According to one example, an exercise system includes a vertical housing, a first weighted touchpoint coupled to the vertical housing and configured to allow a user to exercise one or more muscles on a first side of the user, a first weight system coupled to the first weighted touchpoint, a second weighted touchpoint coupled to the vertical housing and configured to allow the user to exercise one or more muscles on a second side of the user, and a second weight system coupled to the second weighted touchpoint. The exercise system further includes a control system configured to cause the first weight system to automatically provide a first heavier weight to the first weighted touchpoint for a first exercise and further cause the second weight system to automatically provide a second lighter weight to the second weighted touchpoint for the first exercise.

There is provided a limb exercise device comprising: a force sensor configured to determine a weight applied to the device; a sliding component configured to facilitate the sliding movement of the device along a separate surface, wherein the separate surface is a surface that is separate to the device, wherein the sliding component comprises a part of an external housing of the device; a device movement sensor configured to determine a movement of the device on the separate surface; a limb position sensor configured to determine a position, in at least one dimension, of a limb of a user positioned above or adjacent to the device; and an output device configured to output an indication in dependence on a signal from at least one of: the force sensor, the device movement sensor and the limb position sensor.

Provided are a bilateral limb coordination training system and a bilateral limb coordination training control method. The bilateral limb coordination training control method includes: detecting, by a force sensor, force information of a three degree-of-freedom bilateral motion mechanism and sending the force information to a main controller; determining, by the main controller, target motion information of the three degree-of-freedom bilateral motion mechanism of a robot according to the force information; and controlling, by the main controller, the three degree-of-freedom bilateral motion mechanism to perform a corresponding motion based on the target motion information and sending training data and running status information generated during training to an upper computer; where a training instruction includes a bilateral non-association motion training instruction, a bilateral flexible-association motion training instruction or a bilateral rigid-association motion training instruction.

A system and method for targeted neurological treatment using brainwave entrainment therapy with passive treatment that allows for targeted treatment of particular areas of the brain, particular neurological functions, particular neurological states, and combinations of areas, functions, and states. The system and method receive gait parameters for an individual and compare those against a database of historical gait data to determine if an onset neurodegenerative condition is present, and applies a brainwave entrainment therapy responsive to the determination of the condition. The system and method receive a neurological assessment identifying areas of the brain or neurological functions to be treated, select one or more treatment modalities and frequencies, select a treatment regimen, and apply brainwave entrainment using a treatment regimen while the subject engages in dual-task activities selected to stimulate the areas of the brain, neurological functions, or neurological states to be treated, enhanced, or altered.

Systems and methods are disclosed for generating and providing guided practices and coaching feedback (e.g., illustrated in 3D images, video, or audio) that allow golfers to follow along to improve their physical swing in a digital environment. The feedback may be provided with a 3D avatar using a biomechanical analysis of observed actions with a focus on representing actions through computer-generated 3D avatars. Physical quantities of biomechanical actions can be measured from the observations, and the system can analyze these values, compare them to target or optimal values, and use the observations and known biomechanical capabilities to generate the guided practices and coaching feedback.

Proposed is a golf analysis device with a calibration function, which includes a sensor unit configured to generate tracking data for at least one of a golf club moving by a user's swing motion and a golf ball hit by the user's swing motion; an analysis unit configured to generate a swing analysis value of the user by analyzing the tracking data; and a communication unit configured to transmit the swing analysis value to a user terminal, and receive calibration information on the swing analysis value from the user terminal. As a swing analysis value can be generated based on the calibration information received from the user terminal, the golf analysis device allows the user to receive very accurate swing analysis results.

Controlling an exercise machine includes receiving a stream of measurements of extension of a component of an exercise machine. It further includes characterizing the stream of measurements including detecting at least one extremum having at least one extremum parameter. It further includes matching the extremum parameter with a previously determined signature associated with a user. It further includes changing an output of the exercise machine based at least in part on the match.

Controlling an exercise machine includes receiving a stream of measurements of extension of a component of an exercise machine. It further includes detecting a first phase of a repeated motion. It further includes detecting a transition to a second phase of the repeated motion. A time constraint is applied to the detection of the transition to the second phase of the repeated motion. It further includes controlling a resistance associated with the second phase of the repeated motion.

Methods, systems, and computer-readable mediums for generating, by an artificial intelligence engine, an alignment plan capable of enabling, during a treatment session, the aligning of a user's body. The method comprises generating machine learning models trained to identify alignment plans. The method also comprises receiving treatment data that comprises a first position of the user's body, aspects of a treatment plan, and one or more attributes of the user. The method further comprises generating the alignment plan by using the machine learning models. The generating is based on at least the aspects of the treatment plan and at least one of the one or more attributes of the user. The alignment plan may comprise a target position of the user's body and one or more elements for adjusting the user's body from the first position to the target position. The method also comprises transmitting the plan to a computing device.