METHOD AND SYSTEM FOR ASSESSING THE HEALTH OF THE HUMAN BODY BASED ON THE LARGE-VOLUME SLEEP DATA

FIELD: medicine.SUBSTANCE: group of inventions relates to medicine, namely, to assessment of human health based on the large-volume sleep data. Proposed is a terminal apparatus containing a system for implementing the method, wherein the system comprises a sleep data receiving unit for obtaining various physiological data on the human body during sleep, wherein the data is supplied from a sensor installed on the electric bed or an intelligent bed containing an electrical control system; a sleep data storage unit containing a cloud server for storing all the sleep data collected by the sleep data receiving unit, wherein the cloud server is configured to interact with the database of the control system for receiving sleep data in real time; a unit for training using the data for pre-processing the sleep data and training using the data by means of an artificial intelligence learning module for obtaining the physiological assessment index; a unit for training a classifier model for training the classifier model on the sleep data obtained during training of the artificial intelligence learning model; and a report generating unit for generating a report on the analysis of the state of human health in accordance with the human physiological assessment index and the classifier model obtained based on the training using the data; wherein the unit for training using the data comprises: a pre-processor for data processing, intended to filter incomplete and incorrect sleep data stored on the cloud server and enter the correct data into the artificial intelligence learning model for training so that the artificial intelligence learning model could study the characteristics of diseases and conduct calculations in order to obtain the physiological assessment index; and an autoencoder for creating an autoencoder network and conducting iterative training using the data by calculating the losses of the network; wherein the correct data after pre-processing is divided into sleep data with the tag of the disease and sleep data without the tag of the disease, wherein the sleep data with the tag of the disease comes from the body of a person suffering from a disease of a known type while the sleep data without the tag of the disease comes from the body of a person with a condition corresponding to an unknown disease; wherein the process of entering the correct data into the artificial intelligence learning model for training includes: sending the sleep data without the tag of