Described herein are systems and methods of guiding a user to achieve musculoskeletal counterpulsation. A method may include receiving a cardiovascular cycle signal from a first sensor; determining a heart rate of the user based on the cardiovascular cycle signal; receiving a rhythmic musculoskeletal activity timing signal from a second sensor; determining an actual musculoskeletal activity cycle (MSKC) to cardiovascular cycle (CC) timing relationship; comparing the actual MSKC to CC timing relationship to a target MSKC to CC timing relationship; providing a recurrent prompt to the user as a timing indication for performance of a rhythmic musculoskeletal activity to guide the user to achieve a musculoskeletal activity cycle rate (MSKR) that approaches the target MSKC to CC timing relationship; and altering a feature of the recurrent prompt based on a determined alignment between the actual MSKC to CC timing relationship and the target MSKC to CC timing relationship.

Disclosed are systems and methods for a computerized framework that leverages artificial intelligence (AI) / machine learning (ML) mechanisms to assign selected individuals to military operations. The disclosed framework comparatively analyzes an ops sheet of a military operation and profile data related to a user(s), and automatically determines user(s) who are optimal for the operation. The determined user or users possess the physical and/or intellectual capabilities to accurately and efficiently, with respect to real-world and electronic resources, perform and complete the operation. The disclosed framework provides a computerized platform that selects users for highly specific tasks based on the users’ analyzed skill sets, and based on computerized determinations of how such users are predicted to perform using those skill sets, securely and/or confidentially provides the users access to information related to the operation.

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.

A system, method, and wireless earpieces for implementing a virtual assistant. A request is received from a user to be implemented by wireless earpieces. A virtual assistant is executed on the wireless earpieces. An action is implemented to fulfill the request utilizing the virtual assistant. The wireless earpieces may be a set of wireless earpieces and the virtual assistant may be implemented independently by the wireless earpieces.

An athletic training system has a data recording system and a data engine. The data recording system is configured to record an athletic competition event. The event may have a first team of players competing against a second team of players. The data engine is configured to receive data associated with the recorded athletic competition event. The data engine processes the data and displays the data as a replay of the event in animated form.

A method is disclosed for using an artificial intelligence engine to interact with a user of an exercise device during an exercise session. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive data as input, and based on the data, providing an output. While a user performs an exercise using the exercise device, the method includes receiving the data from an input peripheral of a computing device associated with the user. Based on the data being received from the input peripheral, the method includes determining, via the machine learning model, the output to control an aspect of the exercise device.

A computer-implemented method including receiving, at a computing device, a first treatment plan designed to treat a sexual performance health issue of a user. The first treatment plan comprises at least two exercise sessions that, based on the sexual performance health issue, enable the user to perform an exercise at different exertion levels. While the user uses a treatment apparatus to perform the first treatment plan for the user, the computing device receives cardiovascular data from one or more sensors configured to measure the cardiovascular data associated with the user, and transmits the cardiovascular data. A machine learning model is used to generate a second treatment plan that modifies at least one exertion level, and the modification is based on a standardized measure comprising perceived exertion, the cardiovascular data, and the cardiovascular health issue of the user. The method includes receiving the second treatment plan.

A computer-implemented system includes one or more processing devices configured to receive attribute data associated with a user, generate, based on a pulmonary condition of the user, a selected set of the attribute data, determine, based on the selected set of the attribute data, a first probability of improving a pulmonary condition of the user subsequent to at least one of a pulmonary procedure being performed on the user, a pulmonary treatment being performed on the user, and a pulmonary 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 method for assisting a patient in physical rehabilitation, the method being executed by a controller, and the controller being configurable with at least one physical rehabilitation strategy and being communicatively connected with a respiratory device and an exercise device. The method includes controlling at least one of a device setting of the respiratory device and a device setting of the exercise device, based on a target physical rehabilitation strategy among the at least one physical rehabilitation strategy.

An apparatus includes a first cable, a first motor configured to provide first tension to the first cable, a second cable coupled to the first cable at an end effector, and a second motor configured to provide second tension to the second cable. The first cable and the second cable are routed such that the first tension and the second tension combine to provide a force on the end effector. At least one of the first tension or the second tension is directed at least partially in a downward direction.