The present embodiments provide systems and methods for aggregating measurements captured by different technologies during a golf swing. By capturing measurements using different technologies, more accurate measurements may be provided to a user by selecting from the measurements, offsetting measurements based on the technologies used, and aligning measurements between devices. Further, by aggregating measurements received from different devices, additional features and functionality may be provided to the user that is absent from any one device used alone. Additionally, by storing the aggregated measurements, users, club fitters and instructors may access and leverage larger databases of measurements to better understand the user's golf swing and to provide better recommendations and instruction to the user.

Virtual and augmented reality sports training environments are disclosed. A user interacts with virtual players in a simulated environment of a virtual reality sporting event. In some embodiments, the user's actions and decisions are monitored by the simulated environment. The environment evaluates the user's performance, and provides performance feedback based on the user's decisions and timing. In one application, real life pitchers and their pitching data are tracked and replicated in a simulated pitching environment. A team of users may practice against a simulation of a pitcher they are about to compete against, swinging at pitches that they would see in a real game. Such environments may maximize effective practice time for users, and help develop better players with improved decision-making skills. Some embodiments include various pitch recognition training, which may be against replicated real-life pitchers.

Disclosed is an electronic device capable of automatically identifying a workout environment, such as a swimming pool environment or outdoor environment, based on position-associated information of the electronic device and providing workout information per the workout environment.

A fitness equipment control system is provided. The system includes a receiver and a mobile apparatus, and performs the operations: generating a first control signal based on a training course of a user; transmitting the first control signal to the receiver to make the receiver generates a signal which is readable by the fitness equipment according to the first control signal and transmit the readable signal to the fitness equipment; receiving at least one physiological signal from at least one of the wearable devices worn by the user; based on the training course and the at least one physiological signal, generating a second control signal; and when the second control signal is generated, transmitting the second control signal to the receiver, wherein the receiver generates a signal which is readable by the fitness equipment according to the second control signal and transmits it to the fitness equipment.

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.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for a basketball backboard. The basketball backboard includes a display screen, a plurality of sensors configured to generate sensor data regarding a shot attempt of a user, imaging devices configured to generate image data of the shot attempt, a speaker, and a control unit. The control unit can receive (i) the sensor data from the plurality of sensors and (ii) the image data from the imaging devices. Based on the received sensor data, the control unit can determine whether the shot attempt was successful. Based on the received image data and whether the shot attempt was successful, the control unit can generate analytics that indicate characteristics of the user and the shot attempt and recommendations for improving the shot attempt for subsequent shot attempts. The control unit can provide output data representing the analytics.

A walking training system, a harness, and an operation method capable of performing training effectively are provided. A walking training system according to an embodiment includes a harness attached to a trainee's trunk and a pulling unit configured to apply a pulling force to the harness, the harness includes a frame fixed to the trainee's trunk, an attaching member to which the pulling unit is attached, and a guide mechanism configured to enable a position of the frame relative to the attaching member to be variable in an up/down direction.

An exercise device includes a use-sensor connected to a flywheel. The use-sensor detects motion of the flywheel. If the flywheel is moving, a power interrupt on a power supply connects power to the exercise device. If the flywheel is not moving, the power interrupt disconnects power from the exercise device, thereby improving device safety.

The present disclosure discloses a step counting device that includes a motion detection circuit, a storage circuit and a processing circuit. The motion detection circuit detects a body movement to generate a detection signal. The processing circuit executes computer executable commands to execute the steps outlined below. The detection signal is received from the motion detection circuit. Key data points from the detection signal and representing a simplified waveform are approximated and stored in the storage circuit, each corresponding to a turning data point within a predetermined time period of the detection signal. Periodic waveform sections in the simplified waveform are identified, wherein an error value of waveform parameters between each two of the periodic waveform sections is smaller than a predetermined value. A step group count including a left step and a right step corresponding to each of the periodic waveform sections is accumulated.

A system and method for monitoring a walking activity are disclosed, which have three major components: a pre-processing phase, a step detection phase, and a filtering and post-processing phase. In the preprocessing phase, recorded motion data is received, reoriented with respect to gravity, and low-pass filtered. Next, in the step detection phase, walking step candidates are detected from vertical acceleration peaks and valleys resulting from heel strikes. Finally, in the filtering and post-processing phase, false positive steps are filtered out using a composite of criteria, including time, similarity, and horizontal motion variation. The method 200 is advantageously able to detect most walking activities with accurate time boundaries, while maintaining very low false positive rate.