Method and devices of quantification of an occurrence probability of a stroke condition
By combining facial and upper-body movements with pronunciation in a machine learning model, the method enhances stroke detection accuracy, facilitating timely medical intervention.
WO2026139265A1PCT designated stage Publication Date: 2026-07-02AI STROKE
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- AI STROKE
- Filing Date
- 2025-12-15
- Publication Date
- 2026-07-02
AI Technical Summary
Technical Problem
Current systems for detecting strokes are often inaccurate due to the variability and complexity of stroke symptoms, leading to misdiagnosis and delayed medical intervention.
Method used
A method involving a combination of facial movements, upper-body movements, and pronunciation of words, captured through images and sounds, is used to train a machine learning model to quantify the probability of a stroke condition, utilizing a series of instructions to enhance detection accuracy.
Benefits of technology
This approach allows for more accurate determination of stroke conditions by integrating multi-modal data, improving the precision of stroke detection and enabling early intervention.
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Smart Images
Figure EP2025087187_02072026_PF_FP_ABST
Abstract
The method of quantification of an occurrence probability of a stroke condition, comprises the steps of: - providing, by a computer interface, instructions to a user, - capturing a series of images and sounds of the user during the execution of each instruction, - extracting, by a computing device, features from each series captured, - providing the extracted features for each instruction to a dedicated trained machine learning model, said trained machine learning model being trained to associate an intermediate quantified value of an occurrence probability of a stroke condition, - receiving the several intermediate quantified value of an occurrence probability of a stroke condition, - providing the several received intermediate quantified value of an occurrence probability of a stroke condition to a trained machine learning model, said trained machine learning model being trained to associate a final quantified value of an occurrence probability of a stroke condition with several intermediate quantified values of an occurrence probability of a stroke, - receiving the final quantified value of an occurrence probability of a stroke condition, and - providing the final quantified value of an occurrence probability of a stroke condition.
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