Emotion recognition is one of the most important research directions in field brain–computer interface (BCI). However, to conduct electroencephalogram (EEG)-based emotion recognition, there exist difficulties regarding EEG signal processing; moreover, performance classification models this regard restricted. To counter these issues, 2022 World Robot Contest successfully held an affective BCI co...

PURPOSE We set out to determine clinical and EEG features of seizures presenting with falls, epileptic drop attacks and atonia in the video EEG monitoring unit. METHODS We searched the video EEG monitoring reports over a 5-year-period for the terms "drop", "fall" and "atonic". RESULTS Seizures presenting as epileptic drop attacks, falls or atonia were found in 23/1112 (2%) admissions. About...

The possibility to act upon the surrounding environment without using our human nervous system’s efferent pathways enables a new interaction modality that can boost and speed up the human sensor-effector loop. In recent years, brain-computer interface (BCI) research is exploring many applications in different fields: communication, environmental control, robotics and mobility, and neuroprosthet...

In this study, a multiple kernel learning support vector machine algorithm is proposed for the identification of EEG signals including mental and cognitive tasks, which is a key component in EEG-based brain computer interface (BCI) systems. The presented BCI approach included three stages: (1) a pre-processing step was performed to improve the general signal quality of the EEG; (2) the features...

The electroencephalogram (EEG) signal plays a key role in the diagnosis of epilepsy. Substantial data is generated by the EEG recordings of ambulatory recording systems, and detection of epileptic activity requires a time-consuming analysis of the complete length of the EEG time series data by a neurology expert. A variety of automatic epilepsy detection systems have been developed during the l...

This review provides an updated overview of the neurophysiological rationale, basic and clinical research literature, and current methods of practice pertaining to clinical neurofeedback. It is based on documented findings, rational theory, and the research and clinical experience of the authors. While considering general issues of physiology, learning principles, and methodology, it focuses on...

Erroneous behavior usually elicits a distinct pattern in neural waveforms. In particular, inspection of the concurrent recorded electroencephalograms (EEG) typically reveals a negative potential at fronto-central electrodes shortly following a response error (Ne or ERN) as well as an error-awareness-related positivity (Pe). Seemingly, the brain signal contains information about the occurrence o...

Our primary goal was to develop and validate a task that could provide evidence about how humans learn praxis gestures, such as those involving the use of tools. To that end, we created a video-based task in which subjects view a model performing novel, meaningless one-handed actions with kinematics similar to praxis gestures. Subjects then imitated the movements with their right hand. Trials w...