Brain Computer Interfaces

Last updated on 2022-09-07

BCI devices are gaining more and more popularity because of the exciting potential they hold. The non-invasive nature of our fNIRS systems in combination with being easy to set up, makes them a great brain imaging modality for use in BCI applications.

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Assessment of Brain Cortical Activation in Passive Movement During Wrist Task Using Functional Near Infrared Spectroscopy (fNIRS)

Purpose: Nowadays, the number of people diagnosed with movement disorders is increasing. Therefore, the evaluation of brain activity …
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Quantifying mental workload of operators performing n-back working memory task: Toward fNIRS based passive BCI system

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Study protocol of a randomised controlled trial of the effects of near-infrared spectroscopy neurofeedback training coupled with virtual reality technology in children with ADHD

Background The rise in the number of children diagnosed with attention-deficit/hyperactivity disorder (ADHD) highlights the need for …
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The Power of Fear: Exploring the Neural Responses to Horror Scenes in Different Audiovisual Modes

Neurocinematics is an emerging interdisciplinary field at the intersection between Human-Computer Interaction, Brain-Computer …
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Perceived Mental Workload Classification Using Intermediate Fusion Multimodal Deep Learning

A lot of research has been done on the detection of mental workload (MWL) using various bio-signals. Recently, deep learning has …
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Feeling Positive? Predicting Emotional Image Similarity from Brain Signals

The present notion of visual similarity is based on features derived from image contents. This ignores the users' emotional or …
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Crowdsourcing Affective Annotations via fNIRS-BCI

Affective annotation refers to the process of labeling media content based on the emotions they evoke. Since such experiences are …
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Fugl-Meyer hand motor imagination recognition for brain–computer interfaces using only fNIRS

As a relatively new physiological signal of brain, functional near-infrared spectroscopy (fNIRS) is being used more and more in …
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Perceived Mental Workload Classification Using Intermediate Fusion Multimodal Deep Learning

A lot of research has been done on the detection of mental workload (MWL) using various bio-signals. Recently, deep learning has …
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DESIGN AND EVALUATION OF A GUI FOR SIGNAL AND DATA ANALYSIS OF MOBILE FUNCTIONAL NEAR-INFRARED SPECTROSCOPY SYSTEMS A Thesis by

Functional near-infrared spectroscopy (fNIRS) is an emerging neuro-imaging modality that can indicate cortical functionality with good …
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Self-health monitoring and wearable neurotechnologies

Brain-computer interfaces and wearable neurotechnologies are now used to measure real-time neural and physiologic signals from the …
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FNIRS and neurocinematics

In the overlap between Human-Computer Interaction (HCI) and Cinematics, sits an interest in physiological responses to experiences. …
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Classification of overt and covert speech for near-infrared spectroscopy-based brain computer interface

People suffering from neuromuscular disorders such as locked-in syndrome (LIS) are left in a paralyzed state with preserved awareness …
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Using noninvasive methods to drive brain-computer interface (BCI): The role of electroencephalography and functional near-infrared spectroscopy in BCI

The success of brain-computer interfaces (BCI) systems is largely dependent on the ability to record and interpret clear …
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The investigation of brain-computer interface for motor imagery and execution using functional near-infrared spectroscopy

Functional near-infrared spectroscopy (fNIRS), which can measure cortex hemoglobin activity, has been widely adopted in brain-computer …
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A novel semi-immersive virtual reality visuo-motor task activates ventrolateral prefrontal cortex: A functional near-infrared spectroscopy study

Objective. In the last few years, the interest in applying virtual reality systems for neurorehabilitation is increasing. Their …
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Investigating deep learning for fNIRS based BCI

Functional Near infrared Spectroscopy (fNIRS) is a relatively young modality for measuring brain activity which has recently shown …
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A hybrid EEG-fNIRS BCI: Motor imagery for EEG and mental arithmetic for fNIRS

In this paper, we have combined electroencephalography (EEG) and functional near-infrared spectroscopy (fNRIS) to make a hybrid …
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Continuous affective states recognition using functional near infrared spectroscopy

Monitoring the affective states of a person can be highly relevant for numerous disciplines, including adaptive user interfaces, …
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Preserved foot motor cortex in patients with complete spinal cord injury: A functional near-infrared spectroscopic study

Background. Since the brain is intact, persons with a spinal cord injury (SCI) might benefit from a brain-computer interface (BCI) to …
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Singular spectrum analysis as a preprocessing filtering step for fNIRS brain computer interfaces

Near Infrared Spectroscopy is a method that measures the brain’s haemodynamic response. It is of interest in brain-computer …
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Classification of mental tasks in the prefrontal cortex using fNIRS

Functional near infrared spectroscopy (fNIRS) is rapidly gaining interest in both the Neuroscience, as well as the …
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Towards Biometric Person Identification using fNIRS

We investigate the potential of using fNIRS signals for biometric person identification. Independent sessions for training and testing …
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