Non-invasive devices, systems, and methods for monitoring blood flow and coagulation

By combining non-invasive biosensors and machine learning algorithms, real-time monitoring of blood flow and coagulation changes can be achieved, solving the problem of accuracy in venous thrombosis prediction and improving the effectiveness of thrombosis diagnosis and treatment.

CN120603532APending Publication Date: 2025-09-05POPCHECK TECHNOLOGIES INC
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Patent Information

Application Number
CN202380091756.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Priority Date
2022-11-30
Filing Date
2023-11-30
Publication Date
2025-09-05

AI Technical Summary

Technical Problem

Existing technologies make it difficult to accurately predict the probability of thrombosis in the venous system, leading to delayed diagnosis and inappropriate treatment. Traditional scoring systems fail to consider social determinants, imaging examinations lack specific standards, and the use of anticoagulants has individual differences and risks.

Method used

Using non-invasive biosensor patches or sleeves, combined with machine learning algorithms, electrical stimulation of the calf muscles or other local muscles is performed to monitor blood flow and coagulation changes in real time, and the AI ​​system is used to predict the probability of thrombosis and generate risk scores and alerts.

Benefits of technology

It achieves safe and reliable prediction of the probability of thrombosis in different environments, improves the accuracy of diagnosis and the timeliness of treatment, and reduces the risk of delayed diagnosis and inappropriate treatment.

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Abstract

A wearable device, which includes an external patch or cover that adheres to the skin, is used to stimulate and identify changes in blood flow and coagulation. A non-invasive transcutaneous electrical muscle stimulator (EMS) is embedded in the patch or cover and provides sequential stimulation to the surrounding tissue of the blood vessel to promote blood flow. The stimulation system includes a series of electrodes positioned on the skin by a patch or cover, and an external programmable generator with wireless connectivity during stimulation. Biosensors in the patch or cover and other biosensors applied to the body periodically check whether there is an abnormal biomarker pattern. These patterns may be used as early indicators by artificial intelligence (AI) / machine learning (ML) systems, or by prediction methods to predict blood flow and clotting changes caused by venous thrombosis. When an abnormal biomarker pattern is detected, an alert may be sent and a treatment response initiated.
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