A Within-Subject Normal-Mixture Model with Mixed-Effects for Analyzing Heart Rate VariabilityJessica M Ketchum1*, Al M Best2 and Viswanathan Ramakrishnan3
- *Corresponding Author:
- Jessica M. Ketchum
Virginia Commonwealth University
Department of Biostatistics
Director of Statistical Services
VCU-Center for Rehabilitation Science and Engineering, USA
E-mail: [email protected]
Received date: March 19, 2012; Accepted date: April 24, 2012; Published date: April 25, 2012
Citation: Ketchum JM, Best AM, Ramakrishnan V (2012) A Within-Subject Normal-Mixture Model with Mixed-Effects for Analyzing Heart Rate Variability. J Biomet Biostat S7:013.doi:10.4172/2155-6180.S7-013
Copyright: © 2012 Ketchum JM, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data on Heart Rate Variability (HRV) have been used extensively to indirectly assess the autonomic control of the heart. The distributions of HRV measures, such as the RR-interval, are not necessarily normally distributed and current methodology does not typically incorporate this characteristic. In this article, a mixed-effects modeling approach under the assumption of a two-component normal-mixture distribution for the within-subject observations has been proposed. Estimation of the parameters of the model was performed through an application of the EM algorithm, which is different from the traditional EM application for the normal-mixture methods. An application of this method was illustrated and the results from a simulation study were discussed. Differences among other methods were also reviewed.