System and method for continuous care

By using multiple sensors and machine learning algorithms in the respiratory therapy system, the problem of gaps in physiological data during periods when the user is not wearing the user interface was solved, enabling continuous and accurate monitoring of sleep-related parameters.

CN114727763BActive Publication Date: 2026-06-16RESMED SENSOR TECH LTD +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
RESMED SENSOR TECH LTD
Filing Date
2020-09-11
Publication Date
2026-06-16

AI Technical Summary

⚠Technical Problem

Existing respiratory therapy systems generate gaps in physiological data during periods when the user is not wearing the user interface, making it impossible to accurately determine sleep-related parameters.

⚗Method used

Multiple sensors are used to generate physiological data during periods when the user wears and does not wear the user interface, and the data is then trained and calibrated using machine learning algorithms to determine the user's sleep-related parameters.

🎯Benefits of technology

It enables physiological data calibration during periods when the user is not wearing the user interface, ensuring continuous monitoring and accuracy of sleep-related parameters, and improving the system's data integrity and analytical capabilities.

✦ Generated by Eureka AI based on patent content.

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Abstract

A method includes receiving, from a first sensor, first physiological data associated with a first sleep session of a user. The method also includes receiving, from a sensor, second physiological data associated with the first sleep session of the user. The method also includes determining, based at least in part on the first physiological data, a first set of sleep-related parameters associated with the first sleep session of the user. The method also includes determining, based at least in part on the second physiological data, a second set of sleep-related parameters associated with the first sleep session of the user. The method also includes calibrating the second sensor based at least in part on a comparison between the first set of sleep-related parameters and the second set of sleep-related parameters.
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