Heart Rate Variability and Skin Conductance Analysis in Different Postures using Composite Distance Sample Entropy

In this research paper, the effect of postural change on Heart Rate Variability (HRV) and Skin Conductance Response (SCR) has been explored with the help of Sample Entropy (SE). Conventional SE is sensitive to small signal-length data. SE utilizes a single distance function to measure the distance between matched vector pairs, which made the analysis inconclusive to establish the relation between HRV and SCR. This paper proposes a composite distance sample entropy method for matched vector pairs to remove the sensitivity of small-signal length data. The proposed method utilizes the composite distance function to calculate the distance between two template vectors. To validate the superiority of the proposed method different noise signals of varied length are simulated for sample entropy calculation. For this work, a data set of 70 subjects for HRV and SCR has been recorded in the supine and standing positions. Comparative analysis has been done between the proposed and conventional methods on the self-recorded data set using accuracy, and paired t-tests. The proposed method gives higher accuracy than the conventional SE method, appears to be less sensitive to the length of the signal, and establishes the relation between HRV and SCR in different body postures.