Emotion recognition method and system based on multi-modal biological characteristics

By employing a multimodal biometric recognition method, which utilizes eye movement, micro-expression, and voice feature data to calculate credibility and coupling, the problem of emotion masquerading and modal response sequence recognition in existing technologies is solved, thus achieving accurate recognition of genuine emotions.

CN121808672APending Publication Date: 2026-04-07FOURTH MILITARY MEDICAL UNIVERSITY
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Patent Information

Application Number
CN202511929126.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-19
Publication Date
2026-04-07

AI Technical Summary

Technical Problem

Existing biometric emotion recognition technologies cannot distinguish between controllable expressive features and uncontrollable physiological features, cannot identify emotional spoofing scenarios, and cannot identify the real emotion generation path through modal response sequence.

Method used

By using multimodal biometric recognition methods and eye movement, micro-expression, and voice feature data, the credibility parameters of eye movement, micro-expression, and voice are calculated. Combined with coupling degree and leading factor, the credibility index of true emotion is determined.

Benefits of technology

It achieves accurate identification of genuine emotions, distinguishes between natural and deliberate expressions, and improves the credibility and accuracy of emotion recognition.

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Abstract

The invention discloses an emotion recognition method and system based on multi-modal biological characteristics, and relates to the technical field of emotion recognition, and the system comprises a multi-modal module, a calculation module, a dynamic module and a summary module. A coupling unit on the summarizing module also calculates a first coupling degree between the eye movement features and the micro-expression features and a second coupling degree between the eye movement features and the voice features through the eye movement feature fluctuation degree, the micro-expression feature fluctuation degree, the voice feature fluctuation degree and a coupling formula respectively, and when the value of the first coupling degree is closer to 1, the second coupling degree is closer to 1; the micro-expression features and the eye movement features are more synchronous, the micro-expression features and the eye movement features of the tested person are closer to natural physiological reactions, and the micro-expression features are not deliberately controlled; when the numerical value of the second coupling degree is closer to 1, the voice features and the eye movement features are more synchronous, further, the voice features and the eye movement features of the testee are closer to natural physiological reactions, and the voice features are not deliberately controlled.
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