Sleep heart rate variability analysis and k-nearest neighbours classification of primary insomnia

The Heart Rate Variability (HRV) of many sleep disorders shows an alteration of the sympathovagal balance of the Autonomous Nervous System (ANS). Primary insomnia refers to the difficulty in initiating or maintaining sleep that is not caused by other illnesses or substances. The HRV of primary insom...

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Main Authors: Abdullah, Haslaile, Penzel, Thomas, Cvetkovic, Dean
Format: Article
Language:English
Published: Penerbit UTHM 2018
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Online Access:http://eprints.utm.my/id/eprint/86397/1/HaslaileAbdullah2018_SleepHeartRateVariabilityAnalysis.pdf
http://eprints.utm.my/id/eprint/86397/
http://dx.doi.org/10.30880/ijie.2018.10.07.007
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Institution: Universiti Teknologi Malaysia
Language: English
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spelling my.utm.863972020-08-31T14:02:46Z http://eprints.utm.my/id/eprint/86397/ Sleep heart rate variability analysis and k-nearest neighbours classification of primary insomnia Abdullah, Haslaile Penzel, Thomas Cvetkovic, Dean TA Engineering (General). Civil engineering (General) The Heart Rate Variability (HRV) of many sleep disorders shows an alteration of the sympathovagal balance of the Autonomous Nervous System (ANS). Primary insomnia refers to the difficulty in initiating or maintaining sleep that is not caused by other illnesses or substances. The HRV of primary insomnia shows inconsistent findings although it is believed to impair the HRV variables. This study compares the HRV changes during different sleep stages and evaluates the k-nearest neighbours (kNN) classifier using the HRV features for primary insomnia classification. The time and frequency HRV variables were extracted from sleep ECG signals of 10 primary insomnia patients and 10 healthy controls during four sleep stages - N1, N2, N3 and REM. The Mann-Whitney U-test was conducted to evaluate the existence of statistical significant differences between the two groups at different sleep stages. The kNN classifier was adapted for the classification tool. Only the LF index of HRV was significantly higher in the primary insomnia patients compared to the healthy subjects. The classification accuracy of kNN was at 75% when both the HRV time and frequency variables were accounted as inputs to the classifier. Penerbit UTHM 2018 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/86397/1/HaslaileAbdullah2018_SleepHeartRateVariabilityAnalysis.pdf Abdullah, Haslaile and Penzel, Thomas and Cvetkovic, Dean (2018) Sleep heart rate variability analysis and k-nearest neighbours classification of primary insomnia. International Journal of Integrated Engineering, 10 (7). pp. 66-75. ISSN 2229-838X http://dx.doi.org/10.30880/ijie.2018.10.07.007 DOI:10.30880/ijie.2018.10.07.007
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Abdullah, Haslaile
Penzel, Thomas
Cvetkovic, Dean
Sleep heart rate variability analysis and k-nearest neighbours classification of primary insomnia
description The Heart Rate Variability (HRV) of many sleep disorders shows an alteration of the sympathovagal balance of the Autonomous Nervous System (ANS). Primary insomnia refers to the difficulty in initiating or maintaining sleep that is not caused by other illnesses or substances. The HRV of primary insomnia shows inconsistent findings although it is believed to impair the HRV variables. This study compares the HRV changes during different sleep stages and evaluates the k-nearest neighbours (kNN) classifier using the HRV features for primary insomnia classification. The time and frequency HRV variables were extracted from sleep ECG signals of 10 primary insomnia patients and 10 healthy controls during four sleep stages - N1, N2, N3 and REM. The Mann-Whitney U-test was conducted to evaluate the existence of statistical significant differences between the two groups at different sleep stages. The kNN classifier was adapted for the classification tool. Only the LF index of HRV was significantly higher in the primary insomnia patients compared to the healthy subjects. The classification accuracy of kNN was at 75% when both the HRV time and frequency variables were accounted as inputs to the classifier.
format Article
author Abdullah, Haslaile
Penzel, Thomas
Cvetkovic, Dean
author_facet Abdullah, Haslaile
Penzel, Thomas
Cvetkovic, Dean
author_sort Abdullah, Haslaile
title Sleep heart rate variability analysis and k-nearest neighbours classification of primary insomnia
title_short Sleep heart rate variability analysis and k-nearest neighbours classification of primary insomnia
title_full Sleep heart rate variability analysis and k-nearest neighbours classification of primary insomnia
title_fullStr Sleep heart rate variability analysis and k-nearest neighbours classification of primary insomnia
title_full_unstemmed Sleep heart rate variability analysis and k-nearest neighbours classification of primary insomnia
title_sort sleep heart rate variability analysis and k-nearest neighbours classification of primary insomnia
publisher Penerbit UTHM
publishDate 2018
url http://eprints.utm.my/id/eprint/86397/1/HaslaileAbdullah2018_SleepHeartRateVariabilityAnalysis.pdf
http://eprints.utm.my/id/eprint/86397/
http://dx.doi.org/10.30880/ijie.2018.10.07.007
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