Heart rate variability (HRV) analysis has been performed on ECG-derived data sets for more than 170 years but is currently undergoing a rapid evolution, thanks to the expansion of the human and veterinary medical technology sector. Traditional HRV analysis was initially performed to identify changes in vago-sympathetic balance, while the most recent focus has expanded to include the use of complex computer algorithms, neural networks and machine learning technology to identify cardiac arrhythmias, particularly atrial fibrillation (AF). Some of these techniques have recently been translated for use in the field of equine cardiology, with particular focus on improving the diagnosis of arrhythmias both at rest and during exercise. This review focuses on understanding the basic HRV variables and important factors to consider when collecting data for use in HRV analysis. In addition, the use of HRV analysis for the diagnosis of arrhythmias is discussed from human, small animal and equine perspectives. Finally, the future of HRV analysis is briefly introduced, including an overview of future developments in this rapidly expanding and exciting field.

Background: Little is known about normal heart rate variability (HRV) in horses during exercise. It can be difficult to separate premature beats from normal beat-to-beat variation at higher heart rates. Objectives: The aim was to quantify HRV in healthy horses during a high-speed treadmill-standardized exercise test (HSET) and to compare with the HRV in horses observed to have arrhythmias during exercise. Animals: Thirteen healthy horses (Group H), 30 horses with arrhythmias (Group A), and 11 horses with poor performance but no observed arrhythmias (Group O). Methods: Prospective, observational study. All horses performed a HSET with simultaneous electrocardiograph (ECG) recorded. The ECGs were corrected for artifacts, and arrhythmias noted. Percent instantaneous beat-to-beat cycle length variation (% R-R variation) was calculated, and HRV analyses were performed on trot, canter, and recovery segments. Results: Group H showed between −4.4 and +3.8% R-R variation during trot and between −6.1 and +5.4% R-R variation during the canter phase of the HSET. Group A had significantly larger maximum and 1st percentile R-R shortening and lengthening compared with Group H and Group O during the recovery phase where most arrhythmias were observed. During recovery, a cutoff of 6% maximum % R-R shortening predicted the presence of arrhythmia with 88% sensitivity and 97% specificity and likelihood ratio of 26. Conclusions and Clinical Importance: Healthy horses have little instantaneous R-R variation during exercise. If a cardiac cycle shortens more than 6% from the previous cycle during the recovery phase, this R-R interval is likely to represent an arrhythmic event.