Cognitive dysfunction prediction system based on gastrointestinal electrical signal and construction method

A cognitive impairment prediction system based on a gastrointestinal electrical signal, comprising:

• a database configured to store data, wherein a type of the data comprises gastrointestinal electrical signal data and clinical data, and the gastrointestinal electrical signal data are postprandial gastrointestinal electrical signal data;
• wherein the postprandial gastrointestinal electrical signal data comprise postprandial gastric dominant frequency, postprandial gastric percentage of disturbed electrical rhythm, postprandial gastric dominant power ratio, and postprandial intestinal lead time difference;
• wherein the clinical data comprise age, body mass index, high-density lipoprotein, and low-density lipoprotein;
• wherein the data comprise sample data from a sample population and subject data from a subject;
• a data acquisition module configured to acquire the data and store the data in the database;
• a model training module configured to train the sample data using a machine learning algorithm to establish a cognitive impairment prediction model;
• a prediction module configured to acquire the subject data through the data acquisition module and analyze the subject data using the cognitive impairment prediction model to predict a probability of the subject developing cognitive impairment.