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Benchmark Problems and Benchmark Datasets for the evaluation of Machine and Deep Learning methods on Photoplethysmography signals: the D4 report from the QUMPHY project

Urs Hackstein, Jordi Alastruey, Philip Aston, Ciaran Bench, Peter H. Charlton, Loic Coquelin, Nando Hegemann, Vaidotas Marozas, Mohammad Moulaeifard, Manasi Nandi, Andrius Petrenas, Oskar Pfeffer, Mantas Rinkevicius, Andrius Solosenko, Nils Strodthoff, Sara Vardanega

Abstract

This report is part of the Qumphy project (22HLT01 Qumphy) that is funded by the European Union and is dedicated to the development of measures to quantify the uncertainties associated with Machine Learning algorithms applied to medical problems, in particular the analysis and processing of Photoplethysmography (PPG) signals. In this report, a list of six medical problems that are related to PPG signals and serve as Benchmark Problems is given. Suitable Benchmark datasets and their usage are described also.

Benchmark Problems and Benchmark Datasets for the evaluation of Machine and Deep Learning methods on Photoplethysmography signals: the D4 report from the QUMPHY project

Abstract

This report is part of the Qumphy project (22HLT01 Qumphy) that is funded by the European Union and is dedicated to the development of measures to quantify the uncertainties associated with Machine Learning algorithms applied to medical problems, in particular the analysis and processing of Photoplethysmography (PPG) signals. In this report, a list of six medical problems that are related to PPG signals and serve as Benchmark Problems is given. Suitable Benchmark datasets and their usage are described also.

Paper Structure

This paper contains 54 sections, 6 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Photoplethysmography
  3. The Qumphy project
  4. Aim of the report
  5. Benchmark I: Determine systolic and diastolic blood pressure
  6. The problem
  7. Potential datasets
  8. Aurora BP
  9. Vital DB
  10. Making the datasets available
  11. Aurora BP
  12. VitalDB
  13. Dataset usage
  14. Aurora BP
  15. VitalDB
  16. ...and 39 more sections

Figures (6)

  • Figure 1: An exemplary photoplethysmogram (PPG) signal showing a pulse wave for each heartbeat. Pulse onsets, representing individual heartbeats, are shown as red circles. An inter-beat interval is labelled, corresponding to the time between consecutive heartbeats. Adapted from Charlton2020 by Peter H. Charlton - Own work, CC BY 4.0, https://commons.wikimedia.org/wiki/File:Photoplethysmogram_(PPG)_signal.png
  • Figure 2: The example of (a) arterial blood pressure (ABP) segment with labeled fiducial points (systolic (SBP) and diastolic (DBP) blood pressure) and (b) PPG segment.
  • Figure 3: The example of (a) ECG segment and (b) PPG segment with atrial fibrillation from TriggersAF dataset.
  • Figure 4: The example of (a) ECG segment and (b) PPG segment with premature beats and tachycardia from TriggersAF dataset.
  • Figure 5: The changes of signals during sleep apnea episodes: (a) respiratory airflow, (b) finger PPG signal, (c) arterial blood oxygen saturation, SpO2, and heart rate, HR.
  • ...and 1 more figures