Described herein are methods for determining a target musculoskeletal activity cycle (MSKC) to cardiac cycle (CC) timing relationship. The method may include detecting a signal responsive to a cyclically-varying arterial blood flow at a location on a head of a user; providing a recurrent prompt at a frequency of the heart pump cycle using the signal, such that the signal correlates with a magnitude of blood flow adjacent to the location, and the recurrent prompt is provided to guide the user to time performance of a component of a rhythmic musculoskeletal activity with the recurrent prompt; and guiding the user to adjust a timing of the component of the rhythmic musculoskeletal activity to substantially maximize a magnitude of the signal. In some embodiments, the method further includes generating the recurrent prompt by amplifying the sound generated by the blood flow in or in proximity to an ear of the user.

Systems and methods are provided for controlling infrared radiation (IR) sources of a sauna including tuning IR wavelength-ranges and radiated power-levels of IR sources, and directing IR to locations on a user's body. In one illustrative embodiment, a sauna may be provided having adjustable heat sources to emit IR at any wavelength resulting in a desirable radiation treatment for the sauna user. In another illustrative embodiment, a method is provided for tuning IR sources in a sauna.

Systems and methods for applying enhanced guided active compression decompression cardiopulmonary resuscitation are provided. Exemplary systems include a load cell, a handle, an adhesive pad. The handle and the adhesive pad are configured for magnetic coupling.

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 method also comprises, while the user uses an electromechanical machine to perform a first treatment plan for the user, receiving measurement data associated with the user. The method further comprises generating, by 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.

Computer-implemented systems, methods, and tangible, non-transitory computer-readable media for detecting abnormal heart rhythms of a user performing treatment plan with an electromechanical machine. The system includes, in one embodiment, an electromechanical machine, and one or more processing devices. The electromechanical machine is configured to be manipulated by a user while the user is performing a treatment plan. The processing devices are configured to receive, while the user performs the treatment plan, measurements. The processing devices also configured to determine, using machine learning models, a probability that the measurements satisfy a threshold for a condition associated with an abnormal heart rhythm. The processing devices are further configured to perform preventative actions.

A system comprising: a wrist-worn device configured to be worn on the wrist of a rescuer performing cardiopulmonary resuscitation (CPR), the wrist-worn device including: one or more sensors coupled with the wrist-worn device, the one or more sensors being configured to sense one or more parameters indicative of a fatigue level of the rescuer; and a sensor interface configured to provide the sensed parameters to one or more external computing devices via an interface; and a wearable computing device configured to be worn by a rescuer, the wearable computing device including: a device interface for receiving information related to CPR; and a display for displaying an indication of the received information.

A computer-implemented system includes one or more processing devices configured to receive attribute data associated with a user, determine, based on the attribute data, a first probability of improving a medical condition of the user subsequent to at least one of a medical procedure being performed on the user, a medical treatment being performed on the user, and a medical diagnosis, and generate, based on the first probability, a treatment plan that includes one or more exercises directed to modifying the first probability. A treatment apparatus is configured to enable implementation of the treatment plan.

A system and method determines a user's compliance with a prescribed therapeutic pneumatic compression treatment by applying external pressure to a body limb using a pneumatic compression sleeve having a pneumatically fillable cell; measuring pneumatic pressure within the pneumatically fillable cell; generating a pressure signal corresponding to the measured pneumatic pressure; determining biological events associated with the user based upon the pressure signal; generating a positive detection signal for each determined biological event associated with the user; and determining a user's compliance with a prescribed therapeutic pneumatic compression treatment when a predetermined number of positive detection signals have been generated within a predetermined time interval.

A system and method determines a user's compliance with a prescribed therapeutic pneumatic compression treatment by applying external pressure to a body limb using a pneumatic compression sleeve having a pneumatically fillable cell; measuring pneumatic pressure within the pneumatically fillable cell; generating a pressure signal corresponding to the measured pneumatic pressure; determining biological events associated with the user based upon the pressure signal; generating a positive detection signal for each determined biological event associated with the user; and determining a user's compliance with a prescribed therapeutic pneumatic compression treatment when a predetermined number of positive detection signals have been generated within a predetermined time interval.

A soft-inflatable exosuit for knee rehabilitation is fabricated in two different beam-like structures (I and O cross-section actuators) and mechanically characterized for their torque performance in knee-extension assistance. The fabrication procedure of both types of actuators is presented as well as their integration into a light-weight, low-cost and body-conforming interface. To detect the activation duration of the device during the gait cycle, a soft-silicone insole with embedded force-sensitive resistors (FSRs) is used. In evaluation studies, the soft inflatable exosuit device is tested for its ability to reduce muscle activity during the swing phase of the knee. Using sEMG (surface electromyography) sensors, the rectus femoris muscle group of a healthy individual is recorded while walking on a treadmill at a constant speed, with and without the soft device.