Artificial intelligence body weight generation management method

Abstract

The present invention discloses an artificial intelligence body weight generation management method, and relates to the technical field of artificial intelligence. A new method for body weight management scheme generation is constructed to achieve a better heat and nutrient threshold value calculation method and a final individual threshold value determination method. The artificial intelligence body weight generation management method fully considers the Chinese metabolic characteristics to control heat and perform standard control and artificial intelligence of three nutrient energy supply rate and saccharides GL value, and a big data setting scheme is obtained. The storage of a database is performed according to regions, the GL value, unit heat and nutrient data, classification indexesare employed to rapidly complete automatic generation of various recipes, and an artificial intelligence push algorithm is employed to push foods or sports which are loved or are the easiest persistedby the individual.

Description

technical field [0001] The present invention relates to artificial intelligence technology, in particular to an artificial intelligence-generated weight management method. Background technique [0002] With the popularity of artificial intelligence and big data, various algorithms emerge in an endless stream. In terms of weight control, program planning is generally carried out from two aspects, namely diet and exercise. The generation method of this type of plan is still at the academic level. Generally, according to the user's gender, age, height, and weight data, 500-1000kcal is subtracted from the calorie recommended by the Chinese Nutrition Society for normal people's diet. Simple calorie control and the corresponding three major energy-supplying nutrients (carbohydrates, fats, proteins) correspondingly reduce the food supply for recipe matching, and so far, most of the calculation work is still dominated by manual work, supplemented by data calculations To generate th...

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Problems solved by technology

[0003] This type of program generation method generally encounters several problems in the actual operation process: first, the effectiveness is poor, the human body has a threshold effect, and has a certain range of automatic adjustment and adaptability. , it is likely that the heat threshold of the individual has not been reached, resulting in some of the generated solutions being invalid or inefficient

Second, the compliance is low. Due to the professional calculation methods of recipes and exercise, the use is complicated, time-consuming, and has a lot to do with the personal experience of the catering chef, resulting in weak flexibility and diversity of the program, and it is difficult for individuals to stick to it.

Third, the rebound rate is relatively high. Because such programs generally do not consider the response of human metabolism from a medical point of view, nor do they consider the changes in metabolic conditions at different stages. During the control process, appetite cannot be controlled, and the new metabolic balance of the human body cannot be controlled. formed, resulting in a rebound

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