DocumentCode :
1924416
Title :
The effects of blood glucose changes on frequency-domain measures of HRV signal in type 1 diabetes
Author :
Amanipour, Reza ; Nazeran, Homer ; Reyes, Ivan ; Franco, Mario ; Haltiwanger, Emily
Author_Institution :
Electr. Eng. Dept., Univ. of Texas at El Paso, El Paso, TX, USA
fYear :
2012
fDate :
27-29 Feb. 2012
Firstpage :
50
Lastpage :
54
Abstract :
The analysis of time duration between consecutive R waves of electrocardiogram (ECG) is a standard method to evaluate the variations in heart rate. The physiological literature reveals that blood glucose levels modulate the autonomic nervous system (ANS) activity and heart rate variability (HRV) is representative of the cardiovascular autonomic function. In the research described here, a pilot investigation was carried out to investigate the relationship between HRV signal measures derived from ECG and arterial blood glucose changes in a female subject with type 1 diabetes mellitus (T1DM) subject during normoglycemic and mildly hyperglycemic conditions. A CleveLabs BioCapture wireless device was used to acquire ECG signals from a 160 Kg, 59.6 year old female volunteer with type 1 diabetes. The PhysioToolkit Software was used to extract the HRV signal and the Kubios software package was deployed to perform comprehensive HRV signal analysis. This software has an easy-to-use graphical user interface that displays the HRV signal and provides three options to calculate: Time-domain, Frequency-domain and Nonlinear Dynamics parameters from raw HRV signals. In its Frequency-domain analysis section, it provides frequency bands such as VLF (Hz), LF (Hz), and HF (Hz), with LF/HF as an index that reflects the sympathovagal balance of the ANS. ECG data were acquired for 30 minutes during normoglycemic condition and for another 30 minutes during mildly hyperglycemic conditions, while blood glucose levels were measured manually by the subject using a glucometer every 5 minutes. ECG signal segments of 5 minute durations were then processed to extract HRV signals and these in turn were analyzed to provide frequency-domain measures. The results indicated that blood glucose changes were inversely related to LF/HF. For this dataset, it was observed that mean ± std of the LF/HF decreased from 6.0 ± 1.04 to 0.91 ± 0.17 when blood glucose levels increased from 156- ± 22 mg/dl to 202 ± 29 mg/dl. Further investigation is underway to recruit more diabetic subjects to acquire a large dataset and explore the relationships between different HRV signal parameters and blood glucose changes under different gylcemic conditions in a comprehensive way.
Keywords :
diseases; electrocardiography; frequency-domain analysis; graphical user interfaces; medical signal processing; sugar; time-domain analysis; CleveLabs BioCapture wireless device; ECG data; ECG signal; HRV signal analysis; Kubios software package; PhysioToolkit Software; arterial blood glucose; blood glucose level; diabetic subject; electrocardiogram; female subject; female volunteer; frequency band; frequency-domain measurement; frequency-domain parameter; glucometer; graphical user interface; mildly hyperglycemic condition; nonlinear dynamics parameter; normoglycemic condition; sympathovagal balance; type 1 diabete; type 1 diabetes mellitus subject; Blood; Diabetes; Electrocardiography; Frequency domain analysis; Heart rate variability; Sugar; blood glucose levels; frequency-domain analysis; heart rate variability (HRV); type 1 diabetes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Communications and Computers (CONIELECOMP), 2012 22nd International Conference on
Conference_Location :
Cholula, Puebla
Print_ISBN :
978-1-4577-1326-2
Type :
conf
DOI :
10.1109/CONIELECOMP.2012.6189880
Filename :
6189880
Link To Document :
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