Diet inference system and method combining blood glucose monitoring and mobile phone behavior

By combining blood glucose monitoring with mobile phone behavior and using a deep learning model to fuse physiological signals and behavioral data, a non-intrusive, continuous, and highly accurate inference of food intake is achieved. This solves the problems of poor user experience and limited accuracy in traditional methods and is suitable for large-scale health management.

CN122290890APending Publication Date: 2026-06-26NANTONG UNIV
0 Cites 0 Cited by

Patent Information

Application Number
CN202610215683.5
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-02-14
Publication Date
2026-06-26

AI Technical Summary

Technical Problem

Existing methods for recording food intake have poor user experience, are burdensome to participate in, and have limited inference accuracy, making it impossible to accurately determine eating events and food types.

Method used

By combining blood glucose monitoring with mobile phone behavior, and integrating physiological signals and behavioral context information through smartphones and continuous blood glucose monitoring devices, a deep learning model is used to infer dietary intake, achieving a seamless, continuous, and highly accurate inference of food intake.

Benefits of technology

It improves the accuracy and granularity of dietary inference, reduces the false alarm rate, achieves 24/7 unburdened automatic monitoring, adapts to individual differences among different users, and is low-cost and easy to promote.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The invention discloses a diet inference system and method combining blood glucose monitoring and mobile phone behaviors. The system comprises a data acquisition module; a data processing and feature extraction module; a multi-modal fusion and joint inference module: a user interaction and calibration module; and the result output and visualization module presents the inference result to the user or uploads the inference result to a health management platform. The method comprises the following steps: synchronously acquiring continuous blood glucose monitoring time sequence data of a user and multi-modal behavior perception data from a mobile terminal; a joint inference model is constructed by performing timestamp alignment, feature extraction and fusion on the two types of data. According to the method, physiological response of continuous blood glucose monitoring and direct behavior observation of the smart phone are fused, and meanwhile, 'behavior precursor 'and'physiological consequence' of the event are utilized, so that the feeding event detection is more reliable, and blood glucose fluctuation caused by pure movement or pressure can be effectively eliminated.
Need to check novelty before this filing date? Find Prior Art