Respiratory sigh associated transient autonomic changes detected with a continuous wavelet method of heart rate variability analysis. (September 2017)

• Record Type: Journal Article
• Authors: Kerut, Edmund K.; Swan, Kevin W.; To, Filip; Giles, Thomas D.; Kadowitz, Philip J.
• Is Part Of: Biomedical signal processing and control. Volume 38(2017)
• Page Start: 143
• Page End: 147
• Publication Date: 2017-09
• Subjects: ANS Autonomic nervous system -- BP Blood pressure -- CWT Continuous wavelet transform -- DC Direct current -- EF Ejection fraction -- EKG Electrocardiogram -- HF High frequency -- HR Heart rate -- HRV Heart rate variability -- LF Low frequency -- LV Left ventricle -- FFT Fast Fourier transform -- PNS Parasympathetic nervous system -- RR R to R interval on EKG -- STFT Short time Fourier transform -- SNS Sympathetic nervous system; Wavelet -- Rat -- Autonomic; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2017.05.005
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: A Morlet CWT transform algorithm for analysis of HRV was written. Nonstationary signals may be analyzed and transients in autonomic tone may be detected. A rat model with EKG and respirations with intermittent sighs recordings was analyzed. Transients in sympathetic and parasympathetic tone associated with sighs was noted. This algorithm may be useful to evaluate diseases associated with autonomic transients. Abstract: The measure of heart rate variability (HRV) from an EKG recording is a non-invasive way to evaluate autonomic nervous system (ANS) activity. Traditional methods use either nonparametric (Fourier techniques) or parametric (autoregressive) algorithms. These methods have poor temporal resolution of signal transients and require a stationary signal for accurate evaluation. The short time Fourier transform (STFT) has been used as an attempt to overcome this problem, but still a transient may be poorly localized to time and "blurred" within the signal. We present a Morlet continuous wavelet transform (CWT) algorithm for HRV analysis. A rat model was used of normal respirations with intermittent sighs. Both EKG and respiratory recordings were made. RR interval files were detrended and resampled at 10 Hz using a cubic spline algorithm. Wavelet scales were generated and converted to frequency bands corresponding to sympathetic (SNS) and parasympathetic (PNS) activity. A transient burst in mostly SNS but also PNS activity was noted leading up to a respiratory sigh. To our knowledge, this is the first time brief changes in ANS activity have been detected in association with a respiratory sigh. As demonstrated by this study, this method of HRV analysis may a useful method of investigating transient changes in ANS activity.