Intelligent table and chair sitting posture adjusting method based on pressure center track

By arranging a grid-like pressure sensor array and a machine learning model on the seat, the system can identify and drive the adjustment of the table and chair mechanism in real time, solving the problems of lag and interference in existing posture correction technologies, achieving imperceptible posture correction, and improving health and work efficiency.

CN122004597APending Publication Date: 2026-05-12ZHEJIANG FORESTRY UNIVERSITY
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Patent Information

Application Number
CN202610134508.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-01-30
Publication Date
2026-05-12

AI Technical Summary

Technical Problem

Existing technologies have drawbacks in identifying and correcting poor posture, such as lag and interference with user work, and cannot achieve real-time, imperceptible posture correction.

Method used

By arranging a grid-like pressure sensor array on the seat, pressure distribution data is collected in real time, the characteristics of the pressure center trajectory are calculated, and a machine learning model is used to identify the sitting posture, driving the table and chair mechanism to make imperceptible adjustments, prompting the user to return to a standard sitting posture.

Benefits of technology

It achieves real-time, imperceptible posture correction, improves recognition accuracy, reduces the duration of poor posture, lowers health risks, and enhances user comfort and work efficiency.

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Abstract

The invention discloses an intelligent table and chair sitting posture adjusting method based on a pressure center track, and the method comprises the following steps: S1, obtaining pressure distribution data of a user in real time through a pressure sensor array arranged on a seat surface and / or a backrest, and calculating and generating a pressure center track changing along with time; s2, preprocessing the acquired pressure center trajectory data, and extracting kinematics and statistics characteristics of the pressure center trajectory data; s3, based on the extracted features, performing real-time identification and classification on the sitting posture state of the current user by using a pre-trained machine learning classification model, and judging whether the sitting posture belongs to a standard sitting posture or one or more pre-defined bad sitting postures; and S4, if the identification result is that the sitting posture is bad, generating a corresponding adjustment instruction, and controlling a driving mechanism of the table and chair to execute a preset adjustment action so as to promote or assist the user to recover to the standard sitting posture. According to the invention, the user can be physically guided to recover to the standard sitting posture unconsciously, and the comfort and health level are improved.
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