Impact of Missing RR-interval on Non-Linear HRV Parameters

rate variability (HRV) analysis with and without interpolation were investigated. In this study, randomly selected data (with frequency of 5 samples up to 50) were removed from actual data (taking first 1000 samples) in the MIT-BIH arrhythmia RR interval database of 10 subjects having 1000 sample data points in each set. In all, the tachograms the artefacts are removed first from the 1000 samples. Poincare plot and entropy analysis were executed for the nonlinear HRV parameters, and the absolute relative errors between the data with and without the missing data duration for these parameters including the interpolation were calculated. In this process, the usefulness of reconstruction was considered when there is missed rr-interval, for which several interpolation methods (linear, delete, and zero order interpolation) were used and the best interpolation method having less error in the HRV analysis was chosen. During the work and performing all the interpolation methods, the delete interpolation gives best results for the reconstruction of data while analysing the HRV non-linear parameters.

[1]  S. Pincus Approximate entropy (ApEn) as a complexity measure. , 1995, Chaos.

[2]  John V. Guttag,et al.  Reconstruction of ECG signals in presence of corruption , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[3]  Bradley Efron,et al.  Missing Data, Imputation, and the Bootstrap , 1994 .

[4]  Marimuthu Palaniswami,et al.  Do existing measures of Poincare plot geometry reflect nonlinear features of heart rate variability? , 2001, IEEE Transactions on Biomedical Engineering.

[5]  Lerma Claudia,et al.  Poincaré plot indexes of heart rate variability capture dynamic adaptations after haemodialysis in chronic renal failure patients , 2003 .

[6]  D. Cuesta-Frau,et al.  Characterization of Sample Entropy in the Context of Biomedical Signal Analysis , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[7]  Yong Gyu Lim,et al.  Effect of missing RR-interval data on nonlinear heart rate variability analysis , 2012, Comput. Methods Programs Biomed..

[8]  C. Mailhes,et al.  Lost Sample Recovering of ECG Signals in e-Health Applications , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[9]  Claudia Lerma,et al.  Poincaré plot indexes of heart rate variability capture dynamic adaptations after haemodialysis in chronic renal failure patients. , 2003, Clinical physiology and functional imaging.

[10]  J. Richman,et al.  Physiological time-series analysis using approximate entropy and sample entropy. , 2000, American journal of physiology. Heart and circulatory physiology.