Self-adaptive waist chasing method, computer readable storage medium and intelligent seat

By dynamically adjusting the lumbar support through a pressure sensor array and recognition model, the shortcomings of smart seats in adaptability to body shape and sitting posture are resolved, personalized lumbar support adjustment is achieved, and user comfort is improved.

CN120732265APending Publication Date: 2025-10-03HANGZHOU HEIBAIDIAO TECH CO LTD
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Patent Information

Application Number
CN202510895619.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-06-27
Publication Date
2025-10-03

AI Technical Summary

Technical Problem

Existing smart seats use fixed threshold judgments or preset modes for lumbar support adjustment, which makes it difficult to meet the personalized needs of different users and cannot adapt to body shape differences and dynamic sitting posture changes, resulting in a mismatch between lumbar support and human needs.

Method used

The pressure sensor array is used to collect data in real time, and combined with pre-trained body shape recognition and sitting posture recognition models, the support parameters of the lumbar support adjustment mechanism are dynamically adjusted to achieve personalized lumbar adaptation.

Benefits of technology

It realizes real-time adjustment of lumbar support according to the user's body shape and sitting posture, improves the user's comfort experience, adapts to different body shapes and dynamic sitting posture changes, and provides personalized lumbar support adjustment.

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Abstract

The invention discloses a self-adaptive waist tracking method, a computer readable storage medium and an intelligent seat, the self-adaptive waist tracking method is used for the intelligent seat, the intelligent seat is provided with a pressure sensor array and a waist support adjusting mechanism, and the method comprises the following steps: acquiring real-time pressure data of a current user collected by the pressure sensor array; extracting pressure characteristic parameters according to the real-time pressure data, and determining the body type category of the current user according to the pressure characteristic parameters by using a pre-trained body type recognition model; determining a current sitting posture type and an initial pressure threshold value of the current user according to the real-time pressure data by utilizing a pre-trained sitting posture recognition model; determining a target pressure threshold value according to the real-time pressure data, the body type category and the initial pressure threshold value; according to the target pressure threshold value, supporting parameters of a waist support adjusting mechanism are adjusted, so that the waist support is matched with the waist state of the user. According to the self-adaptive waist-following method, personalized waist-following adaptation of the user in multiple scenes is realized.
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