Quantitative analysis of pain is extremely difficult, because it is a subjective and individual sensation caused by the potential or existing observable tissue injury. For individuals with major cognitive or communicative impairments, it is necessary to carry out an effective method to quantify pain without self-report. Focusing on using physiological signals of the human body to evaluate pain,...

In the last decade, affordable computing power has become available on platforms intended for low-power, mobile applications. For example, Gumstix Overo products integrate WiFi/Bluetooth connectivity, microSD storage, and 600 MHz Texas Instruments OMAP (Open Multimedia Application Platform) 35xx processors with up to 256 MB of flash memory/SDRAM, offering laptop-like resources and performance i...

This paper presents a comparative study of various trend detection methods developed using fuzzy logic, statistical, and regression techniques. A new method that uses noise rejection fuzzy clustering is also proposed in the paper to enhance the performance of trend detection methodologies. The comparative investigation has produced systematic guidelines for the selection of a proper trend detec...

In many physiological studies, variables of interest are not directly accessible, requiring that they be estimated indirectly from noisy measured signals. Here, we introduce two empirical methods to estimate the true physiological signals from indirectly measured, noisy data. The first method is an extension of Tikhonov regularization to large-scale problems, using a sequential update approach....

The ability to recognize emotion is one of the hallmarks of emotion intelligence. This paper proposed to recognize emotion using physiological signals obtained from multiple subjects. IAPS (International Affective Picture System) images were used to elicit target emotions. Five physiological signals: Blood volume pulse (BVP), Electromyography (EMG), Skin Conductance (SC), Skin Temperature (SKT)...

A modern intensive care unit (ICU) has automated analysis systems that depend on continuous uninterrupted real time monitoring of physiological signals such as electrocardiogram (ECG), arterial blood pressure (ABP), and photo-plethysmogram (PPG). These signals are often corrupted by noise, artifacts, and missing data. We present an automated learning framework for real time reconstruction of co...

This review first gives an overview on the concept of fractal geometry with definitions and explanations of the most fundamental properties of fractal structures and processes like self-similarity, power law scaling relationship, scale invariance, scaling range and fractal dimensions. Having laid down the grounds of the basics in terminology and mathematical formalism, the authors systematicall...

Supervised recognition of emotions from physiological signals has been widely accomplished to measure affective interactions. Less attention is, however, placed upon learning descriptive models to characterize physiological responses. In this work we delve on why and how to learn discriminative, complete and usable descriptive models based on physiological signals from emotion-evocative stimuli...

Physiological sensing offers a unique opportunity for constant, private, effortless interaction between man and machine. Physiological sensors have been used to study health, emotion and activity for decades and now modern sensors and mobile computing devices make it possible to record, analyze and respond to changes in physiological signals in real time mobile situations. This paper presents a...

Current research suggests that using multiple can improve affect detection accuracy. Combining facial expression and physiological signals is one of the most common approaches in multimodal affect detection. Several methods and devices have been proposed for measuring physiological signals with simplicity and have been used widely in affective computing applications. Out of the various approach...