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

Szymon Siecinski; Laura Pauline Scherf; Marcin Grzegorzek

doi:10.1109/IEEECONF58974.2023.10405047

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

Szymon Siecinski
, Laura Pauline Scherf
, Marcin Grzegorzek

Katedra Informatyki Medycznej i Sztucznej Inteligencji (RIB/RIB1)

University of Lübeck

Wyniki badań: Rozdział w książce/raport/materiał konferencyjny › Wkład w konferencję › recenzja

3 Cytowania z bazy Scopus

Abstrakt

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.

Język oryginału	angielski
Tytuł publikacji goszczącej	2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023
Wydawca	Institute of Electrical and Electronics Engineers Inc.
Strony	161-162
Liczba stron	2
ISBN (elektroniczny)	9798350383386
Identyfikatory DOI	https://doi.org/10.1109/IEEECONF58974.2023.10405047
Status publikacji	Opublikowano - 2023
Wydarzenie	2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023 - Malta, Malta Czas trwania: 7 gru 2023 → 9 gru 2023

Seria publikacji

Nazwa	2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023

Konferencja

Konferencja	2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023
Kraj/Terytorium	Malta
Miejscowość	Malta
Okres	7/12/23 → 9/12/23

Obszary tematyczne ASJC Scopus

Sztuczna inteligencja
Interakcja człowiek-komputer
Systemy informacyjne
Nauki o podejmowaniu decyzji (różne)
Systemy informacyjne i zarządzanie
Inżynieria biomedyczna
Informatyka medyczna

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10.1109/IEEECONF58974.2023.10405047

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Siecinski, S., Scherf, L. P., & Grzegorzek, M. (2023). Evaluation of the quality of electrocardiograms, seismocardiograms and gyrocardiograms based on characteristics derived from symmetric projection attractor reconstruction. W 2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023 (str. 161-162). (2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IEEECONF58974.2023.10405047

Siecinski, Szymon ; Scherf, Laura Pauline ; Grzegorzek, Marcin. / Evaluation of the quality of electrocardiograms, seismocardiograms and gyrocardiograms based on characteristics derived from symmetric projection attractor reconstruction. 2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023. Institute of Electrical and Electronics Engineers Inc., 2023. str. 161-162 (2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023).

@inproceedings{93c0f7eb3811435ba614eb566ee7a064,

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

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.",

author = "Szymon Siecinski and Scherf, \{Laura Pauline\} and Marcin Grzegorzek",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023 ; Conference date: 07-12-2023 Through 09-12-2023",

year = "2023",

doi = "10.1109/IEEECONF58974.2023.10405047",

language = "English",

series = "2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "161--162",

booktitle = "2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023",

address = "United States",

}

Siecinski, S, Scherf, LP & Grzegorzek, M 2023, Evaluation of the quality of electrocardiograms, seismocardiograms and gyrocardiograms based on characteristics derived from symmetric projection attractor reconstruction. w 2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023. 2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023, Institute of Electrical and Electronics Engineers Inc., str. 161-162, 2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023, Malta, Malta, 7/12/23. https://doi.org/10.1109/IEEECONF58974.2023.10405047

Evaluation of the quality of electrocardiograms, seismocardiograms and gyrocardiograms based on characteristics derived from symmetric projection attractor reconstruction. / Siecinski, Szymon; Scherf, Laura Pauline; Grzegorzek, Marcin.
2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023. Institute of Electrical and Electronics Engineers Inc., 2023. str. 161-162 (2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023).

Wyniki badań: Rozdział w książce/raport/materiał konferencyjny › Wkład w konferencję › recenzja

TY - GEN

T1 - Evaluation of the quality of electrocardiograms, seismocardiograms and gyrocardiograms based on characteristics derived from symmetric projection attractor reconstruction

AU - Siecinski, Szymon

AU - Scherf, Laura Pauline

AU - Grzegorzek, Marcin

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

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U2 - 10.1109/IEEECONF58974.2023.10405047

DO - 10.1109/IEEECONF58974.2023.10405047

M3 - Conference contribution

AN - SCOPUS:85185557306

T3 - 2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023

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EP - 162

BT - 2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023

Y2 - 7 December 2023 through 9 December 2023

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Siecinski S, Scherf LP, Grzegorzek M. Evaluation of the quality of electrocardiograms, seismocardiograms and gyrocardiograms based on characteristics derived from symmetric projection attractor reconstruction. W 2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023. Institute of Electrical and Electronics Engineers Inc. 2023. str. 161-162. (2023 IEEE EMBS Special Topic Conference on Data Science and Engineering in Healthcare, Medicine and Biology, IEEECONF 2023). doi: 10.1109/IEEECONF58974.2023.10405047

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

Abstrakt

Seria publikacji

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Obszary tematyczne ASJC Scopus

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