A New Measure to Quantify the Complexity of Phase Data (Phase_cmp) from Cross-Spectral Analysis

Authors: Banerji A.¹; Yeragani V.K.²

Source: Cardiovascular Engineering: An International Journal, Volume 3, Number 4, December 2003 , pp. 149-154(6)

Publisher: Springer

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Abstract:

Cross-spectral analysis is a very useful technique to study the relationship between two series of data obtained simultaneously in time. This includes beat-to-beat series of heart rate and blood pressure, heart rate and respiration, and heart rate and QT intervals. Cross-spectral analysis yields the transferphase, which indicates the direction of changes between the two variables. This will yield a negative value of when changes in the input signal precede changes in the output. The phase lag between an input and output signal can be above or below zero, where the zero phase is defined as synchrony between the two signals. Many of the previous studies used a simple average of the phase in a particular frequency band to compare different populations and physiological conditions. As a simple average may not indicate the complexity of these changes in phase, in this study, we describe a new, simple, and objective technique to quantify the complexity of phase (Phase_cmp). We performed cross-spectral analysis on time series of beat-to-beat heart rate and QT intervals obtained from the surfaceelectrocardiogram and applied this new measure to quantify the complexity ofphase. We show that the Phase_cmp is significantly lower in children compared to adults and there is a significant decrease of this value, only children during standing posture (p < 0.001). Phase_cmp ratio of standing/supine conditions was significantly higher in adults (p < 0.003). Phase_cmp did not correlate significantly with either the mean or the standard deviation of the phase data. These findings suggest that a higher Phase_cmp may be associated with an increase in cardiac sympathovagal activity. This new measure may yield important information about cardiac autonomic function.

Keywords: cross-spectral analysis; phase; complexity of phase; cardiac; autonomic; age

Document Type: Research article

DOI: http://dx.doi.org/10.1023/B:CARE.0000018829.50391.78

Affiliations: 1: Institute of Bioinformatics and Applied Biotechnology, Bangalore, India 2: Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, Michigan. Professor of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, or Flat No. 103, Embassy Orchid,

Publication date: 2003-12-01