The synthetic dataset is a collection of simulated electrocardiogram (ECG) and pulse oximetry (photoplethysmogram, PPG) signals. The signals were generated to allow researchers to check that their algorithms are able to estimate respiratory rate (RR) accurately on idealised data. It is particularly helpful for ensuring that algorithms are reasonably implemented.


The dataset contains ECG and PPG signals across covering a range of heart rates (HRs) and RRs. Three signals are provided for each combination of HR and RR, each exhibiting either baseline wander (BW), amplitude modulation (AM), or frequency modulation (FM).

The dataset is provided in Matlab format. Firstly, the source code used to generate the dataset is provided (here). This allows users to modify the dataset to their own liking. Secondly, the dataset is provided having used a particular configuration of the source code to produce it (below).


Exemplary Synthetic Signals: Idealised PPG and ECG signals are shown on the top row. On the three subsequent rows are idealised signals modulated with Baseline Wander (BW), Amplitude Modulation (AM) and Frequency Modulation (FM). Adapted from:

(1) Addison, P.S. et al.: Developing an algorithm for pulse oximetry derived respiratory rate (RR(oxi)): a healthy volunteer study. Journal of Clinical Monitoring and Computing, 26(1), 45-51 (2012), DOI: 10.1007/s10877-011-9332-y

(2) Pimentel, M.A. et al.: Probabilistic estimation of respiratory rate from wearable sensors. in Wearable Electronics Sensors, Springer International Publishing, 15, 241-262 (2015), DOI: 10.1007/978-3-319-18191-2_10


This dataset was first reported in this publication, which contains additional information on the dataset.


When using this dataset please cite this publication:

Charlton P.H. and Bonnici T. et al. An assessment of algorithms to estimate respiratory rate from the electrocardiogram and photoplethysmogram, Physiological Measurement, 37(4), 2016

Link to download

The dataset is provided in three formats. Use the links below to download the dataset in your preferred format:

The following additional files are also provided:

The dataset and accompanying files are stored at DOI: 10.18742/RDM01-23.