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How to design the biofeedback training for the rehabilitation of PTSD patients? / Bazanova, Olga; Zakharov, Alexander; Larkova, Irina et al.
2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. p. 283-286 (2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2023 - Proceedings).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Harvard
Bazanova, O, Zakharov, A, Larkova, I, Maryanovskaya, T, Melnikov, A, Ermolaeva, S, Nikolenko, E & Shirolapov, I 2023,
How to design the biofeedback training for the rehabilitation of PTSD patients? in
2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2023 - Proceedings. 2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2023 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 283-286, 2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, Новосибирск, Russian Federation,
28.09.2023.
https://doi.org/10.1109/CSGB60362.2023.10329818APA
Bazanova, O., Zakharov, A., Larkova, I., Maryanovskaya, T., Melnikov, A., Ermolaeva, S., Nikolenko, E., & Shirolapov, I. (2023).
How to design the biofeedback training for the rehabilitation of PTSD patients? In
2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2023 - Proceedings (pp. 283-286). (2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2023 - Proceedings). Institute of Electrical and Electronics Engineers Inc..
https://doi.org/10.1109/CSGB60362.2023.10329818Vancouver
Bazanova O, Zakharov A, Larkova I, Maryanovskaya T, Melnikov A, Ermolaeva S et al.
How to design the biofeedback training for the rehabilitation of PTSD patients? In 2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2023. p. 283-286. (2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2023 - Proceedings). doi: 10.1109/CSGB60362.2023.10329818
Author
Bazanova, Olga ; Zakharov, Alexander ; Larkova, Irina et al. /
How to design the biofeedback training for the rehabilitation of PTSD patients?. 2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2023 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 283-286 (2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2023 - Proceedings).
BibTeX
@inproceedings{f8411afabdbd4bf294bddbf7b0775533,
title = "How to design the biofeedback training for the rehabilitation of PTSD patients?",
abstract = "Rationale for this review is the pressing medical and social problem of the posttraumatic stress disorder (PTSD) treatment. It is known that biofeedback technology is one of the most effective methods of treatment and rehabilitation for emotional profile disorders. In order to develop biofeedback aimed to PTSD rehabilitation, we conducted a literature search on this problem. However, it appears that at the moment there is not enough unambiguous data on this type of biofeedback design. The pathogenesis of PTSD is closely related to impaired efficiency of sensorimotor integration (SMI). The effectiveness of therapy for psychosomatic disorders in patients with PTSD can be increased by restoring normal sensorimotor integration. The review examines various autonomic, electrophysiological and postural markers of destroyed sensorimotor integration (SMI) in individuals with PTSD. We have found that the most informative indicators of SMI in norm include: an increase in EEG power in the individually determined high-frequency alpha subrange, a decrease in the speed of body sway and energy demands to maintain a vertical posture, and a decrease in EMG activity of muscles not involved in cognitive or psychomotor performance. We intend to use these indicators in diagnostic purposes and to develop neurofeedback technology for SMI recovery in patients with PTSD.",
keywords = "PTSD, biofeedback, electroencephalography, electromyography, sensorimotor integration, stabilography",
author = "Olga Bazanova and Alexander Zakharov and Irina Larkova and Tatiana Maryanovskaya and Andrey Melnikov and Sargylana Ermolaeva and Ekaterina Nikolenko and Igor Shirolapov",
note = "{\textcopyright} 2023 IEEE.; 2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2023 ; Conference date: 28-09-2023 Through 29-09-2023",
year = "2023",
doi = "10.1109/CSGB60362.2023.10329818",
language = "English",
isbn = "9798350307979",
series = "2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2023 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "283--286",
booktitle = "2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2023 - Proceedings",
address = "United States",
}
RIS
TY - GEN
T1 - How to design the biofeedback training for the rehabilitation of PTSD patients?
AU - Bazanova, Olga
AU - Zakharov, Alexander
AU - Larkova, Irina
AU - Maryanovskaya, Tatiana
AU - Melnikov, Andrey
AU - Ermolaeva, Sargylana
AU - Nikolenko, Ekaterina
AU - Shirolapov, Igor
N1 - © 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Rationale for this review is the pressing medical and social problem of the posttraumatic stress disorder (PTSD) treatment. It is known that biofeedback technology is one of the most effective methods of treatment and rehabilitation for emotional profile disorders. In order to develop biofeedback aimed to PTSD rehabilitation, we conducted a literature search on this problem. However, it appears that at the moment there is not enough unambiguous data on this type of biofeedback design. The pathogenesis of PTSD is closely related to impaired efficiency of sensorimotor integration (SMI). The effectiveness of therapy for psychosomatic disorders in patients with PTSD can be increased by restoring normal sensorimotor integration. The review examines various autonomic, electrophysiological and postural markers of destroyed sensorimotor integration (SMI) in individuals with PTSD. We have found that the most informative indicators of SMI in norm include: an increase in EEG power in the individually determined high-frequency alpha subrange, a decrease in the speed of body sway and energy demands to maintain a vertical posture, and a decrease in EMG activity of muscles not involved in cognitive or psychomotor performance. We intend to use these indicators in diagnostic purposes and to develop neurofeedback technology for SMI recovery in patients with PTSD.
AB - Rationale for this review is the pressing medical and social problem of the posttraumatic stress disorder (PTSD) treatment. It is known that biofeedback technology is one of the most effective methods of treatment and rehabilitation for emotional profile disorders. In order to develop biofeedback aimed to PTSD rehabilitation, we conducted a literature search on this problem. However, it appears that at the moment there is not enough unambiguous data on this type of biofeedback design. The pathogenesis of PTSD is closely related to impaired efficiency of sensorimotor integration (SMI). The effectiveness of therapy for psychosomatic disorders in patients with PTSD can be increased by restoring normal sensorimotor integration. The review examines various autonomic, electrophysiological and postural markers of destroyed sensorimotor integration (SMI) in individuals with PTSD. We have found that the most informative indicators of SMI in norm include: an increase in EEG power in the individually determined high-frequency alpha subrange, a decrease in the speed of body sway and energy demands to maintain a vertical posture, and a decrease in EMG activity of muscles not involved in cognitive or psychomotor performance. We intend to use these indicators in diagnostic purposes and to develop neurofeedback technology for SMI recovery in patients with PTSD.
KW - PTSD
KW - biofeedback
KW - electroencephalography
KW - electromyography
KW - sensorimotor integration
KW - stabilography
UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85180361131&origin=inward&txGid=65f240fe149b03bd83f3816d9e1d60ff
UR - https://www.mendeley.com/catalogue/0dfcd2bb-30ad-37b0-88a3-31776e60f356/
U2 - 10.1109/CSGB60362.2023.10329818
DO - 10.1109/CSGB60362.2023.10329818
M3 - Conference contribution
SN - 9798350307979
T3 - 2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2023 - Proceedings
SP - 283
EP - 286
BT - 2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine, CSGB 2023 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive Science, Genomics and Biomedicine
Y2 - 28 September 2023 through 29 September 2023
ER -
