Effect of heart rate and body position on the complexity of the QRS and T wave in healthy subjects

Abstract

We analysed the effect of heart rate and body position on the complexity of the QRS and T wave quantified by the ratio of 2 nd /1 st eigenvalue from principal component analysis (PCA) (QRS-PCA, T-PCA) . In both positions, the intrasubject variability of QRS-PCA and T-PCA was significantly smaller than the inter-subject variability. IntroductionPrincipal component analysis (PCA) quantifies the complexity of the ECG waves by defining a set of independent forms (components) with decreasing relative value, which can fully describe their shape. Visibly more complex QRS or T waves with irregularities, notches, etc., which are frequently observed in diseased hearts are described by a greater number of independent components, with increasing relative value of the smaller components.Whilst the diagnostic [1-3] and prognostic [4,5] value of PCA of the T wave has been demonstrated, the effect of physiological factors on the QRS and T wave complexity is unknown. The T wave shape or polarity can be influenced by age, sex, heart rate, body position, autonomic activity, respiration, temperature, electrolyte concentration, food and mental activity [6][7][8][9][10]. It is possible that these factors can also affect T wave complexity. We investigated the effect of heart rate and body position on QRS and T wave complexity using an ECG database recorded in healthy subjects. MethodsA digital ECG database was previously recoded for another project in 15 subjects (8 men, 7 women, age 28.6±7.5 years, range 21.5 -49.1 years) with negative medical history, normal physical examination and normal resting 12-lead ECG, who were not taking any medications during the project.Data were acquired after 5 minutes of rest in the supine position. In each subject, a continuous digital 12-lead ECG was recorded for 25 minutes (5 minutes supine → 10 minutes standing → 10 minutes supine) with Mason-Likar electrode positions [11] using a PC-based 12-lead ECG recorder (CardioSoft™, GE Medical Systems, Milwaukee, USA, 500 Hz, 4.88 µV resolution). In each individual, the same protocol was repeated after approximately 1 week at the same time of the day (within±1 hour). The local Ethics Committee approved the study protocol and each subject provided a written consent. Data analysisAll ECG recordings were visually assessed on screen using the CardioSoft™ software programme in order to exclude segments with noise or premature beats. The first 2 minutes and the last 30 seconds of recording in each position were excluded from the study, and 2.5 minutes supine → 7.5 minutes standing → 7.5 minutes supine were analysed. The ECG were preprocessed suppressing power-line interference, electromyogram noise and baseline drift according to our previously published material on Q-onset and T-end delineation [12].QRS detection was performed following the work of Christov [13], then one complex lead was synthesised from the initials 8 leads [14]. The QRS and the T wave boundaries as well as the RR interval were delineated and

ECG biometric analysis in different physiological recording conditions

“…A set of them, in particular the first studies, proposed systems based on the extraction of a set of fiducial temporal and amplitude features from the ECG, from the P-QRS-T [1, 5-7, 10, 11, 16] or only the QRS-T segment [8,23], which is generally a difficult task. To bypass it, more recent approaches compute non fiducial parameters between windowed ECG into single heartbeat signals, needing only the R-peaks detection [13,19,21,22], except in [9,12] where no waveform detection is required.…”

“…Even if it represents an interest from a technological point of view, in [14] the number of leads is equal to 2, in [19] it is equal to 3, in [23] it is equal to 12 and different numbers of leads are compared in [13] (1 and 3), in [12] (1 and 12) and in [1] (1, 6 and 12).…”

“…Nevertheless, heart rate changes have been considered in some papers. In [7], Israel et al studies the effect of anxiety, Batchvarov et al [23] investigates the effect of the body position by comparing fiducial parameters obtained in supine rest and standing positions and non healthy subjects are included in [20] and [22]. Only a few papers deal with exercise.…”

The chemical profile ofFubai Chrysanthemum(Fubaiju) and its mechanism in preventing cataract based on ultrahigh‐performance liquid chromatography coupled with mass spectrometry and network pharmacology

“…PCA is a widespread data dimensionality reduction algorithm that statistically analyses and simplifies data sets [15]. In this study, PCA was conducted on 20 batches of chrysanthemums to observe the differences between Fubaiju and other varieties of chrysanthemums.…”