Heart rate and respiration rate monitoring method and system based on remote photoplethysmography

By integrating face detection and tracking models in remote photoplethysmography technology and combining heart rate breathing rate monitoring model, high-precision real-time monitoring of heart rate and breathing rate among multiple people is achieved, solving the monitoring problems in multi-person scenarios in the existing technology.

CN119856905APending Publication Date: 2025-04-22天津(滨海)人工智能创新中心
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Patent Information

Application Number
CN202411869243.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-18
Publication Date
2025-04-22

AI Technical Summary

Technical Problem

The existing remote photoplethysmography technology mainly stays in single-person scenarios, lacks the model application deployment of dynamic multi-person scenarios, making it difficult to realize real-time monitoring of heart rate and respiration rates of multiple people.

Method used

By integrating the face detection model and face tracking model on the model inference end, combining the remote photoplethysmography model, the current image data with face images is obtained, and the trained heart rate and breathing rate monitoring model is used for inference to monitor the heart rate and breathing rate of multiple people in real time.

Benefits of technology

It realizes high-precision real-time monitoring of heart rate and respiration rates for multiple people, and can work effectively in resource-constrained environments, shorten development cycles and reduce the consumption of manpower and hardware resources.

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Abstract

The invention provides a heart rate and respiration rate monitoring method and system based on remote photoplethysmography, and the method comprises the steps: obtaining current image data with a face image based on a model reasoning end; inputting the current image data into a heart rate and respiratory rate monitoring model, and performing monitoring reasoning by using the heart rate and respiratory rate monitoring model to obtain the identity of the person, the heart rate of the person and the respiratory rate of the person in the current image data; wherein the heart rate and respiration rate monitoring model is obtained by training a remote photoplethysmography model at a model training end by adopting historical image data, and then is imported into the model reasoning end; a face detection model and a face tracking model are integrated in the model reasoning end. A mode of combining a model training end and a model reasoning end is adopted, so that a heart rate and respiratory rate monitoring model, a face detection model and a face tracking model are effectively combined, and heart rate and respiratory rate physiological signs of identities of multiple persons can be obtained and monitored in real time.
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