Brain-Computer Interface (BCI) systems have become one of the valuable research area of ML (Machine Learning) and AI based techniques have brought significant change in traditional diagnostic systems of medical diagnosis. Specially; Electroencephalogram (EEG), which is measured electrical activity of the brain and ionic current in neurons is result of these activities. A brain-computer interfac...

Brain-computer interface (BCI) systems must process neural signals with consistent timing in order to support adequate system performance. Thus, it is important to have the capability to determine whether a particular BCI configuration (i.e., hardware and software) provides adequate timing performance for a particular experiment. This report presents a method of measuring and quantifying differ...

Abstract The recovery of hand motor function can effectively improve the living standard stroke patients and relieve their psychological anxiety. Traditional physical rehabilitation training is unable to target cause loss; therefore, effect not ideal. objective this study propose a system combining brain–computer interface (BCI), soft glove virtual reality (VR), explore its effectiveness on mov...

Brain-computer interface (BCI) is combination of hardware and software systems that allows the severely or partially disabled persons to communicate with their surroundings. The study of brain activities precisely is an important step in BCI system. Many invasive and non-invasive neuro-imaging techniques are being conducted. In this paper, a comparative analysis of these different approaches ha...

Brain-computer interface (BCI) technology can offer individuals with severe motor disabilities greater independence and a higher quality of life. The BCI systems take recorded brain signals and translate them into real-time actions, for improved communication, movement, or perception. Four patient participants with a clinical need for intracranial electrocorticography (ECoG) participated in thi...

Affective annotation refers to the process of labeling media content based on emotions they evoke. Since such experiences are inherently subjective and depend individual differences, central challenge is associating digital with its affective, interindividual experience. Here, we present a first-of-its-kind methodology for affective directly from brain signals by monitoring experience crowd ind...

this paper describes the system design of a portable and economical mu rhythm based brain computer interface which employs cypress semiconductors programmable system on chip (psoc). by carrying out essential processing on the psoc, the use of an extra computer is eliminated, resulting in considerable cost savings. microsoft visual studio 2005 and psoc designer 5.01 are employed in developing th...

This paper is aimed to introduce IDIAP Brain Computer Interface (IBCI) research that successfully applied Ambience Intelligence (AmI) principles in designing intelligent brain-machine interactions. We proceed through IBCI applications describing how machines can decode and react to the human mental commands, cognitive and emotive states. We show how effective human-machine interaction for brain...