A Framework for Psychophysiological Classification within a Cultural Heritage Context Using Interest

This article presents a psychophysiological construct of interest as a knowledge emotion and illustrates the importance of interest detection in a cultural heritage context. The objective of this work is to measure and classify psychophysiological reactivity in response to cultural heritage material presented as visual and audio. We present a data processing and classification framework for the classification of interest. Two studies are reported, adopting a subject-dependent approach to classify psychophysiological signals using mobile physiological sensors and the support vector machine learning algorithm. The results show that it is possible to reliably infer a state of interest from cultural heritage material using psychophysiological feature data and a machine learning approach, informing future work for the development of a real-time physiological computing system for use within an adaptive cultural heritage experience designed to adapt the provision of information to sustain the interest of the visitor

The NeuroDante Project: Neurometric measurements of participant’s reaction to literary auditory stimuli from dante’s “divina commedia”

Neurodante. Progetto di analisi neurometrica di alcuni brani della Commedi

Anger-based BCI Using fNIRS Neurofeedback

Functional near-infrared spectroscopy (fNIRS) holds increasing potential for Brain-Computer Interfaces (BCI) due to its portability, ease of application, robustness to movement artifacts, and relatively low cost. The use of fNIRS to support the development of affective BCI has received comparatively less attention, despite the role played by the prefrontal cortex in affective control, and the appropriateness of fNIRS to measure prefrontal activity. We present an active, fNIRS-based neurofeedback (NF) interface, which uses differential changes in oxygenation between the left and right sides of the dorsolateral prefrontal cortex to operationalize BCI input. The system is activated by users generating a state of anger, which has been previously linked to increased left prefrontal asymmetry. We have incorporated this NF interface into an experimental platform adapted from a virtual 3D narrative, in which users can express anger at a virtual character perceived as evil, causing the character to disappear progressively. Eleven subjects used the system and were able to successfully perform NF despite minimal training. Extensive analysis confirms that success was associated with the intent to express anger. This has positive implications for the design of affective BCI based on prefrontal asymmetry

User experience in cross-cultural contexts

This dissertation discusses how interdisciplinary UX teams can consider culturally sensitive design elements during the UX design process. It contributes a state-of-the-art meta review on UX evaluation methods, two software tool artifacts for cross-functional UX teams, and empirical insights in the differing usage behaviors of a website plug-in of French, German and Italian users, website design preferences of Vietnamese and German users, as well as learnings from a field trip that focused on studying privacy and personalization in Mumbai, India. Finally, based on these empirical insights, this work introduces the concept culturally sensitive design that goes beyond traditional cross-cultural design considerations in HCI that do not compare different approaches to consider culturally sensitive product aspects in user research