Patient restlessness escape behavior early warning method and system based on video image analysis

By constructing a multi-feature fusion analysis framework and a cross-camera tracking system in a closed psychiatric ward, the problem of the inability of existing technologies to comprehensively predict patients' agitated and escape behaviors was solved. This enabled multi-dimensional prediction and precise intervention of patient behavior, reducing the false alarm rate and false negative rate of the system.

CN122135436APending Publication Date: 2026-06-02DATONG SIXTH PEOPLES HOSPITAL (DATONG RONGFU MILITARY HOSPITAL DATONG MENTAL HEALTH CENTER DATONG SOCIAL WELFARE PSYCHIATRIC HOSPITAL)
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
DATONG SIXTH PEOPLES HOSPITAL (DATONG RONGFU MILITARY HOSPITAL DATONG MENTAL HEALTH CENTER DATONG SOCIAL WELFARE PSYCHIATRIC HOSPITAL)
Filing Date
2026-03-18
Publication Date
2026-06-02

AI Technical Summary

Technical Problem

Existing technologies lack intelligent early warning methods for patient agitation and escape attempts that integrate multi-dimensional behavioral precursor features and have cross-camera full-domain tracking capabilities in closed psychiatric wards. As a result, they cannot effectively predict and intervene in patients' agitated and impulsive behaviors and escape attempts.

Method used

A multi-feature fusion analysis framework covering facial emotional state, skeletal posture and movement, and spatial movement trajectory is constructed. Cross-camera identity association and trajectory tracking are achieved through video image analysis. Combined with a time-series early warning mechanism, comprehensive risk assessment and hierarchical early warning are carried out, and a closed-loop feedback mechanism is established to optimize system parameters.

Benefits of technology

It significantly improves the perception dimension and warning comprehensiveness of behavioral precursors, reduces the false alarm rate and missed alarm rate, and enables early prediction and precise intervention of patients' agitated escape behavior.

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Abstract

This invention relates to the fields of computer vision and medical information technology, and discloses a method and system for early warning of patient agitation and escape behavior based on video image analysis. The method includes: video acquisition and adaptive preprocessing; multi-target detection and cross-camera trajectory tracking; parallel analysis of three dimensions: facial emotion, skeletal posture, and trajectory abnormalities; multi-feature temporal fusion risk assessment; and graded early warning and feedback optimization. The system supports early prediction and graded early warning of agitated and impulsive behavior and escape attempts of patients in closed psychiatric wards, effectively assisting nursing staff to take timely intervention measures before the behavior actually occurs, thereby reducing the incidence of agitated and impulsive events and escape events.
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