Date of Award


Degree Name

Master of Science


Electrical Engineering


Homer Nazeran


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, an investigation was carried out to investigate the relationship between HRV signal measures derived from ECG and arterial blood glucose changes in five non-diabetic and five diabetic individuals during normoglycemic and mildly hyperglycemic conditions. A CleveLabs BioCapture wireless device was used to acquire ECG signals from ten subjects. 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 mildly hyperglycemic conditions, while blood glucose levels were measured manually by the subject using a glucometer every 10 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 the LF/HF decreased in non-diabetic and diabetic individuals when blood glucose levels increased.




Received from ProQuest

File Size

355 pages

File Format


Rights Holder

Reza M. Amanipour