Novel Sensing Technologies and Artificial Intelligence for Human–Computer Interaction

Dear Colleagues,

Two technological developments are offering new possibilities for people to interact with computing devices. On the one hand, there has been a rapid growth in new sensing technologies. The new generation of sensors is small and can be integrated into a variety of interactive devices, from mobile phones to extended reality systems (such as virtual and augmented reality head-mounted displays). In addition, despite their smaller size, these sensors can capture more varieties of data with high precision. For example, we can now capture hand and body motions and different types of physiological data, including heart rate, eye gaze, respiration, and brain activity, in a non-invasible and unobtrusive way. These data can be measured, manipulated, and, to some extent, interpreted using AI-based approaches.

On the other hand, advances in artificial intelligence, particularly from the subfields of machine learning and deep learning, are helping to make interactions more refined and adapted to the needs of single users or groups of users. Machine learning techniques allow computing devices to learn from and adapt to new data captured via sensors without direct intervention from users. Deep learning techniques enable this automatic learning by absorbing vast amounts of unstructured data such as text, images, or video, which new sensing technologies capture and feed into these AI-based algorithms.

This Special Issue aims to bring state-of-the-art developments that integrate novel sensing technologies with artificial intelligence for augmenting the interaction between people and interactive devices around them.

Prof. Dr. Hai-Ning Liang
Prof. Dr. Maurizio Caon
Guest Editors

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