Covert visual attention decoding from EEG signals is a key challenge in cognitive neuroscience and brain-computer interface applications. Traditional approaches often rely on manual feature extraction and handcrafted pipelines, which limit scalabilit...
The advancement in computing technology, online learning platforms, and pedagogical tools enable educators and learners to connect without temporal and geographical boundaries. The existing deep learning models to predict student performance are eith...
Neural encoding of visual stimuli aims to predict brain responses in the visual cortex to different external inputs. Deep neural networks trained on relatively simple tasks such as image classification have been widely applied in neural encoding stud...
Communication with artificial agents, such as virtual characters and social robots, is becoming more prevalent, making it crucial to understand how their behaviours can best support social interaction. Eye gaze is a key communicative behaviour, as it...
Developments in image captioning technologies played a crucial role in improving the quality of life for individuals with visual impairments, advancing better social inclusivity. Image captioning is the task of representing the visual content of the ...
The challenge of providing independent living for elderly and disabled individuals is a critical societal concern. Accurate human activity recognition (HAR) is core to allow the development of context-aware applications that involve the identificatio...
PURPOSE: Mind wandering (MW), a common cognitive phenomenon marked by a shift of attention away from the task at hand, poses significant challenges in online educational settings. This study aims to advance MW detection by developing a classification...
Mental workload is an interdisciplinary construct that significantly influences human performance, particularly in tasks requiring sustained attention and cognitive processing. Effective mental workload assessment is critical for preventing cognitive...
Motor imagery-based Brain-Computer Interfaces (BCIs) hold transformative potential for individuals with severe motor impairments, yet their clinical deployment remains constrained by the inherent complexity of electroencephalographic (EEG) signal dec...
While delays in human-robot encounters can harm perceptions of competence, they can also enhance engagement and relatability, making timing a crucial factor in the design of robot behaviors for effective human-robot interaction. Previous research has...
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