King's College London

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Data used in paper 'An Assessment of Algorithms to Estimate Respiratory Rate from the Electrocardiogram and Photoplethysmogram'

posted on 2021-09-12, 20:31 authored by Peter H. Charlton, Timothy Bonnici, Lionel Tarassenko, David A. Clifton, Richard Beale, Peter J. Watkinson
This dataset contains electrocardiogram (ECG), photoplethysmogram (PPG), Impedance Pneumography (imp) and reference oral-nasal pressure (paw) signals acquired from young subjects (aged 18-39). Data were acquired for approximately 10 minutes while lying supine at rest. Following this subjects were asked to run on a treadmill (data are not provided from this period). Data were then collected during a second recording period whilst subjects recovered from the exercise, lying supine once again. An example of the signals available in the dataset is included in the accompanying ReadMe file.

Further details of the dataset and acquisition procedures are provided in the published paper: Charlton P.H. and Bonnici T.B. et al., An assessment of algorithms to estimate respiratory rate from the electrocardiogram and photoplethysmogram, Physiological Measurement, 37(4), 2016. DOI: 10.1088/0967-3334/37/4/610.

Data files included in this dataset: VORTAL_rest_data.mat VORTAL_rec_data.mat

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Data collection from date


Data collection to date


Collection method

Physiological signals acquired from healthy volunteers lying supine. Further details are provided in the accompanying publication.



Copyright owner

Peter H. Charlton, King's College London; Timothy Bonnici, King's College London; Richard Beale, King's College London