A computer-implemented system includes a processing device configured to receive a plurality of user and blood vessel characteristics associated with a user, generate a selected set of user and blood vessel characteristics, determine, based on the selected set of the user and blood vessel characteristics, a probability that angiogenesis will occur, and generate, based on the probability and the selected set of the user and blood vessel characteristics, a treatment plan that includes one or more exercises directed to modifying the probability that angiogenesis will occur, and a treatment apparatus configured to implement the treatment plan while the treatment apparatus is being manipulated by the user.

The embodiments set forth a technique implemented by a computing device. The technique includes the steps of (1) receiving one or more characteristics associated with a user, wherein the one or more characteristics comprise personal information, performance information, measurement information, cohort information, familial information, comorbidity information, healthcare professional information, or some combination thereof; (2) determining, based on the one or more characteristics, one or more conditions of the user, wherein the one or more conditions pertain to cardiac health, pulmonary health, bariatric health, oncologic health, cardio-oncologic health, or some combination thereof; (3) based on the one or more conditions, identifying, using one or more trained machine learning models, one or more subgroups to present via the display, wherein the one or more subgroups represent different partitions of the one or more characteristics; and (4) presenting, via the display, the one or more subgroups.

Safe and effective exercise poses a specific set of challenges for subjects diagnosed with diabetes. These challenges include the coordination of exercise with blood glucose monitoring and insulin administration. Failure to coordinate these factors effectively can lead to various pathologies related to aberrant blood glucose levels. Presented herein are methods, systems, algorithms, computer program products, web portals, real-time live instruction, and computer-executable code for exercise guidance and instruction specific to diabetes relief and management. The systems as disclosed herein can help ameliorate, slow, or reduce a likelihood of developing a diabetic condition.

Safe and effective exercise poses a specific set of challenges for subjects diagnosed with diabetes. These challenges include the coordination of exercise with blood glucose monitoring and insulin administration. Failure to coordinate these factors effectively can lead to various pathologies related to aberrant blood glucose levels. Presented herein are methods, systems, algorithms, computer program products, web portals, real-time live instruction, and computer-executable code for exercise guidance and instruction specific to diabetes relief and management. The systems as disclosed herein can help ameliorate, slow, or reduce a likelihood of developing a diabetic condition.

The present disclosure relates to activity monitoring systems and methods for gating whether or not steps should be counted in an observation window based on whether a decision tree concludes there are consecutive step activities (versus no activity or other activities) in the observation window. Particularly, certain aspects are directed to a method that includes obtaining acceleration data for an observation window of an accelerometer, inputting two or more characteristics of the acceleration data into a decision tree to determine activity occurring within the observation window, assigning a first class to the observation window when the determined activity is associated with consecutive steps, assigning a second class to the observation window when the determined activity is not associated with consecutive steps, and when the first class is assigned to the observation window, determining a step count for the observation window using frequency analysis.

The disclosure provides methods, systems and devices for guiding breathing of a wearer through a breathing pattern. The system includes a wearable device with a non-rotating body and a rotating body, the rotating body configured to rotate about the non-rotating body, a position sensor coupled to the wearable device, a physiological sensor in communication with the wearer configured to detect at least one physiological parameter of the wearer, an actuator, a guiding element in communication with the actuator and configured to provide one or more guiding signals to the wearer, and a controller in communication with the actuator, the physiological sensor and the position sensor. The controller includes an input unit, a processing unit and an output unit for transmitting an output signal to the actuator to actuate the guiding element to provide one or more guiding signals to the wearer to guide the wearer through the breathing pattern.

A pedal drive system, in particular for an electric vehicle or a training apparatus, and for generating electrical power from muscle power of a user with at least one pedal and an electric generator, connected mechanically with said at least one pedal, is provided. To improve the haptic feel and feedback at the pedal, a control unit is provided for controlling a feedback torque, applied at said pedal, wherein the control unit comprises a haptic renderer, configured for control of said feedback torque based on at least one predefined pedal reference trajectory.

The present disclosure relates to activity monitoring systems and methods for gating whether or not steps should be counted in an observation window based on whether a decision tree concludes there are consecutive step activities (versus no activity or other activities) in the observation window. Particularly, certain aspects are directed to a method that includes obtaining acceleration data for an observation window of an accelerometer, inputting two or more characteristics of the acceleration data into a decision tree to determine activity occurring within the observation window, assigning a first class to the observation window when the determined activity is associated with consecutive steps, assigning a second class to the observation window when the determined activity is not associated with consecutive steps, and when the first class is assigned to the observation window, determining a step count for the observation window using frequency analysis.

Safe and effective exercise poses a specific set of challenges for subjects diagnosed with diabetes. These challenges include the coordination of exercise with blood glucose monitoring and insulin administration. Failure to coordinate these factors effectively can lead to various pathologies related to aberrant blood glucose levels. Presented herein are methods, systems, algorithms, computer program products, web portals, real-time live instruction, and computer-executable code for exercise guidance and instruction specific to diabetes relief and management. The systems as disclosed herein can help ameliorate, slow, or reduce a likelihood of developing a diabetic condition.

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.