Exemplary embodiments of the present disclosure are directed to systems, methods, and computer-readable media configured to autonomously generate personalized recommendations for a user before, during, or after a round of golf. The systems and methods can utilize course data, environmental data, user data, and/or equipment data in conjunctions with one or more machine learning algorithms to autonomously generate the personalized recommendations.

Disclosed is a technical training garment configured for use with modular, interchangeable electronics and resistance modules. The garment provides resistance to movement throughout an angular range of motion and tracks biomechanical parameters such as stride length, stride rate, angular velocity and incremental power expended by the wearer. The garment may be low profile, and worn by a wearer as a primary garment or beneath or over conventional clothing. Alternatively, the device may be worn as a supplemental training tool during conventional training protocols.

Methods, systems, and devices for athlete monitoring are described. The method may include receiving, at a gateway device, physiological measurement data from a sensor configured to transmit wireless signals according to a Bluetooth 5 protocol. The method may further include identifying a user associated with the received physiological measurement data based at least in part on an identity of the sensor and storing at least the received physiological measurement data. In some cases, the method may include receiving the physiological measurement data via one or more of a plurality of repeaters that are configured to transmit wireless signals according to the Bluetooth 5 protocol.

Systems and methods provide feedback to at least one participant in a field of play. A performance analysis device determines performance information of each participant in the field of play, where the performance information is based upon at least one of determined location, speed, path, acceleration and biometrics of said each participant. At least one output device provides real-time feedback to the at least one participant based upon the performance information. The real-time feedback comprises performance information of the at least one participant and/or performance information of one or more other participants in the field of play.

A stool is provided that provides a raised heel squat position to a user that engages the stool. The raised heel squatting position promotes a healthy and productive experience on a toilet. The stool may be collapsible for easier storage and transportation. The stool may be adjustable to provide custom fittings to different size users. Additionally, the stool may be intelligent and may provide a customized immersive experience to a person on a toilet.

Embodiments of the invention provide apparatus, systems, and methods wherein pre-event and post-event analyte concentration readings associated with an event are collected and processed to determine a numerical delta. The numerical delta may be displayed on a visual display to aid in a ready determination of the affect that the event (alone or in combination with medication and/or insulin dosages) had on the analyte concentration levels. Medication and/or insulin dosages may be displayed alongside the numerical delta to gauge immediate relationships between numerical delta, dosage, and/or an associated event. Apparatus and systems for calculating and displaying the numerical delta are described, as are other aspects.

An electronic device includes a display, a memory configured to store priorities of sensors included in at least one of the electronic device and an external electronic device connected to the electronic device through a communication circuit, the priorities being set based on a type of exercise, a processor electrically connected to the display and the memory, and a connection interface configured to electrically connect the processor with the sensors. The processor is configured to select at least one first sensor of the sensors, based on the stored priorities of the sensors when the type of the exercise is designated, to designate the first sensor as an exercise measuring sensor that measures the exercise, to obtain first sensing data, based on the exercise, through the exercise measuring sensor, to analyze the first sensing data, and to provide exercise information based on the analyzed result of the first sensing data.

A wearable device such as a garment is disclosed, having at least one resistance element at a motion segment such as a hip or knee. The garment includes at least one sensor, for sensing a parameter. Electronics are provided for processing the sensed parameter, and for providing feedback. Feedback may be in the form of proprioceptive tactile or audible feedback, or in the form of an adjustment of a performance parameter of the wearable device. In one implementation, resistance to movement of the wearer is adjusted up or down in response to changes in power output by the wearer.

Methods, systems, and computer-readable mediums for generating, by an artificial intelligence engine, treatment plans for optimizing a user outcome. The method comprises receiving attribute data associated with a user. The attribute data comprises one or more symptoms associated with the user. The method also comprises, while the user uses a treatment apparatus to perform a first treatment plan for the user, receiving measurement data associated with the user. The method further comprises generating, by the artificial intelligence engine configured to use one or more machine learning models, a second treatment plan for the user. The generating is based on at least the attribute data associated with the user and the measurement data associated with the user. The second treatment plan comprises a description of one or more predicted disease states of the user. The method also comprises transmitting, to a computing device, the second treatment plan for the user.

A computer-implemented system may include an electromechanical machine configured to be manipulated by a user while the user performs a treatment plan, an interface comprising a display configured to present information associated with the treatment plan, and a processing device configured to receive, from one or more data sources, information associated with the user, wherein the information comprises one or more risk factors associated with a cardiac condition or a cardiac outcome, generate, using one or more trained machine learning models, the treatment plan for the user, wherein the treatment plan is generated based on the information associated with the user, and the treatment plan comprises one or more exercises associated with managing the one or more risk factors in order to reduce a probability of a cardiac intervention for the user, and transmit the treatment plan to cause the electromechanical machine to implement the one or more exercises.