CITATION.cff

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title: >-
  Accelerated Sample-Accurate R-Peak Detectors Based on
  Visibility Graphs
message: 'If you use this package, please cite it as below.'
type: software
authors:
  - given-names: Jonas
    family-names: Emrich
    email: mail@jonasemrich.de
  - given-names: Taulant
    family-names: Koka
  - given-names: Sebastian
    family-names: Wirth
  - given-names: Michael
    family-names: Muma
identifiers:
  - type: doi
    value: 10.23919/EUSIPCO58844.2023.10290007
repository-code: 'https://github.com/JonasEmrich/vg-beat-detectors'
abstract: >-
  The effective detection and accurate clinical diagnosis of
  cardiac conditions strongly relies on the correct
  localization of R-peaks in the electrocardiogram (ECG).
  Recently, demand for sample-accurate R-peak detection,
  which is essential to precisely reveal vital features,
  such as heart rate variability and pulse transit time, has
  increased. Therefore, we propose two novel sample-accurate
  visibility-graph-based R-peak detectors, the FastNVG and
  the FastWHVG detector. The visibility graph (VG)
  transformation maps a discrete signal into a graph by
  representing sampling locations as nodes and establishing
  edges between mutually visible samples. However,
  processing large-scale clinical ECG data urgently demands
  further acceleration of VG-based algorithms. The proposed
  methods reduce the required computation time by one order
  of magnitude and simultaneously decrease the required
  memory compared to a recently proposed VG-based R-Peak
  detector. Instead of transforming the entire ECG, the
  proposed acceleration benefits largely from building the
  VG based on a subset containing only the samples relevant
  to R-peak detection. Further acceleration is obtained by
  adopting the computationally efficient horizontal
  visibility graph, which has not yet been used for R-peak
  detection. Numerical experiments and benchmarks on
  multiple ECG databases demonstrate a significantly
  superior performance of the proposed VG-based methods
  compared to popular R-peak detectors.
keywords:
  - R-peak detection
  - Visibility graph
license: GPL-3.0
preferred-citation:
  type: conference-paper
  authors:
  - given-names: Jonas
    family-names: Emrich
    email: mail@jonasemrich.de
  - given-names: Taulant
    family-names: Koka
  - given-names: Sebastian
    family-names: Wirth
  - given-names: Michael
    family-names: Muma
  title: "Accelerated Sample-Accurate R-Peak Detectors Based on Visibility Graphs"
  conference:
    name: "2023 31st European Signal Processing Conference (EUSIPCO)"
  collection-title: "2023 31st European Signal Processing Conference (EUSIPCO)"
  month: 9
  doi: 10.23919/EUSIPCO58844.2023.10290007
  start: 1090 # First page number
  end: 1094 # Last page number
  year: 2023