A Trusted Affective Model Approach to Proactive Health Monitoring System

Abstract

How to intensify real-time health monitoring to patients effectively and correctly is a crucial and acknowledged precondition for the adoption of new intelligent technologies such as affective and proactive computing. This paper proposed an overview of the approaches to build a reliable affective model on the basis of affective trust theory for high accurate health monitoring systems. Proactive environment was applied for health monitor to provide ideal environments and achieve monitor tasks by sensor or machine vision so as to minimize mistakes for patients in advance. A central design for trusted monitor report was how to capture patient's affective expressions. In general, a person-independent affective model based on swift trust was proposed for specific patient's facial expressions and biomedical signals were caught by sensor for swift trusted comparison with emotions. Based on cognitive analysis, the model could help analyze and void the crucial mistaken reports for real-time health monitoring systems.