Abstract Recognizing emotions from physiological signals has proven to be important in various scenarios. To assist developing emotion recognizers, software frameworks and toolboxes have emerged, offering ready-to-use components. However,these limitations regarding the type of supported, recognition steps covered, or acquisition multiple signals. This paper presents metaFERA, an architectural m...

We report on the development of an automated detector acute stress based physiological signals. Our discriminates between high and low levels accumulated by students when performing cognitive tasks a computer. The proposed builds well-known signal processing principles combined with state-of-art support vector machine (SVM) classifier. novelty aspects here come from design implementation pre-pr...

Music influence on people was noticed long time ago. Psychologists look for visual and behavioral effects to explain music influence. Our work is one of the first that tries to view the topic from engineering side, find influence on physiological signals. The work deals with the ECG and Respiratory signals that were taken from newborn while they listened to music. We are applying different anal...

This report studies physiological signals measured from patients in the Intensive Care Unit (ICU). The signals explored include heart rate, arterial blood pressure, pulmonary artery pressure, and central venous pressure measurements. Following an introduction to these signals, several methods are proposed for visualizing the data using time and frequency domain techniques. By way of a patient c...

In this article, we describe a new approa ch to enhance presence technologies. First we discuss the strong relationship between cognitive processes and emotions and how human physiology is uniquely affected when experiencing each emotion. Then we introduce our prototype Multimodal Affective User Interface. In the remaining of the paper we describe the emotion elicitation experiment we designed ...

Driving a vehicle involves a series of events, which are related to and evolve with the mental state (such as sleepiness, mental load, and stress) of the driver. These states are also identified as causal factors of critical situations that can lead to road accidents and vehicle crashes. These driver impairments need to be detected and predicted in order to reduce critical situations and road a...