We compared the encoding and decoding performance of several intracortical neural signals—single units, multi-units, and band-limited local field potential (LFP) power—within an eye movement brain-computer interface (BCI) paradigm. We find that broadband high-frequency LFPs exhibit the best performance, and may be an easily obtainable, high-performance signal for BCI applications.

The project reported in this abstract aims to confirm whether a tactile stimulator ”touch– sense glove” is effective for a novel brain-computer interface (BCI) and whether it would improve BCI classification accuracies. We also report that tactile stimuli delivered to fingers could be utilized to evoke event related potential (ERP) responses with an attention modulation. The designed new stimul...

Steady-state visual evoked potential (SSVEP)-brain-computer interface (BCI) has fast input speeds, high accuracy, and a large number of inputs. The problem with SSVEP is the stress caused by flickering stimuli risk developing photosensitivity. In this study, we attempted to reduce flicker high-frequency SSVEP-BCI. addition, measured critical fusion frequency (CFF) at which humans cannot perceiv...

Introduction: Maintaining means of communication is an extremely important issue in occupational therapy for patients with intractable neurological disease. A brain-computer interface (BCI) a device control technology utilizing physiological signals, and eagerly awaited application as aid severe motor dysfunction. As exploratory study the development BCI, we examined accuracy discriminating bra...

Human-computer interface (HCI) has been a growing field of research and development in recent years [1]-[4]. Most of the effort has been dedicated to the design of user-friendly and ergonomic systems by means of innovative interfaces such as voice, vision, and other input/output devices in virtual reality [5]-[15]. Direct brain-computer interface (BCI) adds a new dimension to HCI [16]-[23]. Int...

The Brain Computer Interface (BCI) systems enable unblessed people to operate devices and applications through their mental activities. It is believed that the BCI technology should be a blessing for the unblessed persons who may be suffering from severe neuromuscular disorders. So in this paper, we present a review on the progress of research efforts and then we analyze the challenges in BCI r...

We present results of a classification improvement approach for a code–modulated visual evoked potential (cVEP) based brain– computer interface (BCI) paradigm using four high–frequency flashing stimuli. Previously published research reports presented successful BCI applications of canonical correlation analysis (CCA) to steady–state visual evoked potential (SSVEP) BCIs. Our team already previou...

Mental fatigue is a psychophysical condition with significant adverse effect on daily life, compromising both physical and mental wellness. We are experiencing challenges in this fast-changing environment, problems becoming more prominent. This demands an urgent need to explore effective accurate automated system for timely detection. Therefore, we present systematic review of brain-computer in...

bci is one of the most intriguing technologies among other hci systems, mostly because of its capability of recording brain activities. spelling bcis, which help paralyzed people to maintain communication, are one of the striking topics in the field of bci. in this scientific a spelling bci system with high transfer rate and accuracy that uses ssvep signals is proposed. in addition, we suggeste...

Unsupervised manifold learning for dimensionality reduction has drawn much attention in recent years. This paper applies two manifold learning methods for the first time to feature dimensionality reduction in brain-computer interface (BCI) design, and compares them with principal component analysis (PCA) and supervised PCA that is mathematically equivalent to the common spatial patterns (CSP) m...