Self-health intervention management system for patients with sarcopenia

Abstract

The invention discloses a sarcopenia patient self-health intervention management system, which comprises a system overall architecture module, a personalized scheme generation module, a monitoring and feedback module, an evaluation and adjustment module and a data storage and analysis module, and is characterized in that the output end of the system overall architecture module is electrically connected with the input end of the personalized scheme generation module; the invention relates to the technical field of medical health management. According to the self-health intervention management system for the patients with sarcopenia, factors of different age groups, genders, physical conditions, personal preferences and the like are comprehensively considered, exercise and nutrition intervention are organically combined, personalized exercise and nutrition plans are generated, and the self-health intervention management system for the patients with sarcopenia is provided for the patients with sarcopenia. The limitation of single movement or nutrition intervention and lack of personalized schemes in the prior art is overcome, the prognosis condition of the patient with sarcopenia can be more effectively improved, and the patient is comprehensively assisted to improve the muscle quality, enhance the muscle strength, improve the body function and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of medical health management, and specifically to a self-health intervention management system for sarcopenia patients. Background Art

[0002] Sarcopenia is a syndrome characterized by a decrease in skeletal muscle mass and function with aging, which can lead to many adverse consequences such as decreased mobility, increased risk of falls, and reduced quality of life.

[0003] At present, intervention measures for sarcopenia mainly focus on resistance exercise and optimizing nutritional intake. However, single exercise or nutritional intervention has obvious limitations in improving sarcopenia. For example, exercise intervention alone may not achieve the ideal muscle growth effect due to insufficient nutritional support; and relying solely on nutritional supplements, if there is a lack of appropriate exercise stimulation, the improvement of muscle function will also be limited. In addition, the existing intervention methods lack a comprehensive plan that organically integrates exercise and nutrition, and most of them do not fully consider the physical differences of sarcopenia patients of different age groups, making it difficult to achieve personalized intervention. At the same time, during the intervention process, there is a lack of effective monitoring and evaluation mechanisms, making it difficult to accurately quantify the intervention effect, and thus it is impossible to adjust the intervention strategy in a timely manner, which is not conducive to the long-term health management of patients. In this regard, we propose a self-health intervention management system for sarcopenia patients to solve the above problems. Summary of the invention

[0004] In view of the deficiencies of the prior art, the present invention provides a self-health intervention management system for sarcopenia patients, which solves the problems raised in the background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a self-health intervention management system for sarcopenia patients, including a system overall architecture module, a personalized program generation module, a monitoring and feedback module, an evaluation and adjustment module, and a data storage and analysis module. The output end of the system overall architecture module is electrically connected to the input end of the personalized program generation module, the output end of the personalized program generation module is electrically connected to the input end of the monitoring and feedback module, the output end of the monitoring and feedback module is electrically connected to the input end of the evaluation and adjustment module, and the output end of the evaluation and adjustment module is electrically connected to the input end of the data storage and analysis module.

[0006] Preferably, the overall architecture module of the system includes a user interaction unit and a data integration unit, the user interaction unit is used to collect basic information and health status of the user, and display personalized exercise and nutrition plans, monitoring feedback information and evaluation results, the data integration unit is used to integrate user information, monitoring data and evaluation data to ensure data accuracy, completeness and consistency, the personalized plan generation module includes a data acquisition unit and an exercise plan generation unit, the data acquisition unit is used to collect user age, gender, weight, muscle mass, muscle strength, physical function status, serum protein, hemoglobin level, personal exercise preferences and dietary preference information, the exercise plan generation unit formulates a personalized exercise plan according to the user's physical fitness assessment results and personal preferences, including determining the aerobic exercise method, intensity and frequency, as well as resistance training movements, intensity and frequency, and provides centralized training or video remote guidance according to the exercise environment.

[0007] Preferably, the monitoring and feedback module includes a motion monitoring unit and a diet monitoring unit. The motion monitoring unit monitors the user's motion data in real time with the help of motion sensors, including the type, intensity, time, frequency and posture of exercise, and determines whether the exercise meets the standard based on preset standards. If not, a reminder and correction suggestion are issued. The diet monitoring unit records the user's daily diet intake through a diet recording tool, and analyzes whether the nutrient intake complies with the personalized nutrition plan based on the nutrition database. If not, adjustment suggestions are given. The evaluation and adjustment module includes a health check unit and an effect evaluation unit. The health check unit regularly reminds the user to undergo a health check, and the examination items include muscle strength test, muscle mass measurement and physical function assessment, and enters the examination results. The effect evaluation unit uses an evaluation algorithm to comprehensively evaluate the intervention effect based on the motion monitoring data, diet monitoring data and health examination results.

[0008] Preferably, the data storage and analysis module includes a database unit and a data analysis unit. The database unit constructs a database to store user personal basic information, exercise data, diet data, health check data and intervention plan data, and has data backup and recovery functions. The data analysis unit uses data analysis algorithms to mine and analyze data in the database to provide a basis for personalized program optimization and intervention strategy adjustment.

[0009] Preferably, in the exercise plan generating unit, the intensity of aerobic exercise is set to reach 60%-75% of the maximum heart rate, 3-5 times per week; the intensity of resistance training is set to 70%-85% of the maximum weight, 2-3 times per week.

[0010] Preferably, the motion sensor in the motion monitoring unit is a MEMS accelerometer and a gyroscope, which is worn on the wrist, ankle, etc., and is connected to the user's smart terminal via Bluetooth or other wireless communication technologies.

[0011] Preferably, the diet recording tool in the diet monitoring unit is a mobile phone application, which has a food database and intelligent recognition function, and can enter diet information by searching for food names or scanning food barcodes.

[0012] Preferably, the health check unit formulates a personalized regular health check plan based on the user's age, gender, and severity of sarcopenia. The examination items include grip strength test, walking speed test, muscle mass assessment, balance ability test, stair climbing ability test, 5 sit-up tests, and muscle mass measurement using dual-energy X-ray absorptiometry and other technologies.

[0013] Beneficial Effects

[0014] The present invention provides a self-health intervention management system for patients with sarcopenia. Compared with the prior art, it has the following beneficial effects:

[0015] (1) The system of the present invention comprehensively considers multiple factors such as different age groups, genders, physical conditions and personal preferences, organically combines exercise and nutritional intervention, and generates personalized exercise and nutrition plans, overcoming the limitations of existing single exercise or nutritional intervention and the lack of personalized plans. It can more effectively improve the prognosis of patients with sarcopenia and comprehensively help patients improve muscle mass, increase muscle strength and improve physical function.

[0016] (2) The monitoring and feedback module tracks the user's exercise and diet in real time, provides timely reminders and corrective suggestions, and uses the evaluation and adjustment module to regularly conduct comprehensive evaluations of the intervention effect, and adjusts the intervention plan in a timely manner based on the results, so that the entire intervention process forms an effective closed-loop management. This can not only accurately control the actual effect of the intervention, but also help improve patients' compliance with intervention measures, ensure that the intervention behavior continues to advance at a scientific and reasonable pace, and thus maximize the role of the intervention.

[0017] (3) The data storage and analysis module can be used to store and conduct in-depth mining and analysis of massive amounts of user data. For example, by analyzing the differences in responses of different user groups to interventions, and the relationship between exercise and dietary data and sarcopenia improvement indicators, more accurate suggestions can be provided for the sarcopenia health management of different individuals, and the risk of disease progression can be predicted in advance, thereby optimizing personalized intervention plans, improving the accuracy and foresight of health management, and helping patients better cope with the health challenges brought about by sarcopenia. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a system block diagram of the present invention;

[0019] Figure 2 It is a schematic diagram of the overall system architecture module of the present invention;

[0020] Figure 3 A schematic diagram of a personalized solution generation module of the present invention;

[0021] Figure 4 It is a schematic diagram of the monitoring and feedback module of the present invention;

[0022] Figure 5 It is a schematic diagram of the evaluation and adjustment module of the present invention;

[0023] Figure 6 It is a schematic diagram of the data storage and analysis module of the present invention.

[0024] In the figure: 01, system overall architecture module; 02, personalized plan generation module; 03, monitoring and feedback module; 04, evaluation and adjustment module; 05, data storage and analysis module; 011, user interaction unit; 012, data integration unit; 021, data acquisition unit; 022, exercise plan generation unit; 031, exercise monitoring unit; 032, diet monitoring unit; 041, health check unit; 042, effect evaluation unit; 051, database unit; 052, data analysis unit. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] The present invention provides three technical solutions, including the following embodiments:

[0027] Example 1

[0028] See also Figure 1-Figure 3 The self-health intervention management system for sarcopenia patients includes a system overall architecture module 01, a personalized program generation module 02, a monitoring and feedback module 03, an evaluation and adjustment module 04, and a data storage and analysis module 05. The output end of the system overall architecture module 01 is electrically connected to the input end of the personalized program generation module 02, the output end of the personalized program generation module 02 is electrically connected to the input end of the monitoring and feedback module 03, the output end of the monitoring and feedback module 03 is electrically connected to the input end of the evaluation and adjustment module 04, and the output end of the evaluation and adjustment module 04 is electrically connected to the input end of the data storage and analysis module 05.

[0029] The overall system architecture module 01 includes a user interaction unit 011 and a data integration unit 012. The user interaction unit 011 is used to collect basic user information and health status, and to display personalized exercise and nutrition plans, monitoring feedback information, and evaluation results. A user-friendly interface is designed to facilitate users to enter basic personal information (such as age, gender, height, weight, medication history, etc.) and health status (such as whether they suffer from other chronic diseases, daily activity ability, etc.). This interface is also used to display personalized exercise and nutrition plans, monitoring feedback information, and evaluation results generated by the system for users, so that users can intuitively understand their own sarcopenia intervention process and status. The data integration unit 012 is used to integrate user information, monitoring data, and evaluation data to ensure data accuracy, completeness, and consistency, and integrate and process data collected from various sources, including information entered by users, data collected by the monitoring module, and data generated by the evaluation module. To ensure the accuracy, completeness and consistency of the data, and provide a reliable data basis for subsequent data analysis and decision-making, the personalized program generation module 02 includes a data acquisition unit 021 and an exercise plan generation unit 022. The data acquisition unit 021 is used to collect user age, gender, weight, muscle mass, muscle strength, physical function status, serum protein, hemoglobin level, personal exercise preferences and dietary preferences, and comprehensively collect various types of user data, such as age, gender, weight, muscle mass (which can be measured by bioelectrical impedance analysis and other technologies), serum protein, hemoglobin level, and personal exercise and dietary preferences. These data will be used as the basis for generating personalized programs. The exercise plan generation unit 022 formulates a personalized exercise plan based on the user's physical fitness assessment results and personal preferences, including determining the aerobic exercise method, intensity and frequency, as well as resistance training movements, intensity and frequency, and provides centralized training or video remote guidance based on the exercise environment. According to the user's physical fitness assessment results and personal preferences, combined with the principles of sports science, a personalized exercise plan is formulated. For aerobic exercise, if you determine the exercise method suitable for the user (walking, slow walking, Tai Chi, etc.), set the exercise intensity to 60%-75% of the maximum heart rate, and the exercise frequency is 3-5 times a week; for resistance training, determine the specific training movements (seated leg raise, seated stepping, standing back leg raise, standing side leg raise, standing stepping, etc.), set the intensity to 70%-85% of the maximum weight, 2-3 times a week. At the same time, considering the user's exercise environment (community, institution or home), arrange centralized training when conditions permit, and provide video remote guidance when conditions do not permit.

[0030] Example 2

[0031] Based on Example 1, see Figure 4-Figure 6As shown, the monitoring and feedback module 03 includes a motion monitoring unit 031 and a diet monitoring unit 032. The motion monitoring unit 031 uses a motion sensor to monitor the user's motion data in real time, including the type, intensity, time, frequency and posture of the motion, and judges whether the motion meets the standard according to the preset standard. If it does not meet the standard, it will issue a reminder and correction suggestion. With the help of a motion sensor (such as an accelerometer, a gyroscope, etc.), it can be worn on the key parts of the user's body (such as the wrist, ankle, etc.) to monitor the user's motion data in real time, including the type, intensity, time, frequency and posture of the motion. These data are transmitted to the system, and the system judges whether the user's motion meets the standard according to the preset motion standard. If it does not meet the standard, it will issue a reminder and correction suggestion in time. For example, if the user's aerobic exercise intensity does not reach the required maximum heart rate range, the system will prompt the user to speed up the exercise or increase the range of exercise appropriately. The diet monitoring unit 032 records the user's daily diet intake through the diet recording tool, and analyzes whether the nutrient intake is in line with the personalized nutrition plan based on the nutrition database. If not, it will give adjustment suggestions. The user is provided with a diet recording tool. The user can record the daily diet intake through mobile phone applications or other terminal devices, including food types, quantities and other information. The system analyzes the user's diet data based on the nutrition database to determine whether the intake of nutrients such as protein and calories is in line with the personalized nutrition plan. If the intake is insufficient or excessive, the system will give corresponding adjustment suggestions, such as recommending to increase the intake of certain protein-rich foods or reduce the intake of high-calorie foods. The evaluation and adjustment module 04 includes a health check unit 041 and an effect evaluation unit 042. The health check unit 041 regularly reminds the user to undergo a health check. The examination items include muscle strength test, muscle mass measurement and body function assessment, and enter the examination results. Regularly remind the user to undergo a health check. The examination items include muscle strength test (such as grip test, knee flexion and extension strength test, etc.), muscle mass measurement (can use dual-energy X-ray absorptiometry, bioelectrical impedance analysis, magnetic resonance imaging and other technologies) and body function assessment (such as walking speed test, stand-up-walk test, etc.). The examination results are entered into the system as an important basis for evaluating the improvement of the user's sarcopenia. The effect evaluation unit 042 uses an evaluation algorithm to comprehensively evaluate the intervention effect based on the exercise monitoring data, diet monitoring data and health examination results. According to the user's exercise monitoring data, diet monitoring data and health examination results, a specific evaluation algorithm is used to comprehensively evaluate the user's intervention effect. For example, the system analyzes whether the user's muscle mass has increased, muscle strength has improved, and physical function has improved. If the evaluation results show that the intervention effect is not good, the system will activate the adjustment mechanism.

[0032] The data storage and analysis module 05 includes a database unit 051 and a data analysis unit 052. The database unit 051 constructs a database to store the user's basic personal information, exercise data, diet data, health check data and intervention plan data, and has data backup and recovery functions to build a safe and reliable database for storing all the user's data, including basic personal information, exercise data, diet data, health check data and intervention plan data. The database has data backup and recovery functions to prevent data loss. At the same time, the data is classified and managed to facilitate data query and call. The data analysis unit 052 uses data analysis algorithms to mine and analyze the data in the database to provide a basis for personalized program optimization and intervention strategy adjustment. The data analysis algorithm is used to mine and analyze a large amount of data stored in the database. For example, the response differences of sarcopenia patients of different age groups, genders, and physical conditions to different exercise and nutrition intervention programs are analyzed, thereby providing data support for the optimization of personalized programs. By analyzing the long-term data change trend of users, the development risk of sarcopenia in users is predicted, and the intervention strategy is adjusted in advance to achieve precise health management.

[0033] Example 3

[0034] Based on Example 2, see Figure 3-Figure 5 As shown, in the exercise plan generating unit 022, the intensity of aerobic exercise is set to reach 60%-75% of the maximum heart rate, 3-5 times per week; the intensity of resistance training is set to 70%-85% of the maximum weight, 2-3 times per week.

[0035] The motion sensors in the motion monitoring unit 031 are MEMS accelerometers and gyroscopes, which are worn on the wrist, ankle, etc., and connected to the user's smart terminal via Bluetooth or other wireless communication technologies.

[0036] The diet recording tool in the diet monitoring unit 032 is a mobile phone application with a food database and intelligent recognition functions. Diet information can be entered by searching for food names or scanning food barcodes.

[0037] Health check unit 041 develops a personalized regular health check plan based on the user's age, gender, and severity of sarcopenia. The examination items include grip strength test, walking speed test, muscle mass assessment, balance ability test, stair climbing ability test, 5 sit-up tests, and muscle mass measurement using dual-energy X-ray absorptiometry and other technologies.

[0038] Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0039] The above embodiments of the invention are described in detail, but the contents are only preferred embodiments of the invention and cannot be considered to limit the scope of the invention. All equivalent changes and improvements made within the scope of the invention should still fall within the scope of the invention.

Claims

1. The self-health intervention management system for sarcopenia patients is characterized by: The system comprises a system overall architecture module (01), a personalized solution generation module (02), a monitoring and feedback module (03), an evaluation and adjustment module (04), and a data storage and analysis module (05), wherein the output end of the system overall architecture module (01) is electrically connected to the input end of the personalized solution generation module (02), the output end of the personalized solution generation module (02) is electrically connected to the input end of the monitoring and feedback module (03), the output end of the monitoring and feedback module (03) is electrically connected to the input end of the evaluation and adjustment module (04), and the output end of the evaluation and adjustment module (04) is electrically connected to the input end of the data storage and analysis module (05).

2. The self-health intervention management system for sarcopenia patients according to claim 1, characterized in that: The system overall architecture module (01) includes a user interaction unit (011) and a data integration unit (012). The user interaction unit (011) is used to collect basic information and health status of the user, and display personalized exercise and nutrition plans, monitoring feedback information and evaluation results. The data integration unit (012) is used to integrate user information, monitoring data and evaluation data to ensure data accuracy, completeness and consistency. The personalized program generation module (02) includes a data acquisition unit (021) and an exercise plan generation unit (022). The data acquisition unit (021) is used to collect user age, gender, weight, muscle mass, muscle strength, physical function status, serum protein, hemoglobin level, personal exercise preference and dietary preference information. The exercise plan generation unit (022) formulates a personalized exercise plan based on the user's physical fitness assessment results and personal preferences, including determining aerobic exercise methods, intensity and frequency, as well as resistance training movements, intensity and frequency, and provides centralized training or video remote guidance based on the exercise environment.

3. The self-health intervention management system for sarcopenia patients according to claim 1, characterized in that: The monitoring and feedback module (03) includes a motion monitoring unit (031) and a diet monitoring unit (032). The motion monitoring unit (031) uses a motion sensor to monitor the user's motion data in real time, including the type, intensity, time, frequency and posture of the motion, and determines whether the motion meets the standard according to the preset standard. If it does not meet the standard, it will issue a reminder and correction suggestion. The diet monitoring unit (032) records the user's daily diet intake through a diet record tool, and analyzes whether the nutrient intake meets the personalized nutrition plan according to the nutrition database. If it does not meet the standard, it will give adjustment suggestions. The evaluation and adjustment module (04) includes a health check unit (041) and an effect evaluation unit (042). The health check unit (041) regularly reminds the user to undergo a health check. The examination items include muscle strength test, muscle mass measurement and body function assessment, and enters the examination results. The effect evaluation unit (042) uses an evaluation algorithm to comprehensively evaluate the intervention effect based on the motion monitoring data, diet monitoring data and health examination results.

4. The self-health intervention management system for sarcopenia patients according to claim 1, characterized in that: The data storage and analysis module (05) comprises a database unit (051) and a data analysis unit (052). The database unit (051) constructs a database to store the user's personal basic information, exercise data, diet data, health check data and intervention plan data, and has data backup and recovery functions. The data analysis unit (052) uses a data analysis algorithm to mine and analyze the data in the database to provide a basis for personalized program optimization and intervention strategy adjustment.

5. The self-health intervention management system for sarcopenia patients according to claim 2, characterized in that: In the exercise plan generating unit (022), the intensity of aerobic exercise is set to reach 60%-75% of the maximum heart rate, 3-5 times a week; the intensity of resistance training is set to 70%-85% of the maximum weight, 2-3 times a week.

6. The self-health intervention management system for sarcopenia patients according to claim 3, characterized in that: The motion sensor in the motion monitoring unit (031) is a MEMS accelerometer and a gyroscope, which is worn on the wrist, ankle, etc. and connected to the user's smart terminal via Bluetooth or other wireless communication technologies.

7. The self-health intervention management system for sarcopenia patients according to claim 3, characterized in that: The diet recording tool in the diet monitoring unit (032) is a mobile phone application, which has a food database and intelligent recognition function, and can enter diet information by searching food names or scanning food bar codes.

8. The self-health intervention management system for sarcopenia patients according to claim 3, characterized in that: The health check unit (041) formulates a personalized regular health check plan based on the user's age, gender, and severity of sarcopenia. The examination items include grip strength test, walking speed test, muscle mass assessment, balance ability test, stair climbing ability test, 5 sit-up tests, and muscle mass measurement using dual-energy X-ray absorptiometry and other technologies.

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