Power Spectral Study of Heart Rate Variability Time Series by the Adaptive Modified Continuous Morlet Wavelet Transform

Abstract

In this paper, a newly developed method referred as adaptive modified continuous Morletwavelet transform has been proposed to improve the energy concentration in the timefrequencydomain. The improvement is achieved by introducing the shape parameter to theMorlet function that is known as modified Morlet function. To make it adaptive, the modifiedMorlet function was optimized by concentration measure based on automatic determinationalgorithm. The proposed method was validated on set of synthetic time series signals likestationary signal and non-stationary signals with fast changing frequency and slow varyingfrequency components of signals. Also, this method is tested on all synthetic signalscontaminated with additive white Gaussian noise with signal to noise ratio (SNR) of 30dB.The results show that the proposed method improves energy concentration in time-frequencydomain compared to standard Morlet wavelet transform, standard Stockwell Transform (STransform),adaptive S-Transform and modified S-Transform. Further, this method has beenused for analysis of heart rate variability (HRV) time series signals for estimating the value ofmean power in VLF (0.004 Hz–0.04 Hz), LF (0.04 Hz–0.15 Hz), HF (0.15 Hz–0.4 Hz) andLF/HF ratio in frequency band of HRV spectrum. For this analysis, two group of healthysubjects, 21 young [10 M self-recorded, 11 (5 M+6 F) Fantansia database, age range 23–32]and 16 elderly [(9 M+ 7 F) Fantansia database, age range 70–82)] are used.

Keywords: Adaptive continuous Morlet wavelet transform, energy concentration, globalmethod, shape parameter

Cite this Article:

R.S. Singh, B.S. Saini, R.K. Sunkaria.Power Spectral Study of Heart RateVariability Time Series by the AdaptiveModified Continuous Morlet WaveletTransform. Research & Reviews:Journal of Medical Science andTechnology. 2017; 6(2): 5–20p.