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Development of a brain-computer interface for patients in the critical care setting
by
Le, Anh
, Egbebike, Jennifer
, Velazquez, Angela
, Agarwal, Sachin
, Roh, David
, Connolly, E. Sander
, Gonzales, Ian Jerome
, Claassen, Jan
, Eliseyev, Andrey
, Doyle, Kevin
, Park, Soojin
in
Biology and Life Sciences
/ Brain
/ Brain injury
/ Brain mapping
/ Brain research
/ Care and treatment
/ Communication
/ Computer applications
/ Computer programs
/ Consciousness
/ Critical care
/ Critically ill
/ Depersonalization
/ Drafting software
/ Editing
/ EEG
/ Electroencephalography
/ Engineering and Technology
/ Event-related potentials
/ Experiments
/ Frustration
/ Functional magnetic resonance imaging
/ Head injuries
/ Health aspects
/ Health care facilities
/ Human-computer interface
/ Human-machine systems
/ Implants
/ Injuries
/ Intensive care
/ Magnetic resonance
/ Magnetic resonance imaging
/ Medicine and Health Sciences
/ Neuroimaging
/ Neurology
/ Neurosurgery
/ Pain
/ Patients
/ Research and Analysis Methods
/ Sentences
/ Sleep
/ Social Sciences
/ Software
/ Technology application
/ Unconsciousness
/ User interface
/ Visual evoked potentials
/ Visual signals
2021
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Development of a brain-computer interface for patients in the critical care setting
by
Le, Anh
, Egbebike, Jennifer
, Velazquez, Angela
, Agarwal, Sachin
, Roh, David
, Connolly, E. Sander
, Gonzales, Ian Jerome
, Claassen, Jan
, Eliseyev, Andrey
, Doyle, Kevin
, Park, Soojin
in
Biology and Life Sciences
/ Brain
/ Brain injury
/ Brain mapping
/ Brain research
/ Care and treatment
/ Communication
/ Computer applications
/ Computer programs
/ Consciousness
/ Critical care
/ Critically ill
/ Depersonalization
/ Drafting software
/ Editing
/ EEG
/ Electroencephalography
/ Engineering and Technology
/ Event-related potentials
/ Experiments
/ Frustration
/ Functional magnetic resonance imaging
/ Head injuries
/ Health aspects
/ Health care facilities
/ Human-computer interface
/ Human-machine systems
/ Implants
/ Injuries
/ Intensive care
/ Magnetic resonance
/ Magnetic resonance imaging
/ Medicine and Health Sciences
/ Neuroimaging
/ Neurology
/ Neurosurgery
/ Pain
/ Patients
/ Research and Analysis Methods
/ Sentences
/ Sleep
/ Social Sciences
/ Software
/ Technology application
/ Unconsciousness
/ User interface
/ Visual evoked potentials
/ Visual signals
2021
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Development of a brain-computer interface for patients in the critical care setting
by
Le, Anh
, Egbebike, Jennifer
, Velazquez, Angela
, Agarwal, Sachin
, Roh, David
, Connolly, E. Sander
, Gonzales, Ian Jerome
, Claassen, Jan
, Eliseyev, Andrey
, Doyle, Kevin
, Park, Soojin
in
Biology and Life Sciences
/ Brain
/ Brain injury
/ Brain mapping
/ Brain research
/ Care and treatment
/ Communication
/ Computer applications
/ Computer programs
/ Consciousness
/ Critical care
/ Critically ill
/ Depersonalization
/ Drafting software
/ Editing
/ EEG
/ Electroencephalography
/ Engineering and Technology
/ Event-related potentials
/ Experiments
/ Frustration
/ Functional magnetic resonance imaging
/ Head injuries
/ Health aspects
/ Health care facilities
/ Human-computer interface
/ Human-machine systems
/ Implants
/ Injuries
/ Intensive care
/ Magnetic resonance
/ Magnetic resonance imaging
/ Medicine and Health Sciences
/ Neuroimaging
/ Neurology
/ Neurosurgery
/ Pain
/ Patients
/ Research and Analysis Methods
/ Sentences
/ Sleep
/ Social Sciences
/ Software
/ Technology application
/ Unconsciousness
/ User interface
/ Visual evoked potentials
/ Visual signals
2021
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Development of a brain-computer interface for patients in the critical care setting
Journal Article
Development of a brain-computer interface for patients in the critical care setting
2021
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Overview
Behaviorally unresponsive patients in intensive care units (ICU) are unable to consistently and effectively communicate their most fundamental physical needs. Brain-Computer Interface (BCI) technology has been established in the clinical context, but faces challenges in the critical care environment. Contrary to cue-based BCIs, which allow activation only during pre-determined periods of time, self-paced BCI systems empower patients to interact with others at any time. The study aims to develop a self-paced BCI for patients in the intensive care unit.
BCI experiments were conducted in 18 ICU patients and 5 healthy volunteers. The proposed self-paced BCI system analyzes EEG activity from patients while these are asked to control a beeping tone by performing a motor task (i.e., opening and closing a hand). Signal decoding is performed in real time and auditory feedback given via headphones. Performance of the BCI system was judged based on correlation between the optimal and the observed performance.
All 5 healthy volunteers were able to successfully perform the BCI task, compared to chance alone (p<0.001). 5 of 14 (36%) conscious ICU patients were able to perform the BCI task. One of these 5 patients was quadriplegic and controlled the BCI system without any hand movements. None of the 4 unconscious patients were able to perform the BCI task.
More than one third of conscious ICU patients and all healthy volunteers were able to gain control over the self-paced BCI system. The initial 4 unconscious patients were not. Future studies will focus on studying the ability of behaviorally unresponsive patients with cognitive motor dissociation to control the self-paced BCI system.
Publisher
Public Library of Science,Public Library of Science (PLoS)
Subject
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