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 m...