4 results about "Individual exercises" patented technology

The application discloses a kind of exercise monitoring management systems for diabetic foot patients, specifically relates to the field of diabetic patient monitoring, for solving the problem that existing exercise monitoring mode is difficult to effectively identify individualized risk trend and implement precise intervention;Through the pressure acquisition module, the main pressure area of the plantar under different gait is obtained, the pressure analysis module constructs the time sequence evolution track of the plantar stress direction, the electrical impedance acquisition module synchronously constructs the electrical impedance response sequence in the main pressure area of the plantar, the matrix construction module is jointly encoded into two-dimensional time sequence matrix of double channel, the lag extraction module analyzes the impedance lag area, the risk analysis module identifies the spatial overlap degree of impedance lag area and the main pressure area of the next cycle, the strategy construction module constructs risk trend turning point index with minimum point of coincidence degree and establishes individual exercise monitoring strategy based on different gait parameters, finally drives monitoring terminal to realize dynamic exercise intervention and prompt.

This invention relates to the field of sports and health management technology, and discloses a method, device, electronic device, and storage medium for generating exercise prescriptions. The method includes: acquiring user data; generating an exercise prescription and a predicted adaptation index based on this data using a large language model; instructing the user to exercise according to the exercise prescription and acquiring relevant data for the current exercise stage; if the preset exercise goal is not achieved, performing a three-dimensional ability assessment to obtain a comprehensive muscle strength index; quantifying the user's actual adaptation index at the current exercise stage; determining exercise intensity constraint parameters based on the actual adaptation index; optimizing the large language model; regenerating the exercise prescription and predicted adaptation index using the optimized large language model; and returning to the step of instructing the user to exercise according to the exercise prescription until the preset exercise goal is achieved. This invention, through a closed-loop feedback mechanism, enables the model to continuously absorb individual user exercise data, making the exercise prescription conform to individual exercise patterns and improving the accuracy and scientific nature of the exercise prescription.

The application provides a method and device for determining the intensity of an individual's exercise, which comprises: obtaining individual exercise information; inputting the individual exercise information into an individual exercise intensity determination model to obtain an individual exercise intensity grade; wherein the individual exercise intensity determination model is obtained based on supervised source domain samples and is tested for performance by unsupervised target domain samples; the source domain samples comprise an individual exercise information sample training set and corresponding individual exercise intensity grades, and the target domain samples comprise an individual exercise information sample test set and corresponding individual exercise intensity grades. The method and device are used to solve the defects of low accuracy and high data collection cost in the prior art, and achieve high accuracy and low cost in the identification of the intensity of an individual's exercise.

The invention provides an individual difference-oriented ankle pump motion multi-source signal adaptive feature modeling method, which comprises the following steps of: acquiring an active ankle pump motion multi-source signal of a user without task constraint, and determining an individual safe and effective motion parameter interval; establishing a personalized task parameter mapping relationship associated with a preset training task based on the parameter interval; driving the user to execute a training task based on the mapping relation, synchronously collecting multi-source time sequence signals, and extracting basic motion characteristics representing the motion control ability of the user from the signals; fusing the basic motion features and the task performance data, and constructing an individual difference feature model for quantifying the matching degree between the user state and the task configuration; according to the method, the current task adaptation degree is evaluated based on the individual difference feature model, the training task is adaptively adjusted according to the evaluation result, the strong constraint influence of the task can be stripped from the active motion signal, the individual motion control difference of the user is truly reflected, and the adaptive accurate matching of the training task is realized accordingly.