Developing an affective Point-of-Care technology

Abstract

Mobile intelligent clinical monitoring systems provide mobility and out of hospital monitoring. It can be used in the follow-up of high-risk patients in out of hospital situations and to monitor “healthy” persons to prevent medical events. The inherent characteristics of local diagnosis and actuation permit an improvement and advance in the diagnosis and emergency decision support. Additionally, Affective Systems have been used in different applications, such as stress monitoring in aircraft seats and managing sensitivity in autism spectrum disorder. Although many scientific progresses have been made there are many computational challenges in order to embedded affectivity into traditional user interfaces. For example, context-sensitive algorithms, low-complexity pattern recognition models and hardware customizations are requirements to support the simplification of user's experience becoming more intuitive, transparent and less obstructive. In this paper a multiparametric affective monitor is presented. The Emopad acquisition system has been developed to analyze user's biofeedback particularly when they are playing games. It is able to capture Galvanic Skin Response (GSR), Temperature, Force, Heart Rate (HR) and its variability (HRV) while complementary algorithms are executed to recognize events related to user's emotional states. Also, in this paper a sliding window-based algorithm is presented and evaluated to detect specific events related to emotional responses. The success of multiparametric affective monitors can lead to a paradigm shift, establishing new scenarios for the Point-of-Care technologies applications.