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Multifactor consciousness level assessment of participants with acquired brain injuries employing human–computer interfaces

BACKGROUND: A lack of communication with people suffering from acquired brain injuries may lead to drawing erroneous conclusions regarding the diagnosis or therapy of patients. Information technology and neuroscience make it possible to enhance the diagnostic and rehabilitation process of patients w...

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Autores principales: Czyżewski, Andrzej, Kurowski, Adam, Odya, Piotr, Szczuko, Piotr
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6954635/
https://www.ncbi.nlm.nih.gov/pubmed/31924202
http://dx.doi.org/10.1186/s12938-019-0746-y
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author Czyżewski, Andrzej
Kurowski, Adam
Odya, Piotr
Szczuko, Piotr
author_facet Czyżewski, Andrzej
Kurowski, Adam
Odya, Piotr
Szczuko, Piotr
author_sort Czyżewski, Andrzej
collection PubMed
description BACKGROUND: A lack of communication with people suffering from acquired brain injuries may lead to drawing erroneous conclusions regarding the diagnosis or therapy of patients. Information technology and neuroscience make it possible to enhance the diagnostic and rehabilitation process of patients with traumatic brain injury or post-hypoxia. In this paper, we present a new method for evaluation possibility of communication and the assessment of such patients’ state employing future generation computers extended with advanced human–machine interfaces. METHODS: First, the hearing abilities of 33 participants in the state of coma were evaluated using auditory brainstem response measurements (ABR). Next, a series of interactive computer-based exercise sessions were performed with the therapist’s assistance. Participants’ actions were monitored with an eye-gaze tracking (EGT) device and with an electroencephalogram EEG monitoring headset. The data gathered were processed with the use of data clustering techniques. RESULTS: Analysis showed that the data gathered and the computer-based methods developed for their processing are suitable for evaluating the participants’ responses to stimuli. Parameters obtained from EEG signals and eye-tracker data were correlated with Glasgow Coma Scale (GCS) scores and enabled separation between GCS-related classes. The results show that in the EEG and eye-tracker signals, there are specific consciousness-related states discoverable. We observe them as outliers in diagrams on the decision space generated by the autoencoder. For this reason, the numerical variable that separates particular groups of people with the same GCS is the variance of the distance of points from the cluster center that the autoencoder generates. The higher the GCS score, the greater the variance in most cases. The results proved to be statistically significant in this context. CONCLUSIONS: The results indicate that the method proposed may help to assess the consciousness state of participants in an objective manner.
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spelling pubmed-69546352020-01-14 Multifactor consciousness level assessment of participants with acquired brain injuries employing human–computer interfaces Czyżewski, Andrzej Kurowski, Adam Odya, Piotr Szczuko, Piotr Biomed Eng Online Research BACKGROUND: A lack of communication with people suffering from acquired brain injuries may lead to drawing erroneous conclusions regarding the diagnosis or therapy of patients. Information technology and neuroscience make it possible to enhance the diagnostic and rehabilitation process of patients with traumatic brain injury or post-hypoxia. In this paper, we present a new method for evaluation possibility of communication and the assessment of such patients’ state employing future generation computers extended with advanced human–machine interfaces. METHODS: First, the hearing abilities of 33 participants in the state of coma were evaluated using auditory brainstem response measurements (ABR). Next, a series of interactive computer-based exercise sessions were performed with the therapist’s assistance. Participants’ actions were monitored with an eye-gaze tracking (EGT) device and with an electroencephalogram EEG monitoring headset. The data gathered were processed with the use of data clustering techniques. RESULTS: Analysis showed that the data gathered and the computer-based methods developed for their processing are suitable for evaluating the participants’ responses to stimuli. Parameters obtained from EEG signals and eye-tracker data were correlated with Glasgow Coma Scale (GCS) scores and enabled separation between GCS-related classes. The results show that in the EEG and eye-tracker signals, there are specific consciousness-related states discoverable. We observe them as outliers in diagrams on the decision space generated by the autoencoder. For this reason, the numerical variable that separates particular groups of people with the same GCS is the variance of the distance of points from the cluster center that the autoencoder generates. The higher the GCS score, the greater the variance in most cases. The results proved to be statistically significant in this context. CONCLUSIONS: The results indicate that the method proposed may help to assess the consciousness state of participants in an objective manner. BioMed Central 2020-01-10 /pmc/articles/PMC6954635/ /pubmed/31924202 http://dx.doi.org/10.1186/s12938-019-0746-y Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Czyżewski, Andrzej
Kurowski, Adam
Odya, Piotr
Szczuko, Piotr
Multifactor consciousness level assessment of participants with acquired brain injuries employing human–computer interfaces
title Multifactor consciousness level assessment of participants with acquired brain injuries employing human–computer interfaces
title_full Multifactor consciousness level assessment of participants with acquired brain injuries employing human–computer interfaces
title_fullStr Multifactor consciousness level assessment of participants with acquired brain injuries employing human–computer interfaces
title_full_unstemmed Multifactor consciousness level assessment of participants with acquired brain injuries employing human–computer interfaces
title_short Multifactor consciousness level assessment of participants with acquired brain injuries employing human–computer interfaces
title_sort multifactor consciousness level assessment of participants with acquired brain injuries employing human–computer interfaces
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6954635/
https://www.ncbi.nlm.nih.gov/pubmed/31924202
http://dx.doi.org/10.1186/s12938-019-0746-y
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