title: Exercise and cardiac regulation: what can electrocardiographic time series tell us?
abstract: Electrocardiographic (ECG) monitoring allows temporal analysis of cardiac rhythm. We are usually interested in the variability of two components of the ECG: RR interval (a surrogate marker of cardiac interval) and QT interval (the duration of ventricular depolarization/repolarization). Quantification of RR rhythm, called heart rate variability (HRV) analysis, reflects the cardiac influences of the autonomic nervous system. QT variability provides insight regarding the risk of ventricular arrhythmia, and is at least partially independent of HRV. In this review, we consider the analysis of ECG time series during physical exercise. Our objectives were to show the variety of methods that can be used to characterize these time series data and to demonstrate "normal" changes in these characteristics during exercise and recovery. Attaining a comprehensive understanding of cardiac electrical conduction changes during exercise is not straightforward: analysis methods are numerous and results require careful interpretation. However, we recommend that assessment of both HRV and QT properties yields the most valuable information, the utility of which can be appreciated from the viewpoints of the athlete (e.g. providing feedback on the cardiac effects of training), the clinician (assisting in cardiovascular screening and exercise therapy evaluation) and the exercise physiologist (providing data for physiological process modelling).
authors.affiliation: School of Engineering, Swansea University, Swansea, UK. m.j.lewis@swansea.ac.uk
authors.forename: M J
authors.initials: MJ
authors.lastname: Lewis
authors.forename: A L
authors.initials: AL
authors.lastname: Short
mesh_terms: D001341:Autonomic Nervous System / Q000502:physiology; D004562:Electrocardiography; D015444:Exercise / Q000502:physiology*; D006321:Heart / Q000502:physiology*; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008133:Long QT Syndrome; D013997:Time Factors