Deformable Part Model Based Arrhythmia Detection Using Time Domain Features

Yuuka HIRAO; Yoshinori TAKEUCHI; Masaharu IMAI; Jaehoon YU

doi:10.1587/transfun.E100.A.2221

Deformable Part Model Based Arrhythmia Detection Using Time Domain Features

Yuuka HIRAO, Yoshinori TAKEUCHI, Masaharu IMAI, Jaehoon YU

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Summary :

Heart disease is one of the major causes of death in many advanced countries. For prevention or treatment of heart disease, getting an early diagnosis from a long time period of electrocardiogram (ECG) examination is necessary. However, it could be a large burden on medical experts to analyze this large amount of data. To reduce the burden and support the analysis, this paper proposes an arrhythmia detection method based on a deformable part model, which absorbs individual variation of ECG waveform and enables the detection of various arrhythmias. Moreover, to detect the arrhythmia in low processing delay, the proposed method only utilizes time domain features. In an experimental result, the proposed method achieved 0.91 F-measure for arrhythmia detection.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E100-A No.11 pp.2221-2229

Publication Date: 2017/11/01

Publicized

Online ISSN: 1745-1337

DOI: 10.1587/transfun.E100.A.2221

Type of Manuscript: Special Section PAPER (Special Section on Smart Multimedia & Communication Systems)

Category: Digital Signal Processing

Authors

Yuuka HIRAO
  Osaka University
Yoshinori TAKEUCHI
  Osaka University
Masaharu IMAI
  Osaka University
Jaehoon YU
  Osaka University

Keyword

arrhythmia detection, electrocardiogram, deformable part model, time domain features

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Yuuka HIRAO, Yoshinori TAKEUCHI, Masaharu IMAI, Jaehoon YU, "Deformable Part Model Based Arrhythmia Detection Using Time Domain Features" in IEICE TRANSACTIONS on Fundamentals, vol. E100-A, no. 11, pp. 2221-2229, November 2017, doi: 10.1587/transfun.E100.A.2221.
Abstract: Heart disease is one of the major causes of death in many advanced countries. For prevention or treatment of heart disease, getting an early diagnosis from a long time period of electrocardiogram (ECG) examination is necessary. However, it could be a large burden on medical experts to analyze this large amount of data. To reduce the burden and support the analysis, this paper proposes an arrhythmia detection method based on a deformable part model, which absorbs individual variation of ECG waveform and enables the detection of various arrhythmias. Moreover, to detect the arrhythmia in low processing delay, the proposed method only utilizes time domain features. In an experimental result, the proposed method achieved 0.91 F-measure for arrhythmia detection.
URL: https://globals.ieice.org/en_transactions/fundamentals/10.1587/transfun.E100.A.2221/_p

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@ARTICLE{e100-a_11_2221,
author={Yuuka HIRAO, Yoshinori TAKEUCHI, Masaharu IMAI, Jaehoon YU, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Deformable Part Model Based Arrhythmia Detection Using Time Domain Features},
year={2017},
volume={E100-A},
number={11},
pages={2221-2229},
abstract={Heart disease is one of the major causes of death in many advanced countries. For prevention or treatment of heart disease, getting an early diagnosis from a long time period of electrocardiogram (ECG) examination is necessary. However, it could be a large burden on medical experts to analyze this large amount of data. To reduce the burden and support the analysis, this paper proposes an arrhythmia detection method based on a deformable part model, which absorbs individual variation of ECG waveform and enables the detection of various arrhythmias. Moreover, to detect the arrhythmia in low processing delay, the proposed method only utilizes time domain features. In an experimental result, the proposed method achieved 0.91 F-measure for arrhythmia detection.},
keywords={},
doi={10.1587/transfun.E100.A.2221},
ISSN={1745-1337},
month={November},}

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TY - JOUR
TI - Deformable Part Model Based Arrhythmia Detection Using Time Domain Features
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2221
EP - 2229
AU - Yuuka HIRAO
AU - Yoshinori TAKEUCHI
AU - Masaharu IMAI
AU - Jaehoon YU
PY - 2017
DO - 10.1587/transfun.E100.A.2221
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E100-A
IS - 11
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - November 2017
AB - Heart disease is one of the major causes of death in many advanced countries. For prevention or treatment of heart disease, getting an early diagnosis from a long time period of electrocardiogram (ECG) examination is necessary. However, it could be a large burden on medical experts to analyze this large amount of data. To reduce the burden and support the analysis, this paper proposes an arrhythmia detection method based on a deformable part model, which absorbs individual variation of ECG waveform and enables the detection of various arrhythmias. Moreover, to detect the arrhythmia in low processing delay, the proposed method only utilizes time domain features. In an experimental result, the proposed method achieved 0.91 F-measure for arrhythmia detection.
ER -