A pelvis exercising system including: a movable seat, sized and shaped to support a user by his pelvis; a vertical supporter which supports the seat above the ground; a flexible connector mounted between the vertical supporter and the seat; wherein, the seat comprises a front portion and a rear portion extending upwardly away from a central arch, each of the rear and front portions comprises a length which is long enough to support a front portion and rear portion of the user's pelvis, while not significantly restricting the abdomen and lower back from bending in relation to a sagittal plane of the seat. A sensor positioned to measure movement of said seat relative to a base, wherein the sensor provides measured values of the seat relative to the base to a processor; and the processor controls a device based on the measured values. Related apparatus and methods are also described.

A system for transmitting power and data between two circuit boards may include a fixed circuit board having a primary coil and a rotatable circuit board having a secondary coil. The system may further include a sensor in communication with the secondary coil of the rotatable circuit board. The fixed circuit board's primary coil may be inductively coupled to the secondary coil and may provide power and receive data from the sensor when inductively coupled to the secondary coil.

A system for respiratory training including a housing, a respiratory air channel disposed within the housing, a sensor configured to detect a breathing indicator and transmit a breathing indicator signal, a haptic device disposed within the housing, a processor operatively coupled to the sensor and the haptic device, and a memory device operatively coupled to the processor. The memory device includes instructions that, when executed by the processor, cause the processor to receive the breathing indicator signal from the sensor; generate a breath determination based on the breathing indicator signal; and responsive to the breath determination, cause the haptic device to generate a vibration.

Disclosed is a technical training garment configured for use with modular, interchangeable biomechanics units and or resistance modules. The garment may provide resistance to movement throughout an angular range of motion and or tracks a variety of biomechanical parameters such as stride length, stride rate, angular velocity and 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 or athletic uniform. The device may be worn as a supplemental training and or diagnostic tool during conventional training protocols, or as a biomechanics or biometric data capture device during competition.

Disclosed is a smart, physiology monitoring mouthguard (SPMM) system and method for capturing various physiological data of athletes in real-time for health monitoring. The system is configured to provide real-time and/or recorded physiological data of an athlete to a user, and may be configured to record physiological data of the athlete for later retrieval using sensors and communication systems. Sensors may be chosen based on the anticipated activity or sport, the health and age of the athlete, and size and power requirements of the device. Sensors may include accelerometers, gyroscopes, thermometers, hydrometers, pH, electrolyte (e.g., potassium, sodium, etc.) sensors, and the like. These and other sensors may be configured to measure different physiological data of the athlete, including impact, body temperature, hydration, illness, heart rate, and the like. In some embodiments, sensors on the mouthguard are integrated with external sensors (e.g., accelerometers on a helmet, chest-worn heart rate monitor) on the athlete to provide additional or more accurate physiological data.

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.

Systems and methods for identifying a condition of a user. A treatment apparatus is configured to be manipulated by the user for performing an exercise, and an interface is communicably coupled to the treatment apparatus. One or more sensors are configured to sense one or more characteristics of an anatomical structure of the user. A processing device and a memory is communicatively coupled to the processing device. The memory includes computer readable instructions, that when executed by the processing device, cause the processing device to: receive, from the sensors, one or more sensor inputs representative of the one or more of characteristics of the anatomical structures; calculate an infection probability of a disease based on the one or more characteristics of the anatomical structures; and output, to the interface, a representation of the infection probability.

A computer-implemented system may include a treatment device configured to be manipulated by a user while the user is performing a treatment plan, a patient interface comprising an output device configured to present telemedicine information associated with a telemedicine session, and a first computing device configured to: receive treatment data pertaining to the user while the user uses the treatment device to perform the treatment plan; identify at least one aspect of the at least one measurement pertaining to the user associated with a first treatment device mode of the treatment device; determine whether the at least one aspect of the measurement correlates with a secondary condition of the user; and, in response to a determination that the at least one aspect of the at least one measurement is correlated with the at least one secondary condition of the user, generate secondary condition information indicating at least the secondary condition.

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.

An interactive exercise system includes a mechanical support system and a display module held by the mechanical support system. A mirror element is attached to at least partially cover the display module. At least one movable arm is connected to the support system and at least one force-controlled component is connected to the mechanical support system. The force-controlled component can be graspable by a user and allows for a range of exercise types and programs.