A scientific fat-reducing measurement and training integrated system

Abstract

The application provides a scientific fat-reducing measurement and training integrated system, which comprises an integrated device and a measurement and training system; the integrated device comprises a motion load loading module, a respiratory gas measurement module, a physiological signal acquisition module, a control communication module and an analysis host module; the measurement and training system is embedded in the analysis host module and comprises a basic information input module, a static information acquisition module, an extreme state information acquisition module, an optimal fat-reducing test module, an optimal fat-reducing training module and a fat-reducing evaluation report module. The application can calculate the energy supply mode of nutrients in real time, dynamically adjust the motion load to achieve the optimal fat energy supply mode, realize the scientific, accurate and efficient fat-reducing state, and calculate and quantify the fat-reducing effect in real time.

Description

Technical Field

[0001] The present invention belongs to the field of fat reduction, and in particular relates to a test-training integrated system for scientific fat reduction. Background Art

[0002] Fat loss is about reducing body fat content. It's primarily targeted at people with obesity, those working out, and those exercising. Excessive fat content can easily lead to obesity, cardiovascular and cerebrovascular diseases, and other health risks. The human body primarily oxidizes carbohydrates, fats, and proteins for energy. This oxidation process consumes oxygen and produces carbon dioxide. The amount of oxygen consumed and carbon dioxide exhaled in a given period of time can be used to calculate the respiratory quotient (RQ). This RQ, which is synonymous with the resting rate of energy expenditure (RER), reflects the consumption of these three nutrients. Typically, RQ is 0.7 when fueled entirely by fat and 1.0 when fueled entirely by carbohydrates. Assuming complete oxidation, based on chemical formulas, RQ is approximately 0.7 when fueled solely by fat, 0.8 when fueled solely by protein, and approximately 1 when fueled solely by carbohydrates (as shown below). When fueled by a combination of the three nutrients, RQ ranges between 0.7 and 1. Therefore, an RQ of 0.7 is optimal for fat loss. There are differences in energy supply among the three major nutrients. The glycogen in the human body can provide energy quickly, and fat can provide energy efficiently (generating more heat per unit weight). Therefore, the human body usually consumes glycogen first, then fat, and finally protein (protein energy is usually produced under extreme circumstances). Therefore, by adjusting the exercise load, the glycogen in the body can be quickly consumed and the body's fat can be effectively mobilized for energy.

[0003] C6H 12 O6(sugar) + 6O2(oxygen)→6CO2(carbon dioxide)+6H2O(water).

[0004] The current methods of fat loss are as follows: 1. Exercise to increase energy consumption to achieve the purpose of fat loss; 2. Control diet to reduce energy intake to reduce fat synthesis or increase fat consumption; 3. Take medications to inhibit fat absorption or promote fat consumption; 4. Use fat burning products to promote local body fat consumption through physical vibration or heat generation.

[0005] For example, Chinese patent CN2683023Y (Diet, Fitness, and Fat Loss Meter) takes as input the type and total amount of food intake and exercise program, and outputs an exercise plan, aiming to achieve fat loss by creating a negative energy balance. However, this device suffers from the following issues: 1. Energy intake is calculated based on food intake, which is not scientifically accurate and does not take into account food additives and methods of consumption, such as frying, as well as individual differences in digestion and absorption capacity; 2. Energy expenditure is estimated based on exercise program and heart rate, which is not accurate enough. The same exercise program and intensity are affected by individual physical differences, resulting in different energy expenditures; 3. Achieving a negative energy balance does not necessarily mean a state of fat energy supply; it may also lead to significant depletion of muscle glycogen, resulting in muscle loss.

[0006] Chinese patent application CN110634543A (A Fat Loss Management Platform and Implementation Method) primarily monitors body fat scale indicators and employs a strategy of controlling diet and exercise to achieve a negative energy balance. However, this approach suffers from the following issues: 1. The basal metabolic rate measured by body fat scales inherently suffers from significant errors; 2. The monitoring and adjustment process is slow, resulting in a long fat loss cycle and requiring high compliance.

[0007] Chinese patent application CN114496245A (A personalized body fat control and management method and system based on exercise energy consumption monitoring) uses individual resting data and maximum oxygen uptake (VO2) as input to formulate an exercise plan. This approach presents the following issues: 1. It only measures resting energy expenditure, not real-time measurements of energy expenditure and respiratory quotient (RQ) during exercise, making it impossible to effectively observe fat energy supply and control fat loss. 2. The strategy employed is to formulate an exercise plan based on static indicators, without quantifying the energy and fat consumed during exercise. 3. Using VO2 as a reference standard for exercise intensity has a certain lag from a physiological perspective, and VO2 is set at a heart rate of 180 beats / min, which cannot account for individual differences.

[0008] Chinese patent CN116649951B (Exercise data processing method, wearable device, terminal, fitness equipment and medium) proposes a specific exercise data processing method, with the goal of maximizing fat loss, using a device to calculate exercise energy consumption and fat consumption. However, there are the following problems: 1. Its RER measurement uses a prediction model, which varies between different sports and individuals; 2. The quantification of fat consumption is based on total consumption, and a specific formula for quantifying exercise energy consumption is not given; 3. No effective control method for achieving the maximum fat burning state is given, and it only displays the fat consumption and energy consumption during exercise in real time.

[0009] Furthermore, the human body primarily relies on a combination of three major nutrients: carbohydrates, fat, and protein. This energy supply varies with physiological states. For example, glycogen is consumed preferentially when a person is full, while fat is consumed when the person is hungry. Blind exercise can deplete the body's glycogen and fail to effectively reduce fat. Dietary restrictions can easily lead to nutrient imbalances, hypoglycemia, and prolonged hunger, which can damage organs. The side effects of fat-reducing medications are unclear, and their effectiveness varies from person to person. So-called fat-burning products rely on external stimuli to cause passive fat consumption, and they are unable to mobilize systemic fat-reduction processes, resulting in little benefit. In summary, there are currently no effective fat-reduction devices or systems to scientifically and efficiently guide fat-reduction activities. Summary of the Invention

[0010] In order to solve the above technical problems, the present invention proposes an integrated testing and training system for scientific fat loss. By accurately measuring the respiratory quotient (RQ) of the human body in static and dynamic conditions in real time, the nutrient energy supply method is calculated in real time, and the exercise load is dynamically adjusted to achieve the optimal fat energy supply method to achieve a scientific, accurate and efficient fat loss state, and the fat loss effect is quantified in real time.

[0011] In order to achieve the above object, the present invention adopts the following technical solutions:

[0012] A scientific fat-reducing test-training integrated system, comprising an integrated device and a test-training system;

[0013] The integrated device includes an exercise load loading module, a respiratory gas measurement module, a physiological signal acquisition module, a control and communication module, and an analysis host module; the exercise load loading module is used to apply a quantitative exercise load to the individual, causing the individual to exercise in a predetermined manner, thereby achieving energy consumption; the respiratory gas measurement module is used to collect inhaled and exhaled gases and perform oxygen and carbon dioxide content analysis and calculation; the physiological signal acquisition module is used to collect blood oxygen, electrocardiogram, heart rate information, and body fat rate information during individual exercise; the control and communication module is used to realize communication between the respiratory gas measurement module, the exercise load module, the physiological signal acquisition module, and the analysis host module, and is also used to control the operation of the gas measurement module, the exercise load module, and the physiological signal acquisition module; the analysis host module is used for data aggregation, calculation, analysis, and human-computer interaction;

[0014] The testing and training system is embedded in the analysis host module, and includes a basic information entry module, a static information collection module, an extreme information collection module, an optimal fat loss test module, an optimal fat loss training module, and a fat loss evaluation report module; the basic information entry module is used to enter the subject information in the analysis host module; the static information collection module is used to measure the resting heart rate RHR and the resting energy consumption rate RER; the extreme information collection module is used to measure the maximum oxygen uptake VO2Max, the maximum heart rate measurement HRMax, the maximum load power MaxPower and the inertia time ResponseTime; the optimal fat loss test module is used to automatically adjust the exercise load and observe the energy supply ratio of the three major nutrients in real time, estimate the fat loss amount LostFatMess per breath and the energy consumption per breath LostEnergy, and perform adaptive exercise load grading; the optimal fat loss training module performs fat loss exercise according to the optimal fat loss parameters calculated by the optimal fat loss test module and sets the parameters.

[0015] Furthermore, the analysis host module sends a test instruction to the control communication module, and then the control communication module sends a synchronous acquisition instruction to the physiological signal acquisition module and the respiratory gas measurement module. The subject remains motionless, and the data of each module is transmitted back to the analysis host module at a fixed frequency through the control communication module. After processing by the static information acquisition module, the resting heart rate RHR and resting energy expenditure rate RER are obtained.

[0016] Furthermore, the analysis host module sends a test instruction to the control communication module, which then sends a synchronous acquisition instruction to the physiological signal acquisition module and the respiratory gas measurement module, and sends an instruction to execute a step-by-step intensity progressive exercise load to the exercise load loading module. The subject starts to do follow-up exercise, and the data of each module is transmitted back to the analysis host module at a fixed frequency through the control communication module. After real-time processing by the extreme information acquisition module, the heart rate and oxygen intake rate are calculated every 30 seconds. When the heart rate and oxygen intake rate no longer continue to increase, the measurement is stopped, and the maximum oxygen uptake VO2Max, maximum heart rate measurement HRMax, maximum load power MaxPower and inertia time ResponseTime are calculated.

[0017] Furthermore, the formula for the progressive intensity of the exercise load module is as follows:

[0018] ;

[0019] Where Power is the target power of the motion load loading module M1, T is the time, and PV is the power growth rate per unit time. PV is calculated based on the maximum power MaxP that the motion load device can execute and the entire step-by-step operation duration MaxT: PV = MaxP / MaxT. n is the adjustment factor, which is greater than or equal to 1.

[0020] Furthermore, the inertia time ResponseTime represents the time between the maximum oxygen uptake and the maximum heart rate, and its calculation formula is:

[0021] ;

[0022] Among them, VO2MaxT is the moment when the maximum oxygen uptake is reached, and HRMaxT is the moment when the maximum heart rate is reached.

[0023] Furthermore, the adaptive grading of exercise load in the optimal fat loss test module adopts the following graded power formula:

[0024] ;

[0025] Among them, LP is the exercise load power corresponding to the Nth level, and N is the current level;

[0026] The estimation formula of real-time energy consumption LostEnergy is:

[0027] ;

[0028] Where EE is the energy consumption rate during exercise, in kilocalories per day, and T1 is the total duration of each breath, in seconds.

[0029] Furthermore, the estimation formula for the real-time fat loss amount LostFatMess is:

[0030] ;

[0031] Among them, Kf is the fat caloric value, FatRate is the energy supply ratio of fat, which is calculated from RQ;

[0032] After removing the effect of protein, we get:

[0033] ;

[0034] ;

[0035] Among them, Fat is the energy supply ratio of fat, Cho is the energy supply ratio of carbohydrates, Kf and Kc are the calorific value of fat and carbohydrates respectively, Gf and Gc are the amount of fat and carbohydrates respectively, and Qf and Qc are the respiratory quotients produced by the complete oxidation reaction of fat and carbohydrates respectively.

[0036] Furthermore, the analysis host module M5 adjusts the exercise load in real time according to RQ, including the following five steps:

[0037] At the beginning, in the first stage, if the heart rate reaches the maximum heart rate, reduce the exercise intensity by 1 level and maintain it for 2 ResponseTime duration, on the contrary, if RQ is less than or equal to 0.7, enter the fifth stage; if RQ is greater than 0.7 and less than 1, increase the exercise intensity by 1 level and maintain it for 2 ResponseTime duration: If RQ is greater than or equal to 1, reduce the exercise intensity by 1 level and enter the second stage;

[0038] In the second stage, if RQ is greater than or equal to 1, reduce the exercise intensity by 1 level and maintain 2 ResponseTime duration; if RQ is less than 1, enter the third stage;

[0039] In the third stage, if RQ increases, reduce the exercise intensity by 1 level and maintain ResponseTime 2 hours, until RQ starts to decrease; if RQ drops to 0.7, enter the fourth stage;

[0040] In the fourth stage, if RQ is less than 0.7, reduce the exercise load by 1 level and maintain 2 ResponseTime duration, until RQ increases to 0.7, if RQ is stable at 0.7, it reaches 5 The ResponseTime duration records the exercise load at this time, which is the optimal oxygen uptake SVO2 and exercise intensity SL for fat loss, and enters the fifth stage;

[0041] In the fifth stage, this regulation ends.

[0042] Furthermore, in the optimal fat loss training module, power regulation is performed according to a power function.

[0043] Furthermore, the calculation formulas for the total energy consumption LostEnergyT and the total fat consumption LostFatMessT are:

[0044] ;

[0045] ;

[0046] Among them, n1 is the number of breaths in the whole process.

[0047] Beneficial effects:

[0048] 1. The present invention accurately measures the static and dynamic respiratory gases of the human body and calculates the respiratory quotient RQ (the ratio of carbon dioxide production to oxygen consumption in the same time period) in real time, thereby measuring the nutrient energy supply mode. By adjusting the exercise load to target the state of fat energy supply, a scientific, accurate and efficient fat reduction effect is achieved. This solves the problems of difficulty in quantifying the fat reduction effect and controlling the fat reduction process, avoids the harm to the human body caused by blind fat reduction, and makes fat reduction safer and more efficient.

[0049] 2. The present invention quantifies energy consumption by directly measuring respiratory gas conditions using the recognized "gold standard" indirect calorimetry method, and calculates the respiratory quotient RQ in real time to reflect the substrate energy supply, which is more scientific and accurate in quantifying energy consumption and fat loss effects.

[0050] 3. The present invention uses real-time heart rate to effectively control exercise intensity, achieving fat loss in a more scientific and accurate manner.

[0051] 4. The present invention proposes an exercise load control method based on individual conditions, which realizes the change of substrate consumption through exercise load, realizes energy and fat consumption observation, and forms a closed loop of fat reduction behavior through exercise load control, thereby achieving efficient, scientific and accurate fat reduction effects. The present invention does not rely on energy intake for fat reduction.

[0052] 5. The present invention quantitatively calculates the energy consumption and fat-reducing effect during exercise in real time, and proposes a quantitative formula that conforms to physiological laws; the present invention uses the maximum heart rate as the exercise intensity evaluation standard to achieve more precise control.

[0053] 6. The present invention provides an integrated device that integrates precise respiratory gas measurement, forms a closed loop of fat loss behavior based on energy and fat consumption observation and exercise load control, and realizes the measurement of an individual's maximum fat loss state and training in the optimal fat loss state.

[0054] In summary, the present invention proposes a scientific, integrated fat-loss device that uses a "gold standard" approach to quantify energy consumption and the energy supply of the three major nutrients. It also proposes a personalized, automatic adjustment and control method for exercise load based on maximum heart rate, with the respiratory quotient as the target indicator and exercise intensity (comparing exercise heart rate with maximum heart rate) as the adjustment indicator. This method achieves changes in substrate consumption through exercise load, focusing on the fundamental issue of fat loss. Compared to existing fat-loss testing and training devices, this invention disregards subjective energy intake, focusing only on precisely measurable respiration and heart rate at rest and during exercise. It also introduces inertia time to compensate for the relative delay between heart rate and oxygen uptake changes in the respiratory and circulatory systems. Based on energy and fat consumption observations and exercise load control, it forms a closed loop for fat-loss behavior. Finally, by constructing a scientifically comprehensive "static-extreme-exercise" testing and training process, it enables measurement of an individual's maximum fat-loss state and training within that optimal state. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 This is a schematic diagram of an integrated device of a scientific fat loss test and training integrated system of the present invention;

[0056] Figure 2 Schematic diagram of the adjustment strategy for analyzing the host module;

[0057] Figure 3 This is a schematic diagram of the testing and training system of the present invention, which is an integrated testing and training system for scientific fat loss.

[0058] Among them, the accompanying drawings are marked as: exercise load loading module M1, respiratory gas measurement module M2, physiological signal acquisition module M3, control communication module M4, analysis host module M5, basic information entry module S1, static information acquisition module S2, extreme information acquisition module S3, optimal fat reduction test module S4, optimal fat reduction training module S5, and fat reduction evaluation report module S6. DETAILED DESCRIPTION

[0059] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only intended to illustrate the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.

[0060] The present invention provides a scientific fat-reducing test-training integrated system comprising an integrated device and a test-training system.

[0061] like Figure 1 As shown, the integrated device includes a motion load loading module M1, a respiratory gas measurement module M2, a physiological signal acquisition module M3, a control communication module M4 and an analysis host module M5.

[0062] The exercise load loading module M1 is used to apply a quantitative exercise load to the individual, so that the individual exercises in a predetermined manner to achieve energy consumption, including but not limited to treadmills, rowing machines and other equipment that can be used for exercise;

[0063] The respiratory gas measurement module M2 is used to collect inhaled gas and exhaled gas and perform oxygen and carbon dioxide content analysis and calculation;

[0064] The physiological signal acquisition module M3 is used to collect blood oxygen, electrocardiogram, heart rate information and body fat rate information during individual exercise;

[0065] The control communication module M4 is used to realize the communication between the respiratory gas measurement module, the exercise load module, the physiological signal acquisition module and the analysis host module, and is also used to control the operation of the gas measurement module, the exercise load module and the physiological signal acquisition module;

[0066] The analysis host module M5 is a physical device connected to the control communication module M4, providing display, calculation, and input and output basic capabilities for data aggregation, calculation, analysis and human-computer interaction.

[0067] The control method of the analysis host module M5 includes:

[0068] Analysis host module M5 adjusts the motion load in real time according to RQ, and the adjustment strategy is as follows Figure 2 As shown, it includes the following steps:

[0069] 1) At the beginning, in the first stage (S==1), if the heart rate reaches the maximum heart rate, reduce it by 1 level ( Figure 2 L--) Exercise intensity and maintain 2 ResponseTime duration (similarly, according to Shannon sampling theorem, the sampling frequency is set to 2 times). On the contrary, if RQ is less than or equal to 0.7, enter the fifth stage; if RQ is greater than 0.7 and less than 1, increase 1 level ( Figure 2 L++) exercise intensity and maintain 2 ResponseTime duration: If RQ is greater than or equal to 1, reduce the exercise intensity by 1 level and enter the second stage;

[0070] 2) In the second stage (S==2), if RQ is greater than or equal to 1, reduce the exercise intensity by 1 level and maintain 2 ResponseTime duration; if RQ is less than 1, enter the third stage;

[0071] 3) In the third stage (S==3), if RQ increases, reduce the exercise intensity by 1 level and maintain ResponseTime 2 hours, until RQ starts to decrease; if RQ drops to 0.7, enter the fourth stage;

[0072] 4) In the fourth stage (S==4), if RQ is less than 0.7, reduce the exercise load by 1 level and maintain 2 ResponseTime duration, until RQ increases to 0.7, if RQ is stable at 0.7, it reaches 5 The ResponseTime duration records the exercise load at this time as the optimal oxygen uptake SVO2 for fat loss and exercise intensity SL (the ratio of current heart rate to maximum heart rate), and enters the fifth stage;

[0073] 5) In the fifth stage (S==5), this regulation ends.

[0074] according to Figure 2 As shown, the present invention proposes an efficient fat loss control algorithm based on RQ and adaptive exercise load, which conforms to the law of energy supply and consumption of the human body. It is divided into five links, adjusting the exercise load from small to large and then from large to small, reducing anaerobic exercise interference, first consuming a large amount of human glycogen, and then gradually mobilizing fat for energy supply.

[0075] like Figure 3 As shown, the testing and training system includes a basic information entry module S1, a static information collection module S2, an extreme information collection module S3, an optimal fat loss test module S4, an optimal fat loss training module S5, and a fat loss evaluation report module S6. The testing and training system is embedded in the analysis host module M5 as software.

[0076] The basic information entry module S1 can be used to enter and store subject information, including number, name, gender, age, height and weight, in the analysis host module M5 for estimating metabolic equivalents, exercise intensity and body fat percentage.

[0077] The static information acquisition module S2 can measure the resting heart rate (RHR) and the resting energy expenditure rate (RER). The processing flow is as follows: the operator operates the analysis host module M5 to send a test instruction to the control communication module M4, and then the control communication module M4 sends a synchronous acquisition instruction to the physiological signal acquisition module M3 and the respiratory gas measurement module M2. The subject is still, and the data of each module is transmitted back to the analysis host module M5 at a fixed frequency via the control communication module M4. After being processed by the static information acquisition module S2, the resting heart rate (RHR) and the resting energy expenditure rate (RER) are obtained. The calculation formula is as follows:

[0078] ;

[0079] RHN is the number of heartbeats in time T, where T is the duration in minutes.

[0080] ;

[0081] ;

[0082] ;

[0083] Among them, O2R is the oxygen consumption rate, unit is ml / min, V02 is the total amount of oxygen consumed in time T, unit is ml, T is the time, unit is minute; similarly, CO2R is the carbon dioxide production rate.

[0084] The extreme state information acquisition module S3 can realize the measurement of maximum oxygen uptake VO2Max, maximum heart rate measurement HRMax, maximum load power MaxPower and inertia time ResponseTime. The steps are as follows: the operator operates the analysis host module M5 to send a test instruction to the control communication module M4, and then the control communication module M4 sends a synchronous acquisition instruction to the physiological signal acquisition module M3 and the respiratory gas measurement module M2, and sends an execution step-by-step intensity progressive exercise load instruction to the exercise load loading module M1. The subject starts to do the follow-up exercise, and the data of each module is sent back to the control communication module M4 at a fixed frequency. The data is transmitted to the analysis host module M5 and processed in real time by the extreme state information acquisition module S3. The heart rate and oxygen intake rate are calculated every 30 seconds (the respiratory rate is usually above 5 times / minute, about once every 12 seconds or more. According to the Shannon sampling theorem, the sampling frequency should be greater than 2 times the highest frequency of the target signal, so it is set to 30 seconds). When the heart rate and oxygen intake rate no longer increase continuously (the CV coefficient of the values ​​within the window period is within 10%), the maximum oxygen uptake VO2Max, the maximum heart rate measurement HRMax, the maximum load power MaxPower, and the inertia time ResponseTime are calculated. Among them, the present invention innovatively constructs a formula for increasing power load in a step-by-step manner and using a power function formula. This can achieve a rapid power increase in the initial stage and a slow power increase in the later stage to more accurately calculate the maximum oxygen uptake VO2Max, the maximum heart rate measurement MHR, and the maximum load power MaxPower. The formula is as follows:

[0085] ;

[0086] Where Power is the target power of the exercise load module M1, T is the time, and PV is the power growth rate per unit time. PV is calculated from the maximum power MaxP that the exercise load device can perform and the total step-by-step operation duration MaxT. PV = MaxP / MaxT. n is an adjustment factor (n greater than or equal to 1) that controls the power ramp curve. A larger value results in a flatter curve. n can be adjusted based on the individual's resting heart rate; the lower the resting heart rate, the smaller n.

[0087] Maximum oxygen uptake (VO2Max) is defined as the amount of oxygen intake that does not increase with power during a certain period of time under a progressive intensity exercise load test. Maximum heart rate measurement (HRMax) is defined as the heart rate that does not increase with power during a certain period of time under a progressive intensity exercise load test. The inertia time (ResponseTime) represents the time that the maximum oxygen uptake lags behind the maximum heart rate. The physiological basis for this is that the human body is a large system. The heart increases its blood supply capacity, thereby increasing its oxygen consumption demand and promoting oxygen intake. Therefore, when oxygen consumption increases, the heart rate changes faster than the change in exhaled gas composition. Therefore, when performing RQ observation, sufficient time (greater than or equal to ResponseTime) must be ensured to effectively evaluate the energy supply situation. Therefore, the present invention innovatively constructs the following calculation formula:

[0088] ;

[0089] Among them, VO2MaxT is the moment when the maximum oxygen uptake is reached, and HRMaxT is the moment when the maximum heart rate is reached.

[0090] The optimal fat loss test module S4 can automatically adjust the exercise load and observe the energy supply ratio of the three major nutrients in real time, estimate the fat loss per breath LostFatMess and energy consumption per breath LostEnergy, including adaptive exercise load classification. The present invention innovatively constructs the following graded power formula:

[0091] ;

[0092] Among them, LP is the exercise load power corresponding to the Nth level, and N is the current level.

[0093] The present invention innovatively constructs the following real-time energy consumption LostEnergy estimation formula:

[0094] ;

[0095] Among them, EE is the energy consumption rate during exercise, in kilocalories / day (refer to the RER calculation formula), and T1 is the total duration of each breath, in seconds.

[0096] The present invention innovatively constructs the following real-time fat loss estimation formula:

[0097] ;

[0098] Among them, Kf is the calorific value of fat, which is usually 9.4kcal / g clinically, and FatRate is the proportion of fat energy supply, which is calculated from RQ. From the perspective of actual measurement, protein measurement requires 24-hour urine collection, and 24-hour urine nitrogen measurement requires hospitalization measurement in the hospital, which is not convenient for non-patients; at the same time, when the body has no lesions, protein hardly participates in energy supply, and is mainly used for enzyme synthesis and other functions; even if protein participates in energy supply, the impact of its energy supply is only within 1% of the total energy, which can be ignored, so the impact of protein is eliminated. Therefore, the present invention innovatively constructs the following formula to eliminate the impact of protein:

[0099] ;

[0100] ;

[0101] Among them, Fat is the energy supply ratio of fat, Cho is the energy supply ratio of carbohydrates, Kf and Kc are the calorific value of fat and carbohydrates respectively, Gf and Gc are the amount of fat and carbohydrates respectively, and Qf and Qc are the respiratory quotients produced by the complete oxidation reaction of fat and carbohydrates respectively.

[0102] The optimal fat loss training module S5 can perform fat loss exercise according to the optimal fat loss parameters calculated by the optimal fat loss test module S4 and set the parameters, and the specific power adjustment is performed according to the power function.

[0103] The fat loss assessment report module S6 can calculate the total energy consumption LostEnergyT and the total fat consumption LostFatMessT based on the operation process of the optimal fat loss test module S4 and the optimal fat loss training module S5, and draw the exercise power process curve, respiratory quotient process curve, heart rate process curve, energy consumption process curve and oxygen uptake process curve. The present invention innovatively constructs the following calculation formula:

[0104] ;

[0105] ;

[0106] Among them, n1 is the number of breaths in the whole process.

Claims

1. A scientific fat loss test and training integrated system, characterized by: Includes integrated device and testing and training system; The integrated device includes an exercise load loading module, a respiratory gas measurement module, a physiological signal acquisition module, a control and communication module, and an analysis host module; the exercise load loading module is used to apply a quantitative exercise load to the individual, causing the individual to exercise in a predetermined manner, thereby achieving energy consumption; the respiratory gas measurement module is used to collect inhaled and exhaled gases and perform oxygen and carbon dioxide content analysis and calculation; the physiological signal acquisition module is used to collect blood oxygen, electrocardiogram, heart rate information, and body fat rate information during individual exercise; the control and communication module is used to realize communication between the respiratory gas measurement module, the exercise load module, the physiological signal acquisition module, and the analysis host module, and is also used to control the operation of the respiratory gas measurement module, the exercise load loading module, and the physiological signal acquisition module; the analysis host module is used for data aggregation, calculation, analysis, and human-computer interaction; The testing and training system is embedded in the analysis host module and includes a basic information entry module, a static information collection module, an extreme information collection module, an optimal fat loss test module, an optimal fat loss training module, and a fat loss evaluation report module; the basic information entry module is used to enter the subject information in the analysis host module; The static information acquisition module is used to measure the resting heart rate RHR and the resting energy consumption rate RER; the extreme information acquisition module is used to measure the maximum oxygen uptake VO2Max, the maximum heart rate measurement HRMax, the maximum load power MaxPower and the inertia time ResponseTime; the optimal fat loss test module is used to automatically adjust the exercise load and observe the energy supply ratio of the three major nutrients in real time, estimate the fat loss amount per breath LostFatMess and the energy consumption per breath LostEnergy, and perform adaptive exercise load classification; the optimal fat loss training module performs fat loss exercise according to the optimal fat loss parameters calculated by the optimal fat loss test module and sets the parameters.

2. A scientific fat loss test and training integrated system according to claim 1, characterized in that: The analysis host module sends a test instruction to the control communication module, which then sends a synchronous acquisition instruction to the physiological signal acquisition module and the respiratory gas measurement module. The subject remains motionless, and the data from each module is transmitted back to the analysis host module at a fixed frequency via the control communication module. After processing by the static information acquisition module, the resting heart rate RHR and resting energy expenditure rate RER are obtained.

3. The integrated testing and training system for scientific fat loss according to claim 1, characterized in that: The analysis host module sends a test instruction to the control and communication module, which then sends a synchronous acquisition instruction to the physiological signal acquisition module and the respiratory gas measurement module, and sends an instruction to execute a step-by-step intensity progressive exercise load to the exercise load loading module. The subject starts to do follow-up exercise, and the data of each module is transmitted back to the analysis host module at a fixed frequency through the control and communication module. After real-time processing by the extreme information acquisition module, the heart rate and oxygen intake rate are calculated every 30 seconds. When the heart rate and oxygen intake rate no longer continue to increase, the measurement is stopped, and the maximum oxygen uptake VO2Max, maximum heart rate measurement HRMax, maximum load power MaxPower and inertia time ResponseTime are calculated.

4. A scientific fat loss test and training integrated system according to claim 3, characterized in that: The formula for the progressive intensity of the exercise load module is as follows: ； Where Power is the target power of the motion load loading module M1, T is the time, and PV is the power growth rate per unit time. PV is calculated based on the maximum power MaxP that the motion load device can execute and the entire step-by-step operation duration MaxT: PV = MaxP / MaxT. n is the adjustment factor, which is greater than or equal to 1.

5. The integrated testing and training system for scientific fat loss according to claim 4, characterized in that: Inertia time ResponseTime represents the time that the maximum oxygen uptake lags behind the maximum heart rate. Its calculation formula is: ； Among them, VO2MaxT is the moment when the maximum oxygen uptake is reached, and HRMaxT is the moment when the maximum heart rate is reached.

6. The integrated testing and training system for scientific fat loss according to claim 1, characterized in that: The adaptive grading of exercise load in the optimal fat loss test module adopts the following graded power formula: ； Among them, LP is the exercise load power corresponding to the Nth level, and N is the current level; The estimation formula of real-time energy consumption LostEnergy is: ； Where EE is the energy consumption rate during exercise, in kilocalories per day, and T1 is the total duration of each breath, in seconds.

7. The integrated testing and training system for scientific fat loss according to claim 6, characterized in that: The estimation formula for real-time fat loss LostFatMess is: ； Among them, Kf is the fat caloric value, FatRate is the energy supply ratio of fat, which is calculated from RQ; RQ is the respiratory quotient; After removing the effect of protein, we get: ； ； Among them, Fat is the energy supply ratio of fat, Cho is the energy supply ratio of carbohydrates, Kf and Kc are the calorific value of fat and carbohydrates respectively, Gf and Gc are the amount of fat and carbohydrates respectively, and Qf and Qc are the respiratory quotients produced by the complete oxidation reaction of fat and carbohydrates respectively.

8. The integrated testing and training system for scientific fat loss according to claim 5, characterized in that: The analysis host module M5 adjusts the exercise load in real time according to RQ, including the following five steps: At the beginning, in the first stage, if the heart rate reaches the maximum heart rate, reduce the exercise intensity by 1 level and maintain it for 2 ResponseTime duration, on the contrary, if RQ is less than or equal to 0.7, enter the fifth stage; if RQ is greater than 0.7 and less than 1, increase the exercise intensity by 1 level and maintain it for 2 ResponseTime duration: If RQ is greater than or equal to 1, reduce the exercise intensity by 1 level and enter the second stage; In the second stage, if RQ is greater than or equal to 1, reduce the exercise intensity by 1 level and maintain 2 ResponseTime duration; If RQ is less than 1, enter the third stage; In the third stage, if RQ increases, reduce the exercise intensity by 1 level and maintain ResponseTime 2 hours, until RQ starts to decrease; if RQ drops to 0.7, enter the fourth stage; In the fourth stage, if RQ is less than 0.7, reduce the exercise load by 1 level and maintain 2 ResponseTime duration, until RQ increases to 0.7, if RQ is stable at 0.7, it reaches 5 The ResponseTime duration records the exercise load at this time, which is the optimal oxygen uptake SVO2 and exercise intensity SL for fat loss, and enters the fifth stage; In the fifth stage, this regulation ends.

9. The integrated testing and training system for scientific fat loss according to claim 1, characterized in that: In the optimal fat loss training module, power regulation is performed according to a power function.

10. The integrated testing and training system for scientific fat loss according to claim 1, characterized in that: The calculation formulas for total energy consumption LostEnergyT and total fat consumption LostFatMessT are: ； ； Where n1 is the number of breaths in the whole process.

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