Method and device for realizing weight losing target in period

Abstract

The invention particularly relates to a method and a device for realizing a weight losing target in a period. According to the specific technical scheme, the method for realizing the weight losing target in the period comprises the steps of data acquisition and data processing; and calculating daily net energy consumption delta E. The invention provides a personalized weight-losing service method and device aiming at body characteristics and user requirements. The daily energy consumption and weight loss value of the user are calculated by collecting data such as basic information, daily diet and exercise conditions of the user, and the calculation result is corrected by introducing information such as medicine use conditions and psychological states. On the basis, diet, exercise and medication schemes can be recommended in a personalized mode according to the weight loss target of the user, tracking and monitoring are carried out in time, and the task of losing weight within the cycle is helped to be completed.

Description

Technical Field

[0001] The invention belongs to the field of fitness, and in particular relates to a method and a device for achieving a weight loss target within a cycle. Background Art

[0002] With the development of economy and society and the improvement of quality of life, the obesity rate is getting higher and higher. At the same time, people's requirements for body shape are getting higher and higher. Therefore, the market demand for weight loss and body shaping is huge, and the demand for personalized weight loss needs to be met urgently.

[0003] Diet and exercise regulation are the basic ways to control weight. In addition, emotional state and drugs also have an important impact on weight loss. At present, there is a lack of a control method and device that can organically coordinate drugs, diet, exercise and psychology to achieve the goal of weight loss within a cycle. People who want to lose weight often cannot control their food intake and the intensity of daily exercise well, nor can they know the calorie intake value of the relevant diet and the energy consumption value of exercise in detail. In addition, unreasonable excessive dieting or excessive exercise will bring more health and psychological problems, resulting in serious consequences. Summary of the invention

[0004] The object of the present invention is to provide a method and device for achieving the goal of losing weight within a cycle.

[0005] To achieve the above-mentioned purpose, the technical solution adopted by the present invention is: a method for achieving the goal of weight loss within a cycle, comprising the following steps:

[0006] (1) Data collection, including at least: dietary data, daily activities and exercise data, medication data,

[0007] (2) Data processing: the processing methods include:

[0008] 1) Convert the dietary data into the total energy intake of the person who wants to lose weight on that day;

[0009] 2) Calculate the energy consumed by daily activities and exercise TEA: TEA = 0.0175 × w × MET × t; w is body weight, t is exercise time, and MET is exercise intensity;

[0010] 3) Introduce the drug correction coefficient g1, and adjust the energy metabolism formula to: TEA = 0.0175 × w × g1 × MET × t, g1 value is between 0.8-1.2. When the drug taken will increase the basal metabolic rate, g1 is greater than 1, otherwise it is less than 1;

[0011] (3) Calculate the daily net energy expenditure ΔE, ΔE = BMR × g1 × g2 + TEA + TEF-I, BMR is the basal metabolic rate, TEF is the thermal effect of food, TEF = g3 × I, g3 is the thermal effect coefficient of food, the value is 0.1.

[0012] Preferably, an age correction coefficient α is introduced, and the energy metabolism formula is adjusted as follows: TEA = 0.0175 × w × α × g1 × MET × t;

[0013] At 0-1 years old, α = [(150%-100%) / 12] × age in months;

[0014] When the age is 1-20 years old, α = 150% - (age - 1) × 2.6%;

[0015] When the age is 20-60, α = 1;

[0016] For those over 60 years old, α=100%-(age-60)×0.7%.

[0017] Preferably, the mental health factor g2 is introduced, and the energy metabolism formula is adjusted as follows: TEA = 0.0175 × w × α × g1 × g2 × MET × t;

[0018] The value of g2 is: use the PHQ-4 mood scale to assess and collect the psychological status of the person to be dieted during the weight loss period. The value of g2 for normal people is 1.0. When anxiety exists, g2 increases by 10% for each level of severity; when depression exists, g2 decreases by 10% for each level of severity.

[0019] Preferably, step (4) is added after step (3):

[0020] (4) Convert the daily net energy consumption value ΔE into the expected daily weight loss value Δw,

[0021]

[0022] η is the adjustment coefficient, which increases with the number of days of weight loss. The value is 0.3-0.4 in the first week, 0.7 for men and 0.5 for women in the third week, and increases and stabilizes at 0.8-0.9 after the fourth week.

[0023] Accordingly, a device for implementing the method includes:

[0024] A data collection unit, used to collect data required by the method;

[0025] A data processing unit, used to process data according to the method requirements;

[0026] The data output unit is used to output the data processing results.

[0027] Accordingly, a terminal device includes at least one processor and at least one memory; at least one program is stored in the memory and is configured to be executed by the processor to perform the method.

[0028] Accordingly, a computer-readable storage medium is provided, wherein program code is stored in the computer-readable storage medium, and the method is executed when the program code is executed by a processor.

[0029] The present invention has the following beneficial effects: The present invention provides a personalized weight loss service method and device based on physical characteristics and user needs. By collecting basic information, daily diet and exercise data of the user, the user's daily energy consumption and weight loss value are calculated, and information such as drug use and psychological state are introduced to correct the calculation results. On this basis, personalized diet, exercise and medication plans can be recommended according to the user's weight loss goals, and timely tracking and monitoring can be carried out to help complete the task of weight loss within the cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 Schematic diagram of the validation of the daily expected weight loss value model effect. DETAILED DESCRIPTION

[0031] The present invention provides a method for achieving a weight loss goal within a cycle, specifically, based on the daily diet, exercise, drug use and other data of the person to be weight-loss, the daily energy intake and consumption of the person to be weight-loss are evaluated, and based on the weight loss goal set by the person to be weight-loss and the actual situation, weight management suggestions on diet, exercise and drug are put forward, so as to help the person to achieve the weight loss goal within a specific cycle. The specific steps include:

[0032] 1. Data collection and processing. The collected data includes at least: dietary data, daily activities and exercise data. It can also include: medication status and psychological status assessment.

[0033] (1) Dietary data collection and processing. Dietary data collection methods include: manual input by the person to be dieted, or automatically importing local per capita dietary data based on local dietary habits by inputting the area where the person to be dieted is located, or automatically importing relevant data based on local dietary habits after the person to be dieted selects the area, and the person to be dieted then makes adjustments based on actual conditions. The frequency of collecting this part of data is from 3 times a day to once a week, which is determined by the person to be dieted according to changes in the dietary structure of the person to be dieted. If the operator does not make adjustments, the dietary data for the day will be the same as the previous day by default.

[0034] After collecting the dietary data, the total energy intake of the person who is trying to lose weight that day (unit: kcal / g) is calculated using the nutrient conversion table in the Chinese Food Composition Table. For example, consuming 100g of rice is equivalent to consuming 307kcal of calories; consuming 100g of noodles is equivalent to consuming 344kcal of calories.

[0035] (2) Collection and processing of daily activity and exercise data. The daily energy consumption of the human body mainly includes two aspects: one is the energy required to maintain normal life activities of the human body in a resting state, which is calculated based on the user's basal metabolic rate and other data; the other is the calorie consumption caused by the additional activities of the person to lose weight, the most important of which is exercise.

[0036] The collection method is: the person who wants to lose weight fills in / selects the type of exercise, duration and intensity of exercise performed daily in the program. According to the exercise intensity (metabolic equivalent, MET value) of different sports, the corresponding energy consumed can be calculated. 1.0 MET is equivalent to the energy metabolism rate of a healthy adult at rest and sitting, and its value is 3.5 mL / kg / min; during exercise, because skeletal muscles need more energy and oxygen, the MET value will increase. Calculate the energy consumed by daily activities and exercise TEA (unit: calories) according to the following formula.

[0037] TEA=0.0175×w×MET×t

[0038] Among them, w is body weight (unit: kg), t is exercise time (unit: min), and the MET value comes from the MET data in the "Reference Values ​​of Energy Expenditure of Physical Activity in Healthy Adults in China" (Chinese Journal of Sports Medicine, 2022.5.25).

[0039] At the same time, the strength of metabolism is also related to age. Throughout the life cycle, the law of energy metabolism presents a pattern of "rapid increase-decrease-stabilization-slow decrease". Total energy consumption increases in a power law with the increase of lean body mass. After correcting for lean body mass, it is found that there are four different stages of changes in daily energy consumption (total energy consumption and basal energy consumption): 0-1 years old, 1-20 years old, 20-60 years old, and >60 years old. The energy consumption level of newborns is similar to that of adults. From birth to 1 year old, the energy consumption level rises rapidly to 150% of that in adulthood, and then continues to decline and remains stable from 20 to 60 years old, and begins to decline slowly again after 60 years old. In summary, the age correction coefficient α is calculated according to Table 1.

[0040] Table 1 Comparison table of age correction coefficient calculation formula

[0041]

[0042]

[0043] After introducing the age correction coefficient α, the energy metabolism formula is adjusted to:

[0044] TEA=0.0175×w×α×MET×t

[0045] The total daily TEA is the sum of the TEA of all activities and sports performed on that day.

[0046] (3) Data collection and processing of medication status. The current medication status of the person to be weight-loss is collected through manual input by the operator, including the name of the drug and the daily dosage, and the drug correction coefficient g1 is introduced accordingly. Generally speaking, the value of g1 is between 0.8-1.2. When the medication taken increases the basal metabolic rate, g1 is greater than 1, otherwise it is less than 1. The medication status that needs to be collected and the corresponding g1 are shown in Table 2. It should be noted that the g1 coefficient is obtained by the inventor's team through a specific method and is protected as a trade secret. The method for obtaining the g1 coefficient is not disclosed in the present invention.

[0047] Table 2 Comparison table of drugs and correction factor g1

[0048]

[0049]

[0050] After introducing the drug correction coefficient g1, the energy metabolism formula is adjusted to:

[0051] TEA=0.0175×w×α×g1×MET×t

[0052] (4) Collection and processing of psychological status data. The emotional state of the person who is losing weight has an important impact on the body's energy metabolism efficiency. The PHQ-4 emotional scale was used to assess and collect the psychological state of the person who is losing weight during the weight loss period. The core symptoms / signs of depression and anxiety were measured by combining the measurement of two items consisting of the core criteria of depression (PHQ-2) and the measurement of two items of anxiety (GAD-2). The measurement questions and scores are shown in Table 3. In Table 3, the first two questions constitute the GAD-2 subscale to measure anxiety; the last two questions constitute the PHQ-2 self-scale to measure depression. The total score of each subscale is 6, and the total score is 12 points. When the corresponding subscale score is 0-1, it is a normal level, 2 is mild anxiety / depression, 3-4 is moderate anxiety / depression, and 5-6 is severe anxiety / depression.

[0053] Table 3 Psychological state data collection and evaluation table

[0054]

[0055]

[0056] Anxiety increases metabolic rate, while depression usually decreases metabolic rate and causes metabolic disorders. Therefore, the psychological health factor g2 is introduced. The value of normal people is 1.0. When anxiety exists, g2 increases by 10% for each level of severity; when depression exists, g2 decreases by 10% for each level of severity. For example, a person with moderate anxiety (PHQ-2 score of 3-4 points) and mild depression (GAD-1 score of 2 points) has a g2 value of 0.9×1.2×1.0=1.08.

[0057] After the introduction of mental health factor g2, the energy metabolism formula is adjusted to:

[0058] TEA=0.0175×w×α×g1×g2×MET×t

[0059] 2. Calculate the daily net energy consumption. The user's daily energy intake (I) is converted into energy (kcal) based on the collected dietary data using the nutrient conversion table in the "Chinese Food Composition Table" and then added up. Energy consumption consists of three parts: basal metabolic rate (BMR), energy consumption from daily activities and exercise TEA, and food thermal effect TEF.

[0060] In summary, the daily net energy expenditure (ΔE) is calculated according to the following formula (unit: kcal):

[0061] ΔE=BMR×g1×g2+TEA+TEF-I

[0062] Among them, g1 is the drug correction factor, and g2 is the mental health factor. BMR is the basal metabolic rate, which is the amount of energy required to consume daily while keeping the weight constant (unit: kcal / d). BMR is affected by gender, age, and BMI (body mass index, weight (kg) / height). 2 (m)).

[0063] Women: BMR = 447.6 + 9.25 × weight + 3.10 × height - 4.33 × age

[0064] Male: BMR = 88.4 + 13.4 × weight + 4.8 × height - 5.68 × age

[0065] In the formula, height is in centimeters, weight is in kilograms, and age is in years. The calculated BMR is the energy consumed per day in a resting state.

[0066] The thermal effect of food (TEF) is the phenomenon of increased energy consumption due to eating. Its value is related to the energy of daily food intake, which is generally 10% of the caloric intake of food, that is, TEF = g3 × I, g3 is the thermal effect coefficient of food, and its value is 0.1.

[0067] 3. Convert the daily net energy consumption value ΔE into the expected daily weight loss value Δw.

[0068]

[0069] The denominator in the formula is the energy expenditure corresponding to a 1kg weight loss (unit: kcal / kg). When the weight loss is entirely fat, an average of about 7700 kcal of calories is consumed for every 1kg of fat loss. In fact, weight loss is a dynamic process, and the required energy deficit (i.e., the difference between daily energy expenditure and energy intake) is not constant, nor is it entirely fat. When losing weight through diet or exercise, the differences in weight loss and physiological and behavioral responses between individuals are also obvious. Therefore, it is necessary to multiply the correction factor η on the basis of 7700 kcal. The total average energy deficit required for obese women to change their weight within 4 days is 2500 kcal / kg. The energy deficit required for weight change within 3 weeks is 3810 kcal / kg and 5507 kcal / kg for men and women, respectively. It increased significantly in the fourth week, reaching 6119 and 6804 kcal / kg for men and women, respectively. The energy deficit required for women to lose weight is often 20-25% higher than that of men. The main reason is the difference in body composition between men and women. Women have higher initial body fat than men, and will allocate a larger proportion of net energy deficit toward reducing body fat. Therefore, losing the same amount of weight requires a larger energy deficit.

[0070] Therefore, the value of η is a gender-related value that changes dynamically over time. In the early stages of the weight loss cycle, the value of η is small, ranging from 0.3 to 0.4 in the first week, and then gradually increases to 0.7 and 0.5 for men and women, respectively, in the third week. After the fourth week, it gradually increases and stabilizes between 0.8 and 0.9. The calculation formula for η is shown in Table 4.

[0071] Table 4 Comparison table of calculation formulas for correction factor η

[0072]

[0073]

[0074] The technical scheme of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Unless otherwise specified, the technical means used in the embodiments are conventional means well known to those skilled in the art. The data obtained are all average values ​​obtained after at least 3 repetitions, and all the repetitions obtained are valid data.

[0075] Example: Validation of the model effect of daily expected weight loss value

[0076] 1. Select volunteers. Males and females aged 18 years and above, without major diseases; BMI ≥ 28 kg / m 2 ; Able to express and communicate in Mandarin, and able to read and write Chinese; Have experience using computers or smartphones; Willing to comply with the trial procedures / regulations and able to sign the informed consent. The following groups were also excluded: patients with gastrointestinal diseases accompanied by malabsorption; patients with active liver disease or significant liver damage, defined as alanine aminotransferase (ALT) levels exceeding 2.5 times the upper limit of normal; patients with a history of unstable or rapidly progressive kidney disease or renal impairment, defined as serum creatinine 133umol / L for male subjects or 125umol / L (1.4mg / dL) for female subjects; patients diagnosed with diabetes or obesity caused by Cushing's syndrome and other endocrine diseases; patients who have undergone weight loss surgery; patients with mental disorders and unwilling to communicate with him; Those who cannot communicate with others, have language barriers that lead to insufficient understanding of the research project, or are unable to cooperate with researchers; those with severe cardiopulmonary insufficiency, hypothyroidism, and malformed tumors; pregnant women, breastfeeding women, women who plan to become pregnant during the study, and women of childbearing age who refuse to use effective, medically recognized contraceptive measures during the study; those with a history of alcoholism; those with physiological dysfunction that affects aerobic and resistance exercise; those with a weight loss of more than 5% in the past 6 months; hypertensive patients with poorly controlled blood pressure; those who are currently participating in or have participated in other interventional clinical studies within four weeks before screening.

[0077] Through the above screening, 150 subjects were finally selected, half of them were male and half were female. Anthropometric characteristics (height, weight, gender, age, etc.), eating information (nutrients, eating time, etc.), daily activities and exercise conditions (exercise heart rate, speed, time, etc.) were collected. Convolutional neural network algorithms were used to extract features from anthropometric characteristics, exercise and diet data, and multimodal feature fusion was performed. Machine learning and deep learning models were used to extract features, and a model was established to predict energy consumption in each stage of exercise, rest, eating, and sleep in different time periods.

[0078] The digital metabolic chamber is used as a measurement standard for the actual daily energy metabolism of the subjects, which is verified with the measurement results of the digital metabolic chamber. The metabolic chamber is a room (space) that uses whole-room indirect calorimetry to measure human energy metabolism. The subjects can move freely in the chamber for 24 hours to several days, and the different components of their energy consumption, such as the thermal effect of food and resting metabolic rate, can be calculated and recorded in real time. The system samples the air in the room, and the subject's oxygen consumption and carbon dioxide production can be determined by calculating the dynamic changes in the gas composition.

[0079] Among them, the calculation formula of oxygen consumption (VO2) is:

[0080] VO2=(FRe×((FiO2-FeO2)-FiO2×(FeCO2–FiCO2)) / (1-FiCO2)

[0081] The calculation formula for carbon dioxide production (VCO2) is:

[0082] VCO2=(FRe×((FeCO2-FiCO2)+FiCO2×(FiO2–FeO2)) / 1+FiCO2

[0083] In the formula: FeO2 is the outlet oxygen concentration, FeCO2 is the outlet carbon dioxide concentration, FiO2 is the inlet oxygen concentration, FiCO2 is the inlet carbon dioxide concentration, and FRe is the outlet airflow rate (under standard temperature and humidity).

[0084] Then use Weir's formula to calculate the standard metabolic expenditure value EE:

[0085] EE=3.941×VO2+1.106×VCO2

[0086] The calculated EE is compared with the energy consumption value ΔE (introducing g1 and g2) calculated by the method of the present invention for verification. Figure 1 shown. Figure 1 The solid line in the middle is the actual daily energy consumption data of the subjects measured by the digital metabolic chamber; the dotted line is the daily energy consumption data calculated according to the method of the present invention based on human characteristics, exercise, diet, medication and other data; the gray box represents the execution time of each stage of sleep, rest, exercise and eating. It can be seen that the data measured in the metabolic chamber is basically consistent with the data measured according to the method of the present invention.

[0087] Using time-use epidemiology and the "co-variation" method, the epidemiological significance behind the data was explored, and the weight was recorded daily with a weight scale in the metabolic chamber, and verified with the estimated weight loss Δw calculated by the method of the present invention. The results showed that the average prediction rate of the estimated weight loss Δw of these 150 subjects (calculation method: 1-absolute value of relative error / true value) was 87.3%.

[0088] The embodiments described above are only descriptions of the preferred modes of the present invention and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various deformations, modifications, and substitutions made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for achieving a weight loss goal within a cycle, characterized in that: The steps include: (1) Data collection, including at least: dietary data, daily activities and exercise data, and medication data; (2) Data processing: the processing methods include: 1) Convert the dietary data into the total energy intake of the person who wants to lose weight on that day; 2) Calculate the energy consumed by daily activities and exercise TEA: TEA = 0.0175 × w × MET × t; w is body weight, t is exercise time, and MET is exercise intensity; 3) Introduce the drug correction coefficient g1, and adjust the energy metabolism formula to: TEA = 0.0175 × w × g1 × MET × t, g1 value is between 0.8-1.

2. When the drug taken will increase the basal metabolic rate, g1 is greater than 1, otherwise it is less than 1; (3) Calculate the daily net energy expenditure ΔE, ΔE = BMR × g1 × g2 + TEA + TEF-I, BMR is the basal metabolic rate, TEF is the thermal effect of food, TEF = g3 × I, g3 is the thermal effect coefficient of food, the value is 0.

1.

2. The method according to claim 1, characterized in that: The age correction coefficient α was introduced to adjust the energy metabolism formula: TEA = 0.0175 × w × α × g1 × MET × t; At 0-1 years old, α = [(150%-100%) / 12] × age in months; When the age is 1-20 years old, α = 150% - (age - 1) × 2.6%; When the age is 20-60, α = 1; For those over 60 years old, α=100%-(age-60)×0.7%.

3. The method according to claim 2, characterized in that: Introducing the mental health factor g2, the energy metabolism formula is adjusted to: TEA = 0.0175 × w × α × g1 × g2 × MET × t; The value of g2 is: use the PHQ-4 mood scale to assess and collect the psychological status of the person to be dieted during the weight loss period. The value of g2 for normal people is 1.

0. When anxiety exists, g2 increases by 10% for each level of severity; when depression exists, g2 decreases by 10% for each level of severity.

4. The method according to claim 1, characterized in that: Add step (4) after step (3): (4) Convert the daily net energy consumption value ΔE into the expected daily weight loss value Δw, η is the adjustment coefficient, which increases with the number of days of weight loss. The value is 0.3-0.4 in the first week, 0.7 for men and 0.5 for women in the third week, and increases and stabilizes at 0.8-0.9 after the fourth week.

5. A device for implementing the method according to any one of claims 1 to 4, characterized in that: The device comprises: A data collection unit, used to collect data required by the method; A data processing unit, used to process data according to the method requirements; The data output unit is used to output the data processing results.

6. A terminal device, characterized in that: The device comprises at least one processor and at least one memory; at least one program is stored in the memory and is configured so that the processor executes the method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores program codes, and when the program codes are executed by a processor, the method according to any one of claims 1 to 4 is executed.

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