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Applications and Methods of Brain-Computer Interface Technology in Health and Wellness

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensing and Imaging".

Deadline for manuscript submissions: closed (20 January 2023) | Viewed by 2368

Special Issue Editors


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Guest Editor
Institute of Cognitive Science, University of Colorado, Boulder, CO 80309, USA
Interests: human-computer interaction; functional near-infrared spectroscopy; physiological computing

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Guest Editor
Institute of Cognitive Science, University of Colorado, Boulder, CO 80309, USA
Interests: social media account

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Guest Editor
College of Health and Human Sciences, Colorado State University, Fort Collins, CO 80523, USA
Interests: functional near-infrared spectroscopy; electroencephalography; functional magnetic resonance imaging; traumatic brain injury

Special Issue Information

With recent advancements in biotechnology, we are seeing a wave of brain-computer interface (BCI) technologies that are capable of non-invasively measuring a range of health and wellness phenomena in humans, and using that information to help support the individual to improve overall health.  With these emerging BCI sensor technologies, not only can we measure and investigate the neural mechanisms underlying important health and wellness phenomena (e.g., stress, chronic pain, addiction, traumatic brain injury) in the brain, but we can develop techniques to promote wellness across a broad range of applications. The BCI field has made rapid advancements in recent years, with sensing technologies such as functional near-infrared spectroscopy (fNIRS), electroencephalography (EEG), magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI), all contributing to sensing and measurement of the human brain.   For example: BCIs have been used to develop biofeedback systems that help people with chronic pain learn to self-regulate and divert attention away from the pain. Similar bio-feedback BCIs have been succesful in topics such as druEXPAND with a few lines that connect to our own work and interests. As another example, BCIs have recently been used to study the benefits of practicing mindfulness in the brain, whereby positive impacts are measured non-invasively to improve emotion regulation and attentional processing through mindfulness based-stress reduction (MBSR). This special issue is focused on empirical studies, methods, and applications of BCI technologies to benefit general health and wellness.

Dr. Leanne Hirshfield
Dr. Marta Ceko
Dr. Jaclyn Stephens
Guest Editors

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Keywords

  • mindfulness based stress reduction (MBSR)
  • functional near-infrared spectroscopy
  • functional magnetic resonance imaging (fMRI)
  • Brain-computer interfaces
  • chronic pain management
  • traumatic brain injury
  • occupational therapy
  • concussion

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Published Papers (1 paper)

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Research

14 pages, 2178 KiB  
Article
Effect of Stimulus Size in a Visual ERP-Based BCI under RSVP
by Álvaro Fernández-Rodríguez, Aube Darves-Bornoz, Francisco Velasco-Álvarez and Ricardo Ron-Angevin
Sensors 2022, 22(23), 9505; https://doi.org/10.3390/s22239505 - 5 Dec 2022
Cited by 8 | Viewed by 2002
Abstract
Rapid serial visual presentation (RSVP) is currently one of the most suitable paradigms for use with a visual brain–computer interface based on event-related potentials (ERP-BCI) by patients with a lack of ocular motility. However, gaze-independent paradigms have not been studied as closely as [...] Read more.
Rapid serial visual presentation (RSVP) is currently one of the most suitable paradigms for use with a visual brain–computer interface based on event-related potentials (ERP-BCI) by patients with a lack of ocular motility. However, gaze-independent paradigms have not been studied as closely as gaze-dependent ones, and variables such as the sizes of the stimuli presented have not yet been explored under RSVP. Hence, the aim of the present work is to assess whether stimulus size has an impact on ERP-BCI performance under the RSVP paradigm. Twelve participants tested the ERP-BCI under RSVP using three different stimulus sizes: small (0.1 × 0.1 cm), medium (1.9 × 1.8 cm), and large (20.05 × 19.9 cm) at 60 cm. The results showed significant differences in accuracy between the conditions; the larger the stimulus, the better the accuracy obtained. It was also shown that these differences were not due to incorrect perception of the stimuli since there was no effect from the size in a perceptual discrimination task. The present work therefore shows that stimulus size has an impact on the performance of an ERP-BCI under RSVP. This finding should be considered by future ERP-BCI proposals aimed at users who need gaze-independent systems. Full article
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