A brain–computer interface (BCI) establishes a direct communication channel between a
brain and an external device. With recent advances in neurotechnology and artificial …

Assessment of the cognitive functions and state of clinical subjects is an important aspect of
e-health care delivery, and in the development of novel human-machine interfaces. A …

EEG signals have been reported to be informative and reliable for emotion recognition in
recent years. However, the inter-subject variability of emotion-related EEG signals still poses …

A brain–computer interface (BCI) enables a user to communicate with a computer directly
using brain signals. The most common noninvasive BCI modality, electroencephalogram …

In this paper, we present a multimodal emotion recognition framework called EmotionMeter
that combines brain waves and eye movements. To increase the feasibility and wearability …

Affecting computing is an artificial intelligence area of study that recognizes, interprets,
processes, and simulates human affects. The user's emotional states can be sensed through …

A brain–computer interface (BCI) enables a user to communicate directly with a computer
using only the central nervous system. An affective BCI (aBCI) monitors and/or regulates the …

Electroencephalogram (EEG) has been widely used in emotion recognition due to its high
temporal resolution and reliability. Since the individual differences of EEG are large, the …

In this paper, we investigate stable patterns of electroencephalogram (EEG) over time for
emotion recognition using a machine learning approach. Up to now, various findings of …

Affective brain-computer interface (aBCI) introduces personal affective factors to human-
computer interaction. The state-of-the-art aBCI tailors its classifier to each individual user to …