PhysioZoo: A Novel Open Access Platform for Heart Rate Variability Analysis of Mammalian Electrocardiographic Data

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 (F ₁ > 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.

Keywords: R-peak detection; animal models; electrocardiography; heart rate variability; power law.

FIGURE 1

Representative example of the R-peaks detected using gqrs (left) and rqrs (right) on the same 2 s segment. (A) R-peaks detected by gqrs (state-of-the-art human R-peak detector). This figure illustrates the need for mammal-specific R-peak detectors to ensure accuracy. (B) R-peaks detected by rqrs (i.e., adapted for working with mammalian data).

FIGURE 2

Example of power spectral estimation using an AR model and the Welch method. The three modes corresponding to the VLF, LF, and HF bands are illustrated. AR coefficients: n = 20 for the (A) human, (B) dog, and (C) rabbit examples and n = 30 for (D) the mouse example.

FIGURE 3

Example of power spectral estimation of a 3 min mouse RR time series before (yellow) and after (blue) atropine injection. The figure shows that the characteristic vagal peak in the mouse-specific HF band is eliminated with atropine. Some of the power in the LF band is also reduced with atropine.

FIGURE 4

PhysioZoo R-peak detection user interface. (A) Record panel. The mammal type dropdown menu is used to load the mammal-specific R-peak detector parameters. Detected R-peaks can be manually corrected using the “Manual annotations” option. Signal quality annotations can be performed. (B) Display of the ECG signal (in mV) with the detected R-peaks (red crosses) and RR interval time series. The boxes on the ECG signal highlight a segment labeled as bad quality by the annotator. (C) Statistics on R-peak detection and quality annotations.

FIGURE 5

PhysioZoo HRV user interface. (A) “Main” tab for choosing the mammal type, RR prefiltering method. The “Analysis” tab can be used for performing multiple window analysis (i.e., batch processing of the time series). The “Options” tab can be used to change all key parameters of the HRV measures. These “Options” are updated automatically in accordance with the chosen mammal; they can also be modified manually. (B) Graph displaying the RR or HR time series. In blue the raw time series and in green the filtered time series. (C) Panels presenting the HRV measures. Under the tab “Time,” “Frequency,” and “Non-linear,” the HRV measures relative to each of these categories are repeated and the standard figures relative to each category are plotted (e.g., Poincare plots, Power spectrum). More details are available in the software documentation.

FIGURE 6

Double-logarithmic plot of: (A) the mean SampEn vs. typical heart rate (HR_m) and (B) the mean SampEn vs. body mass (BM_m).