Sleep age assessment method and system

By acquiring basic personal data and inherent sleep data, and using a preset model to calculate the baseline and deviation values ​​of sleep age, the problem of subjective error and equipment complexity in sleep age assessment in existing technologies is solved, enabling convenient sleep age assessment and health management.

CN121617641BActive Publication Date: 2026-06-05AIMENG SMART HOME (ZHUHAI) CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
AIMENG SMART HOME (ZHUHAI) CO LTD
Filing Date
2026-02-02
Publication Date
2026-06-05

AI Technical Summary

Technical Problem

Existing methods for assessing sleep age suffer from large subjective assessment errors and require complex and uncomfortable objective assessment equipment, making it difficult to achieve convenient long-term sleep monitoring.

Method used

By acquiring the target user's basic personal data and inherent sleep data, a feature array is constructed. A preset sleep age prediction model is used to generate a basic sleep age value. Combined with sleep monitoring data, the sleep age deviation value is calculated, and the actual sleep age is finally determined, avoiding the memory bias of subjective assessment and the reliance on complex devices.

Benefits of technology

It enables long-term, convenient, and objective sleep monitoring, accurately reflecting the degree of match between sleep status and physiological age, and providing users with more practical references for sleep improvement and health maintenance.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application discloses a sleep age evaluation method and system, and the method comprises the following steps: obtaining user data and sleep monitoring data of a target user, wherein the user data comprises personal basic data and inherent sleep data; determining a sleep age basic value of the target user based on the personal basic data and the inherent sleep data; determining a sleep age deviation value of the target user based on the sleep monitoring data and the inherent sleep data; and determining an actual sleep age of the target user based on the sleep age basic value and the sleep age deviation value. The application can avoid subjective evaluation deviation and realize long-term and convenient monitoring without complex equipment by using inherent sleep data of a user. By using the logic of 'basic value + deviation value', the matching degree of the current sleep state of a user and the long-term inherent mode can be accurately reflected by combining personal data, long-term and short-term sleep data differences, and the long-term mode and short-term fluctuations are taken into account, thereby providing a practical reference for the health of a user and making up for the shortcomings of the existing method.
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