7 results about "Health program" patented technology

This provides useful information to help health insurers and other organizations conducting health programs implement effective measures. [Solution] The program relating to this disclosure is a program that causes a computer to function as an information processing device for supporting a health business, wherein the information processing device includes: prediction means for predicting the health risk of each of the multiple subjects from the health information of the multiple subjects; evaluation means for dividing the multiple subjects into two or more groups with respect to measures for the health business, determining the health risk of each of the two or more groups, and evaluating the health risk of the two or more groups; and presentation information generation means for generating presentation information to present to the user the effects of the measures for the health business based on the evaluation means.

A school food and beverage recognition and processing system includes a self-checkout system that attaches to a school meal line. The self-checkout system uses multiple cameras to obtain images of a student for identification and images of a meal, identify contents of the meal, and determine whether the meal qualifies for reimbursement through a health program or agency. In addition to determining meal reimbursement qualifications, the self-checkout system tracks the meals and items sold for inventory and purchasing purposes. The self-checkout system sends reports to the school or administration agency including reimbursement information, inventory information, and customer information. This information is used to update a student's prepaid school meal account and track transactions.

The invention discloses a post-examination health promotion management method and system based on multi-modal data fusion, and relates to the technical field of medical health information, and the method comprises the steps: carrying out the deep fusion of authoritative clinical examination data and dynamic daily behavior data, and enabling health suggestions to have better medical pertinence and safety. The health task is interesting, scenarized and fragmented, abstract health indexes are converted into concrete daily tasks, and real-time feedback and forward excitation are combined, so that the health becomes interesting and easy to persist. The change from one physical examination to long-term health management is realized, and a continuous optimization closed loop of evaluation, planning, execution, monitoring, feedback and adjustment is formed. Through the automatic evaluation and recommendation system, the scientificity and efficiency of health scheme making are greatly improved, and meanwhile, the accuracy and individuation degree of scheme recommendation are ensured. An optimal intervention strategy is learned from a large amount of user data, and a recommendation algorithm is continuously improved, so that a health promotion scheme becomes more and more accurate.

A system is disclosed that monitors participants in health-related programs, such as weight loss or exercise programs, and that provides automated, personalized health coaching to the program participants. The system includes breath analysis devices that are used by the program participants to generate ketone measurements, and includes a mobile application that runs on mobile devices of the participants and communicates with corresponding breath analysis devices. The system operates generally by monitoring ketone levels (such as acetone levels) and other attributes of the participants and by making personalized, machine-generated changes or updates to such programs to maintain program effectiveness and engagement. In some embodiments the system uses primary and secondary process flows to collect from the participants information that is used to select or recommend health program modifications.

This invention discloses a personalized health program matching method based on electromyography (EMG) pressure, belonging to the field of pelvic floor rehabilitation therapy technology. First, it combines the FSFI scale with pelvic floor EMG pressure assessment data to calculate scores in five dimensions: tightness, excitability, sensitivity, relaxation, and hydration. A personalized initial training program is matched based on the minimum value of each dimension. Second, it extracts pressure data from fast-twitch, slow-twitch, and endurance testing phases, and determines the template adjustment coefficient based on the deviation rate between actual and theoretical values, dynamically adjusting the program's difficulty. Simultaneously, based on the maximum tolerable pressure value of the pelvic floor, combined with the total number of courses and the current session, it calculates the target value for electrical stimulation inflation and sets safety limits. Finally, it determines whether to add hypertonic relief courses based on the pre- and post-pelvic floor resting deviation, and adds stretching training components based on the initial and tolerable EMG values.

A biometric-authenticated wearable system for remote monitoring, chronic disease management, elderly care, occupational therapy, and mental health rehabilitation is disclosed. The system uses fingerprint, facial, and voice recognition to securely associate physiological data with individual users. It monitors vital signs including heart rate, oxygen saturation, movement, and stress indicators, and transmits data to EMR / EHR systems in real time with privacy compliance. Machine learning modules assess disease risk, detect mobility decline, and perform sentiment-based analysis of speech and behavior. The system supports therapy compliance tracking across wellness programs and daily living tasks. The system may optionally employ large language models (LLMs) to enhance contextual understanding and sentiment interpretation from unstructured speech or text inputs. Real-time alerts are generated for health anomalies or non-compliance, enhancing clinical interventions. This integrated platform advances personalized and secure care through biometric authentication, predictive analytics, and seamless EMR / EHR integration.

A system is disclosed that uses profiles of users, including monitored ketone levels of the users, to assess effectiveness levels of health programs (such as weight loss programs) assigned to the users, and to select health program modifications for the users. The system may use a machine learning (artificial intelligence) algorithm to adaptively learn how to classify users and to select messaging and behavioral modifications for the users. For example, in some embodiments the system classifies the users and provides associated health program recommendations using a computer model trained with expert-classified user data records. As another example, a set of rules may be used to generate the health program recommendations and related messaging, and the set of rules may automatically be modified over time based on feedback data reflective of health program effectiveness levels produced by such rules. In some embodiments the system includes a mobile application that runs on mobile devices of users and communicates wirelessly with breath analysis devices of the users. The mobile application may also communicate with a server-based system that generates the health program recommendations.