Why should researchers measure psychophysiological processes repeatedly over time?
The study of psychophysiology inherently involves sampling biological processes as they …

Traditional machine learning classifiers can automatically evaluate human behaviour and
emotion recognition tasks. However, prior research work does not secure users' privacy and …

Emotions significantly shape decision-making, and targeted emotional elicitations represent
an important factor in neuromarketing, where they impact advertising effectiveness by …

Background: Decoding emotions from brain maps is a challenging task. Convolutional
Neural Network (CNN) is commonly used for EEG feature map. However, due to its local …

Emotions play an essential role in human life as they are linked to well-being and markers of
various diseases. Physiological signals can be used to assess emotions objectively and …

The prediction of personality traits offers valuable insights into human behaviour, more
specifically in psychology, healthcare, and social science. In this paper, we present a novel …

Abstract System identification of dynamical systems aims to predict the output of a system for
a given input by inferring model details from data. This is particularly challenging for …

Emotion is one of the main psychological factors that affect human behaviour. Using a
neural network model trained with Electroencephalography (EEG)-based frequency features …

Physiological signal analysis has gained a lot of interest in recent years and has been used
in a variety of fields including emotion recognition, activity recognition, and health …

Identifying emotional responses in products is essential for product design and user
research. Traditional methods, such as interviews and surveys, for gathering product …