Systems and methods for electronically creating and modifying a fitness plan are disclosed. The method may include receiving electronic user data, collecting electronic fitness data, and displaying a suggestion for a fitness activity based on the electronic user data and the electronic fitness data.

A head guard is provided. The head guard includes one or more sensors as part of an sensory input and communications system. The head guard wirelessly communicates data to remote computing devices for intelligent data collection.

A method is disclosed for using an artificial intelligence engine to modify resistance of pedals of an exercise device. The method includes generating, by the artificial intelligence engine, a machine learning model trained to receive measurements as input, and outputting, based on the measurements, a control instruction that causes the exercise device to modify, independently from each other, the resistance of the pedals. While a user performs an exercise using the exercise device, the method includes receiving the measurements from sensors associated with the pedals. The method includes determining, based on the measurements, a quantifiable or qualitative modification to the resistance provided by a pedal of the pedals. The resistance provided by another pedal of the pedals is not modified. The method includes transmitting the control instruction to the exercise device to cause the resistance provided by the pedal to be modified.

The present disclosure provides a system and method for accurately detecting exercises performed by a user through a combination of signals from a visual input device and from one or more sensors of a wearable device. For each workout type, an algorithm leverages multimodal inputs for automatic workout detection/identification. Using multiple sources of visual and gestural inputs to detect the same workout results in a higher confidence in the detection. Moreover, it allows for continued detection of the workout, including counting repetitions, even when one or more signals becomes unavailable, such as if the user moves out of a field of view of the visual input device.

A head guard is provided. The head guard includes one or more sensors as part of an sensory input and communications system. The head guard wirelessly communicates data to remote computing devices for intelligent data collection.

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.

An exercise device includes a frame, handlebars supported by the frame, and a computing device. The handlebars include a yoke that is movable relative to the frame, a biasing element positioned between the yoke and the frame, and a sensor configured to measure a movement of the yoke.

Systems, methods, and computer-readable mediums for generating, by an artificial intelligence engine, an exercise program comprising a first user energy score, wherein the method comprises generating, by the artificial intelligence engine, the exercise program including an exercise plan including a plurality of exercises. Each respective exercise is associated with user energy consumption metrics based at least on a metabolic equivalent of task (MET) value, and based on the user energy consumption metrics, the first user energy score is associated with the exercise program. The method includes receiving data pertaining to a plurality of users. The data includes physical activity goals the plurality of users desires to achieve. The method includes determining second user energy scores for the physical activity goals, and based on the first and second user energy scores, assigning, by the artificial intelligence engine, at least a subset of the plurality of users to the exercise program.

A method of varying a dynamic resistive force during a strength training exercise includes receiving a selection of the strength training exercise from a set of available strength training exercises and obtaining exercise logic for the strength training exercise from computer memory. The exercise logic provides instructions for generating a vector that defines the dynamic resistive force provided at an end effector of a strength training apparatus during the strength training exercise. The method includes determining a real-time geometric arrangement of a plurality of cables coupled to the end effector, generating, based on the real-time geometric arrangement of the plurality of cables and the exercise logic, time-varying operating setpoints for a plurality of actuator assemblies coupled to the plurality of cables, and exerting the dynamic resistive force at the end effector by controlling the plurality of actuator assemblies in accordance with the time-varying operating setpoints.

A method that includes receiving treatment data associated with a user capable of using a treatment device to perform a treatment plan. The method also includes receiving user related data (URD) associated with the use and receiving alignment data associated with the user while the user engages in at least one activity. The method also includes identifying, based on at least the treatment data, the URD, and the alignment data, at least one alignment characteristic associated with the user and modifying at least one aspect of the treatment plan in response to receiving, from a healthcare professional, treatment plan input including at least one modification to the at least one aspect of the treatment plan.