Literature DB >> 18475017

Is 5-minute heart rate variability a useful measure for monitoring the autonomic nervous system of workers?

Kyoung Bok Min1, Jin-Young Min, Domyung Paek, Sung-Il Cho, Mia Son.   

Abstract

Heart rate variability (HRV) is a noninvasive physiological marker used to assess autonomic nervous function and can be recorded over the short or long term. Long-term recording is a good method for assessing mortality and patient prognosis, while short-term measurement is widely used due to practical advantages and reproducibility. However, little is known about whether a short-term assessment reflects the variation in the overall heart rate of workers. This study evaluated the relationship between the 24-hour and 5-minute HRV, which was selected from a 24-hour recording. The study population was 153 male workers at the National Rail Company in Korea, who had their heart rates assessed for 24 hours. In the time and frequency domains, the correlations of the HRV between 24 hours and 5 minutes were calculated for the entire time and limited times (09:00-17:00). We found modest correlations in the time (R = 0.614-0.668) and frequency (R = 0.508-0.817) domains, but the best correlation was for the high-frequency spectra (HF; R = 0.817). Our findings suggest that the short-term HRV remains stable and may be applicable for screening the variation in the heart rate of workers, although not all of the correlations were sufficiently strong.

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Year:  2008        PMID: 18475017     DOI: 10.1536/ihj.49.175

Source DB:  PubMed          Journal:  Int Heart J        ISSN: 1349-2365            Impact factor:   1.862


  16 in total

1.  Reliability of Ultra-Short ECG Indices for Heart Rate Variability.

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2.  Clinical risk model assessment for cardiovascular autonomic dysfunction in the general Chinese population.

Authors:  L Zhang; Z-H Tang; F Zeng; Z Li; L Zhou; Y Li
Journal:  J Endocrinol Invest       Date:  2015-01-03       Impact factor: 4.256

3.  Implications of turbulence slope variations in different approaches.

Authors:  Hung Yi Chen
Journal:  Heart Int       Date:  2011-08-03

4.  Artificial neural network models for prediction of cardiovascular autonomic dysfunction in general Chinese population.

Authors:  Juanmei Liu; Zi-Hui Tang; Fangfang Zeng; Zhongtao Li; Linuo Zhou
Journal:  BMC Med Inform Decis Mak       Date:  2013-07-31       Impact factor: 2.796

5.  Diminished autonomic neurocardiac function in patients with generalized anxiety disorder.

Authors:  Kyungwook Kim; Seul Lee; Jong-Hoon Kim
Journal:  Neuropsychiatr Dis Treat       Date:  2016-12-08       Impact factor: 2.570

6.  Detection of Craving for Gaming in Adolescents with Internet Gaming Disorder Using Multimodal Biosignals.

Authors:  Hodam Kim; Jihyeon Ha; Won-Du Chang; Wanjoo Park; Laehyun Kim; Chang-Hwan Im
Journal:  Sensors (Basel)       Date:  2018-01-01       Impact factor: 3.576

7.  Analysis of a Screening System for Diabetic Cardiovascular Autonomic Neuropathy in China.

Authors:  Ying Xue; Yubao Lv; Zihui Tang; Jingcheng Dong
Journal:  Med Sci Monit       Date:  2017-11-10

8.  Autonomic modulations in patients with bronchial asthma based on short-term heart rate variability.

Authors:  Mohamed F Lutfi
Journal:  Lung India       Date:  2012-07

9.  Comparison of prediction model for cardiovascular autonomic dysfunction using artificial neural network and logistic regression analysis.

Authors:  Zi-Hui Tang; Juanmei Liu; Fangfang Zeng; Zhongtao Li; Xiaoling Yu; Linuo Zhou
Journal:  PLoS One       Date:  2013-08-05       Impact factor: 3.240

10.  A simple Chinese risk score model for screening cardiovascular autonomic neuropathy.

Authors:  Xiaoli Ge; Shu-Ming Pan; Fangfang Zeng; Zi-Hui Tang; Ying-Wei Wang
Journal:  PLoS One       Date:  2014-03-12       Impact factor: 3.240

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