Study of hypertension among UTM staff using analysis of heart rate variability

The occurrence of hypertension around the globe is showing an alarming figure and calls for a mechanism for its early detection. Heart Rate Variability (HRV) analysis can possibly be used as a tool for detecting hypertension due to its appealing non-invasive and quantitative approach. Various resear...

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Bibliographic Details
Main Author: Abdullah Maamuom, Maya
Format: Thesis
Language:English
Published: 2016
Subjects:
Online Access:http://eprints.utm.my/id/eprint/79368/1/MayaAbdullahMaamuomMFBME2016.pdf
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Summary:The occurrence of hypertension around the globe is showing an alarming figure and calls for a mechanism for its early detection. Heart Rate Variability (HRV) analysis can possibly be used as a tool for detecting hypertension due to its appealing non-invasive and quantitative approach. Various research has been done on finding the relationship between HRV and hypertension and generally hypertension is often being related to a decrease in HRV values. However, the results remain inconsistent across measures of gender, age and many other factors. This research aimed to extract HRV features associated to hypertension and investigate the relationship between HRV and hypertension with focus on academic staff. It was carried out by acquiring ECG data from hypertensive and non-hypertensive subjects and extracting HRV signal. This was followed by extracting five time domain and three frequency domain features from the HRV signal. The HRV features were subsequently analysed using statistical approach namely the ROC test, Mann Whitney-U Test and the Spearman Correlation Coefficient Test. Results from the three test done shown that the parameter normalized low frequency (n.u. LF) value can be used to associate between HRV and hypertension. In conclusion, the hypertensive subjects have higher n.u. LF values as compared to the non-hypertensive subjects. However, the limitation of this study is that the number of subjects is relatively small. Therefore, in future, the analysis may be repeated for a larger database.