Methods Inf Med 2016; 55(03): 250-257
DOI: 10.3414/ME15-01-0088
Original Articles
Schattauer GmbH

Comparison of Pulse Rate Variability and Heart Rate Variability for Hypoglycemia Syndrome

Şükrü Okkesim
1   Fatih University, Institute of Biomedical Engineering, Istanbul, Turkey
,
Gamze Çelik
1   Fatih University, Institute of Biomedical Engineering, Istanbul, Turkey
,
Mustafa S. Yıldırım
1   Fatih University, Institute of Biomedical Engineering, Istanbul, Turkey
,
Mahmut M. Ilhan
2   Bezmialem Vakif University, Faculty of Medicine, Department of Endocrinology and Metabolism Diseases, Istanbul, Turkey
,
Özcan Karaman
2   Bezmialem Vakif University, Faculty of Medicine, Department of Endocrinology and Metabolism Diseases, Istanbul, Turkey
,
Ertuğrul Taşan
2   Bezmialem Vakif University, Faculty of Medicine, Department of Endocrinology and Metabolism Diseases, Istanbul, Turkey
,
Sadık Kara
1   Fatih University, Institute of Biomedical Engineering, Istanbul, Turkey
› Author Affiliations
Further Information

Publication History

received: 19 July 2015

accepted: 01 February 2016

Publication Date:
08 January 2018 (online)

Preview

Summary

Background: Heart rate variability (HRV) is a signal obtained from RR intervals of electro -cardiography (ECG) signals to evaluate the balance between the sympathetic nervous system and the parasympathetic nervous system; not only HRV but also pulse rate va -riability (PRV) extracted from finger pulse plethysmography (PPG) can reflect irregularities that may occur in heart rate and control procedures.

Objectives: The purpose of this study is to compare the HRV and PRV during hypogly -cemia in order to evaluate the features that computed from PRV that can be used in detection of hypoglycemia.

Methods: To this end, PRV and HRV of 10 patients who required testing with insulininduced hypoglycemia (IIHT) in Clinics of Endocrinology and Metabolism Diseases of Bezm-i Alem University (Istanbul, Turkey), were obtained. The recordings were done at three stages: prior to IIHT, during the IIHT, and after the IIHT. We used Bland-Altman analysis for comparing the parameters and to evaluate the correlation between HRV and PRV if exists.

Results: Significant correlation (r > 0.90, p < 0.05) and close agreement were found between HRV and PRV for mean intervals, the root-mean square of the difference of successive intervals, standard deviation of successive intervals and the ratio of the low-to-high frequency power.

Conclusions: In conclusion, all the features computed from PRV and HRV have close agreement and correlation according to Bland-Altman analyses’ results and features computed from PRV can be used in detection of hypoglycemia.