Abstract
Background: The time variation between consecutive heartbeats is commonly referred to as heart rate variability (HRV). Loss of complexity in HRV has been documented in several cardiovascular diseases and has been associated with an increase in morbidity and mortality. However, the mechanisms that control HRV are not well understood. Animal experiments are the key to investigating this question. However, to date, there are no standard open source tools for HRV analysis of mammalian electrocardiogram (ECG) data and no centralized public databases for researchers to access.Methods: We created an open source software solution specifically designed for HRV analysis from ECG data of multiple mammals, including humans. We also created a set of public databases of mammalian ECG signals (dog, rabbit and mouse) with manually corrected R-peaks (>170,000 annotations) and signal quality annotations. The platform (software and databases) is called PhysioZoo.Results: PhysioZoo makes it possible to load ECG data and perform very accurate R-peak detection (F1 > 98%). It also allows the user to manually correct the R-peak locations and annotate low signal quality of the underlying ECG. PhysioZoo implements state of the art HRV measures adapted for different mammals (dogs, rabbits, and mice) and allows easy export of all computed measures together with standard data representation figures. PhysioZoo provides databases and standard ranges for all HRV measures computed on healthy, conscious humans, dogs, rabbits, and mice at rest. Study of these measures across different mammals can provide new insights into the complexity of heart rate dynamics across species.Conclusion: PhysioZoo enables the standardization and reproducibility of HRV analysis in mammalian models through its open source code, freely available software, and open access databases. PhysioZoo will support and enable new investigations in mammalian HRV research. The source code and software are available on www.physiozoo.com.
Highlights
Over the past few decades, numerous studies have explored the variation of the time interval between heartbeats, known as heart rate variability (HRV)
Human ECG data were obtained from the public MITBIH Normal Sinus Rhythm (MIT-normal sinus rhythm (NSR)) database (Goldberger et al, 2000)
The “Human” column corresponds to the bands we found for humans
Summary
Over the past few decades, numerous studies have explored the variation of the time interval between heartbeats, known as HRV. In recent years interest in HRV analysis has increased due to (i) the existence of large, publicly available biosignal databases [e.g., the Research Resource for Complex Physiologic Signals, or PhysioNet (Goldberger et al, 2000)], or similar private counterparts; (ii) the development of more advanced digital signal processing algorithms for exploiting the physiological content of the beat-to-beat interval time series; and (iii) the availability of affordable, wearable medical devices and implantable telemetry devices from which continuous heart rate time series can be obtained Despite these encouraging studies, the mechanisms that control HRV are not yet well understood, and the use of HRV analysis has remained limited in medical practice. To date, there are no standard open source tools for HRV analysis of mammalian electrocardiogram (ECG) data and no centralized public databases for researchers to access
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