Impulse Classification Network for Video Head Impulse Test

Shokhrukh Baydadaev; Saidrasul Usmankhujaev; Jangwoo Kwon; Kyu Sung Kim

doi:10.1109/EMBC44109.2020.9175969

Impulse Classification Network for Video Head Impulse Test

Shokhrukh Baydadaev, Saidrasul Usmankhujaev, Jangwoo Kwon, Kyu Sung Kim

Inha University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

The vestibulo-ocular reflex (VOR) is a dynamic system of the human brain that helps to maintain balance and to stabilize vision during head movement. The video head impulse test (vHIT) is a clinical test that uses lightweight, high-speed video goggles to examine the VOR function by calculating the ratio of eye-movement to head-movement velocities. The main problem with a patient's vHIT is that data coming from the goggles may have artifacts and other noise. This paper proposes an impulse classification network (ICN) using a one-dimensional convolutional neural network that can detect noisy data and classify human VOR impulses. Our ICN found actual classes of a patient's impulses with 95% accuracy.Clinical Relevance - ICN is a high-performance classification method that works on a patient's vHIT impulse data by identifying abnormalities and artifacts. This method is an advanced clinical decision support system that can help doctors quickly make decisions.

Original language	English
Title of host publication	42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publication	Enabling Innovative Technologies for Global Healthcare, EMBC 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	240-243
Number of pages	4
ISBN (Electronic)	9781728119908
DOIs	https://doi.org/10.1109/EMBC44109.2020.9175969
State	Published - Jul 2020
Event	42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020 - Montreal, Canada Duration: 20 Jul 2020 → 24 Jul 2020

Publication series

Name	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume	2020-July
ISSN (Print)	1557-170X

Conference

Conference	42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020
Country/Territory	Canada
City	Montreal
Period	20/07/20 → 24/07/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

Convolutional Neural Network (CNN)
Impulse Classification Network (ICN)
Superior Semicircular Canal (SSC)
Vestibulo-ocular Reflex (VOR)
Video Head Impulse Test (vHIT)

Access to Document

10.1109/EMBC44109.2020.9175969

Cite this

Baydadaev, S., Usmankhujaev, S., Kwon, J., & Kim, K. S. (2020). Impulse Classification Network for Video Head Impulse Test. In 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020 (pp. 240-243). Article 9175969 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2020-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC44109.2020.9175969

Baydadaev, Shokhrukh ; Usmankhujaev, Saidrasul ; Kwon, Jangwoo et al. / Impulse Classification Network for Video Head Impulse Test. 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 240-243 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS).

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abstract = "The vestibulo-ocular reflex (VOR) is a dynamic system of the human brain that helps to maintain balance and to stabilize vision during head movement. The video head impulse test (vHIT) is a clinical test that uses lightweight, high-speed video goggles to examine the VOR function by calculating the ratio of eye-movement to head-movement velocities. The main problem with a patient's vHIT is that data coming from the goggles may have artifacts and other noise. This paper proposes an impulse classification network (ICN) using a one-dimensional convolutional neural network that can detect noisy data and classify human VOR impulses. Our ICN found actual classes of a patient's impulses with 95% accuracy.Clinical Relevance - ICN is a high-performance classification method that works on a patient's vHIT impulse data by identifying abnormalities and artifacts. This method is an advanced clinical decision support system that can help doctors quickly make decisions.",

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Baydadaev, S, Usmankhujaev, S, Kwon, J & Kim, KS 2020, Impulse Classification Network for Video Head Impulse Test. in 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020., 9175969, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, vol. 2020-July, Institute of Electrical and Electronics Engineers Inc., pp. 240-243, 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020, Montreal, Canada, 20/07/20. https://doi.org/10.1109/EMBC44109.2020.9175969

Impulse Classification Network for Video Head Impulse Test. / Baydadaev, Shokhrukh; Usmankhujaev, Saidrasul; Kwon, Jangwoo et al.
42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020. Institute of Electrical and Electronics Engineers Inc., 2020. p. 240-243 9175969 (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS; Vol. 2020-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Impulse Classification Network for Video Head Impulse Test

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AU - Usmankhujaev, Saidrasul

AU - Kwon, Jangwoo

AU - Kim, Kyu Sung

PY - 2020/7

Y1 - 2020/7

N2 - The vestibulo-ocular reflex (VOR) is a dynamic system of the human brain that helps to maintain balance and to stabilize vision during head movement. The video head impulse test (vHIT) is a clinical test that uses lightweight, high-speed video goggles to examine the VOR function by calculating the ratio of eye-movement to head-movement velocities. The main problem with a patient's vHIT is that data coming from the goggles may have artifacts and other noise. This paper proposes an impulse classification network (ICN) using a one-dimensional convolutional neural network that can detect noisy data and classify human VOR impulses. Our ICN found actual classes of a patient's impulses with 95% accuracy.Clinical Relevance - ICN is a high-performance classification method that works on a patient's vHIT impulse data by identifying abnormalities and artifacts. This method is an advanced clinical decision support system that can help doctors quickly make decisions.

AB - The vestibulo-ocular reflex (VOR) is a dynamic system of the human brain that helps to maintain balance and to stabilize vision during head movement. The video head impulse test (vHIT) is a clinical test that uses lightweight, high-speed video goggles to examine the VOR function by calculating the ratio of eye-movement to head-movement velocities. The main problem with a patient's vHIT is that data coming from the goggles may have artifacts and other noise. This paper proposes an impulse classification network (ICN) using a one-dimensional convolutional neural network that can detect noisy data and classify human VOR impulses. Our ICN found actual classes of a patient's impulses with 95% accuracy.Clinical Relevance - ICN is a high-performance classification method that works on a patient's vHIT impulse data by identifying abnormalities and artifacts. This method is an advanced clinical decision support system that can help doctors quickly make decisions.

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KW - Superior Semicircular Canal (SSC)

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KW - Video Head Impulse Test (vHIT)

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M3 - Conference contribution

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BT - 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society

PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 20 July 2020 through 24 July 2020

ER -

Baydadaev S, Usmankhujaev S, Kwon J , Kim KS. Impulse Classification Network for Video Head Impulse Test. In 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society: Enabling Innovative Technologies for Global Healthcare, EMBC 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 240-243. 9175969. (Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS). doi: 10.1109/EMBC44109.2020.9175969

Impulse Classification Network for Video Head Impulse Test

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

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