Evaluation of the quality of electrocardiograms, seismocardiograms and gyrocardiograms based on characteristics derived from symmetric projection attractor reconstruction

Szymon Sieciński*, Laura Pauline Scherf, Marcin Grzegorzek

*Corresponding author for this work

Abstract

This study presents the evaluation of cardiovascular signals (electrocardiograms, seismocardiograms, and gyrocardiograms) based on features derived from symmetric projection attractor reconstruction (SPAR). We assessed five classifiers: random forests, bagged trees, gradient boosting, multilayer perceptron, and support vector machine. The highest accuracy was achieved for bagged trees in ECG signals (0.6667) and the lowest overall accuracy for the multilayer perceptron in SCG signals (0.3333). The results showed that five classifiers fed features derived from SPAR can be used to assess the quality of cardiovascular signals.
Original languageEnglish
Pages161-162
Number of pages2
DOIs
Publication statusPublished - 29.01.2024
Event2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology - Hilton Malta, St. Julian's, Malta
Duration: 07.12.202309.12.2023
https://datascience.embs.org/2023

Conference

Conference2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology
Country/TerritoryMalta
CitySt. Julian's
Period07.12.2309.12.23
Internet address

Research Areas and Centers

  • Centers: Center for Artificial Intelligence Luebeck (ZKIL)

DFG Research Classification Scheme

  • 205-32 Medical Physics, Biomedical Engineering
  • 205-07 Medical Informatics and Medical Bioinformatics
  • 205-12 Cardiology, Angiology

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