the preset intensity is set based on user information related to a characteristic of a user. It is detected that the activity is maintained for at least one of the preset time or at the preset intensity. In response to the detecting that the activity is maintained, a second UI is displayed indicating a start of an exercise. A sensor is activated based on the start of the exercise and exercise history of the user. A function is executed for measuring exercise information by using second data received from the activated sensor.

A wrist worn muscle movement monitoring device includes a wrist strap; a sensor that responds to muscle movement at a wrist wearing the wrist strap; and monitoring circuitry connected to the sensor.

A method includes receiving a set of treatment plans. Each treatment plan comprising the set of treatment plans may be associated with a user capable of using a treatment device to perform the associated treatment plan. The method also includes receiving healthcare professional profile information. The method also includes identifying treatment device information for each treatment device capable of being used by a cohort of users associated with respective treatment plans. The method also includes using an artificial intelligence engine, wherein the artificial intelligence engine uses at least one machine learning model configured to generate resource deployment predictions, to generate at least one resource deployment prediction. The at least one machine learning model may generate the at least one resource deployment prediction based on at least some treatment plans comprising the set of treatment plans, at least some of the healthcare professional profile information, and at least some of the treatment device information.

An exercise assistance device includes a data obtainer that obtains motion data on a motion of an arm of a user that is taking exercise while swinging the arm, and at least one processor that obtains a type of arm swing form of the user, based on the motion data obtained by the data obtainer.