Heart rate variability analysis for diagnosis of diabetic peripheral neuropathy

The purpose of this study is to characterize electrocardiogram (ECG) of a diabetic patient having peripheral nerve damage where the hypothesis is to establish ECG as a measure and evaluation of existing measures of diabetic peripheral neuropathy (DPN). Different microvascular and macrovascular diseases (DPN, Retinopathy, Nephropathy, Cardiac autonomic nerve damage, blood vessel damage, and heart diseases) are mutually present in diabetic patients due to uncontrolled high glucose levels for a long period. Uncontrolled high glucose levels for a long period causes cardiovascular dysfunctionality by oxidative stress and inflammation that affects the natural heart rate variation (HRV). Twenty type-2 diabetic patients among them 10 of the subjects are DPN positive (DPN_P) and the other 10 subjects are DPN negative (DPN_N) participated in the research. ECG data of the participants were recorded with a Holter device for 24 hours. ECG data of both classes were characterized using 9 features. Extracted features of ECG are analyzed with a statistical significance method to interpret the information of the uniqueness of DPN positive and negative class. In the analysis, it is observed that the probability of a test statistic between DPN positive and negative class of all features of ECG rejected the null hypothesis at 0.01592% significance level. Through the investigation, the results of this study lend evidence to the validity of the ECG demonstration of DPN positive class and negative class as a new measure of DPN.