fNIRS based brain-computer interfaces.

Link – Subject-Specific feature selection for near infrared spectroscopy based brain-computer interfaces. Abstract BACKGROUND AND OBJECTIVE: Brain-computer interfaces (BCIs) enable people to control an external device by analyzing the brain’s neural activity. Functional near-infrared spectroscopy (fNIRS), which is an emerging optical imaging technique, is frequently used in non-invasive BCIs. Determining the subject-specific features is an […]

Mental State Changes during Performing Brain-Computer Interface.

Link – Exploration of User’s Mental State Changes during Performing Brain-Computer Interface. Abstract Substantial developments have been established in the past few years for enhancing the performance of brain-computer interface (BCI) based on steady-state visual evoked potential (SSVEP). The past SSVEP-BCI studies utilized different target frequencies with flashing stimuli in many different applications. However, it […]

BCI Emotion Recognition Using Particle Swarm Optimization

Link – Enhancing BCI-Based Emotion Recognition Using an Improved Particle Swarm Optimization for Feature Selection. Abstract: Electroencephalogram (EEG) signals have been widely used in emotion recognition. However, the current EEG-based emotion recognition has low accuracy of emotion classification, and its real-time application is limited. In order to address these issues, in this paper, we proposed […]

Quantification of anticipation of excitement with EEG.

Link – Quantification of anticipation of excitement with a three-axial model of emotion with EEG. Abstract OBJECTIVES: Multiple facets of human emotion underlie diverse and sparse neural mechanisms. Among the many existing models of emotion, the two-dimensional circumplex model of emotion is an important theory. The use of the circumplex model allows us to model […]

An Augmented-Reality fNIRS-Based Brain-Computer Interface

Link – An Augmented-Reality fNIRS-Based Brain-Computer Interface: A Proof-of-Concept Study. Abstract Augmented reality (AR) enhances the user’s environment by projecting virtual objects into the real world in real-time. Brain-computer interfaces (BCIs) are systems that enable users to control external devices with their brain signals. BCIs can exploit AR technology to interact with the physical and […]

Stability of a chronic implanted brain-computer interface

Link – Stability of a chronic implanted brain-computer interface in late-stage amyotrophic lateral sclerosis. Abstract OBJECTIVE: We investigated the long-term functional stability and home use of a fully implanted electrocorticography (ECoG)-based brain-computer interface (BCI) for communication by an individual with late-stage Amyotrophic Lateral Sclerosis (ALS). METHODS: Data recorded from the cortical surface of the motor […]

Neuroergonomic Assessment of Wheelchair Control Using fNIRS.

Link – Neuroergonomic Assessment of Wheelchair Control Using Mobile fNIRS. Abstract For over two centuries, the wheelchair has been one of the most common assistive devices for individuals with locomotor impairments without many modifications. Wheelchair control is a complex motor task that increases both the physical and cognitive workload. New wheelchair interfaces, including Power Assisted […]

Designing Spatial Filters to Enhance Performance of SSVEP-Based BCIs.

Link – A Training Data-Driven Canonical Correlation Analysis Algorithm for Designing Spatial Filters to Enhance Performance of SSVEP-Based BCIs. Abstract Canonical correlation analysis (CCA) is an effective spatial filtering algorithm widely used in steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs). In existing CCA methods, training data are used for constructing templates of stimulus targets […]

Brain Communication Using fNIRS Responses.

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Link – Brain-Based Binary Communication Using Spatiotemporal Features of fNIRS Responses. Abstract “Locked-in” patients lose their ability to communicate naturally due to motor system dysfunction. Brain-computer interfacing offers a solution for their inability to communicate by enabling motor-independent communication. Straightforward and convenient in-session communication is essential in clinical environments. The present study introduces a functional […]

Recognitionimagined movement with fNIRS

Link – Recognition of three different imagined movement of the right foot based on functional near-infrared spectroscopy Abstract Brain-computer interface (BCI) based on functional near-infrared spectroscopy (fNIRS) is a new-type human-computer interaction technique. To explore the separability of fNIRS signals in different motor imageries on the single limb, the study measured the fNIRS signals of […]