An exercise machine accessory is disclosed. In one embodiment, a resistance identifier is configured to identify resistance for an exercise machine associated with the exercise machine accessory, wherein the resistance identifier is coupled to the exercise machine. In one embodiment, a motion identifier is configured to identify exercise motion for a user of the exercise machine. In one embodiment, a communications module is configured to communicate with the user of the exercise machine, wherein the communications module is coupled to the resistance identifier and the motion identifier.

An electromechanical device for rehabilitation includes pedals coupled to radially-adjustable couplings, an electric motor coupled to the pedals via the radially-adjustable couplings, and a control system including a processing device operatively coupled to the electric motor. The processing device configured to, responsive to a first trigger condition occurring, control the electric motor to operate in a passive mode by independently driving the radially-adjustable couplings rotationally coupled to the pedals. The processing device also configured to, responsive to a second trigger condition occurring, control the electric motor to operate in an active-assisted mode by measuring revolutions per minute of the radially-adjustable couplings, and cause the electric motor to drive the radially-adjustable couplings when the measured revolutions per minute satisfy a threshold condition, and responsive to a third trigger condition occurring, control the electric motor to operate in a resistive mode by providing resistance to rotation of the radially-adjustable couplings.

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 method for facilitating cardiac rehabilitation among eligible users is disclosed. The method includes the steps of (1) receiving health information associated with one or more users; (2) for each user of the one or more users: determining, based on health information associated with the user, a respective eligibility of the user for cardiac rehabilitation; (3) determining, based on the respective eligibilities, that at least one user of the one or more users is eligible for cardiac rehabilitation; (4) generating a treatment plan for the at least one user, where the treatment plan pertains to a cardiac rehabilitation that is specific to the at least one user; and (5) assigning the treatment plan to at least one electromechanical machine to enable the user to perform the cardiac rehabilitation.

A system for reducing trauma in the head or neck of a living being caused by acceleration of the head relative to a torso of the living being within a range of motion. The system includes a support engaging at least one of the head, neck, and shoulder of the living being without limiting the range of motion of the head or neck relative to the torso; a sensor in electrical communication with the system; a user interface in electrical communication with the sensor; and a damper associated with the support that is configured to mitigate the position, speed or acceleration of the head relative to the torso in response to information received by the sensor or user interface.

The present disclosure provides an electronic apparatus. The electronic apparatus includes a sensor and a processor electrically connected to the sensor and configured to generate information indicating a start of an activity when first data indicating that an activity of the electronic apparatus occurs is received from the sensor and generate information indicating a start of an exercise when second data indicating that the activity is associated with the exercise is received from the sensor.

One or more accelerometers embedded with an earbud and/or a set of earphones are able to sense a moving pace of a user. Based on a moving pace of the user, a signal is sent to a remotely connected electronic device. The electronic device is able to separately increase and decrease a beat or rhythm of the audio from the electronic device based on a pace of the user. In some embodiments, an audio alert is sent to the user to inform the user of pace and whether the user has increased or decreased their pace. Additionally, in some embodiments, a program stored on the electronic device is used to compare the user's current progress and/or speed based on past runs and workouts.

A computer-implemented method is disclosed. The method includes determining whether one or more messages have been received from at least one of an electromechanical machine, a sensor, and an interface. Then the one or more messages may pertain to at least one of a user and a usage of the electromechanical machine by the user. The electromechanical machine may be configured to be manipulated by the user while the user is performing a treatment plan. The method also includes, responsive to determining that the one or more messages have not been received, determining, using one or more machine learning models, one or more preventative actions to perform. The method also includes causing the one or more preventative actions to be performed.

One or more accelerometers embedded with an earbud and/or a set of earphones are able to sense a moving pace of a user. Based on a moving pace of the user, a signal is sent to a remotely connected electronic device. The electronic device is able to separately increase and decrease a beat or rhythm of the audio from the electronic device based on a pace of the user. In some embodiments, an audio alert is sent to the user to inform the user of pace and whether the user has increased or decreased their pace. Additionally, in some embodiments, a program stored on the electronic device is used to compare the user's current progress and/or speed based on past runs and workouts.

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.