A ground-effect footplate against which a user applies plantar force and moves their foot in 3D across all seven lower-extremity biomechanical axes to accomplish specific as well as global ambulatory objectives related to lower extremity performance improvement, injury prevention and rehabilitation. A device comprising at least one articulating leg connected to a ground-effect footplate and a surface for a user to position against. The device can be used in conjunction with software to create virtual ambulatory environments that mimic GRFVs and cause moments of force that initiate muscular activations that substantially mimic human ambulation, and can couple those movements with non-functional movements in order to improve ROM, speed, strength, and proprioception.

An Internet of Thing (IoT) device includes a camera coupled to a processor; and a wireless transceiver coupled to the processor. Blockchain smart contracts can be used with the device to facilitate secure operation.

A method of selecting a golf club head for a specific user, includes: (a) receiving first data comprising impact location of each of a plurality of golf swings taken by the user using a test golf club; (b) generating an impact probability map specific to the user; (c) providing second data comprising correlations between striking face location and coefficient of restitution (COR) for each of a plurality of golf clubs; (d) calculating a user-specific expected COR value for each of the plurality of golf clubs based on the first data, the impact probability map, and the second data for each of the plurality of golf clubs; and (e) outputting and displaying golf club preference information based on the calculated user-specific expected COR.

A computer-implemented method for recommending an item of equipment, which comprises: gathering sensed data from a sensor; processing the sensed data in accordance with a biomechanical protocol to determine at least one performance indicator associated with a subject's execution of the biomechanical protocol; and determining at least one recommended feature of an item of equipment based at least in part on the at least one performance indicator. Also, an equipment recommendation system with specific application to hockey, which comprises: a camera configured to produce images representative of execution of a hockey shot of a given type by a subject; an I/O interface; and a processor connected to the camera via the I/O interface and configured to extract parameters from the images and to output, via the I/O interface, a hockey stick recommendation for the subject that is based on the parameters and on the given type of hockey shot.

An exercise machine may include a frame, a resistance mechanism supported by the frame, first and second pull cables supported by the frame and linked to the resistance mechanism, a power rack attached to the frame, first and second handles selectively attachable to the first and second pull cable, and first and second pulleys. The power rack includes upright posts configured to have barbell holders adjustably attached thereto such that the barbell holders are configured to be adjusted in various positions between highest positions and lowest positions on the upright posts. The pulleys are configured to selectively receive the pull cables to enable the pull cables to be selectively attached to a barbell to assist or hinder a user in lifting the barbell in a combined cable and free weight workout, the pull cables decoupled from the pulleys for cable workouts.

Mouth guard that includes a flexible printed circuit board encapsulated within a base member is provided. The flexible printed circuit board includes multiple separate stiff sections spaced apart from each other within the base member. One or more electronic devices are disposed within the base member. In particular, the one or more electronics are disposed on the base member.

A plurality of motion sensors capable of capturing IR video, depth video, and RGB images. Periodically emitting IR pulses. Capturing IR video, depth video, and RGB images of a user. Generating a point cloud of the user. Generating a 3D model of the user including the point cloud of the user. Inputting the IR video, depth video, and RGB images into a machine learning model. Estimating a set of joints of the user in the 3D model. Tracking, based on the estimated set of joints of the user in the 3D model, the user's motion over a period of time. Determining a number of repetitions of an exercise performed by the user. Determining a feedback value. Calculating, based on the number of repetitions and the feedback value, a user exercise score. Providing, via a graphical user interface, the user exercise score and the feedback value to the user.

The present disclosure relates to method and system for signal processing rehabilitation exercise signals. The method comprises the step of receiving a first and a second motion signals associated with movements of a body part, wherein the motion signals comprise temporal data of the movements. The method further comprises the step of segmenting each of the first and second motion signals into a plurality of segmented signals based on gradients of the motion signals, wherein each segmented signal has consistent gradient. The method further comprises the step of automatically modifying the segmented signals to form multiple combinations of matching signals with similar gradients between the first and second motion signals, such that the first and second motion signals are in one-to-one correspondence. The method further comprises the step of extracting corresponding time intervals of the matching signals in the correspondences.

To more effectively improve mobility impairment of a user by supporting rehabilitation, this invention provides a rehabilitation support apparatus for supporting rehabilitation of a user with mobility impairment, including a requester that requests a target action in a three-dimensional virtual space, and a feedback unit that performs feedback that stimulates at least two of five senses to the user who has performed the target action almost at the same time as a timing of performing the target action.

An exercise feedback system monitors the performance of athletes wearing a garment with sensors while exercising. The sensors generate physiological data such as muscle activation data, heart rate data, or data describing the athlete's movement. The system extracts features from the physiological data and compares the features with reference exercise data to determine metrics of performance and biofeedback. Based on the physiological data, the system may also modify exercise training programs for the athlete. The exercise feedback system can display the biofeedback using visuals or audio, as well as modified exercise training programs, via the athlete's client device in real time while the athlete is exercising. By reviewing the biofeedback, the athlete may correct the athlete's exercise form to properly use the target muscles for the exercise, or change the certain workouts to personalize the training program.