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Dynamic time warping based arrhythmia detection using photoplethysmography signals

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Abstract

Photoplethysmography (PPG) based methods have gained popularity in recent times for arrhythmia detection. However, limited research has been carried out for multiple arrhythmia detection using PPG signals. Dynamic time warping (DTW) is a widely used time series technique for the comparison of speech and word recognition. However, the use of the DTW technique for arrhythmia detection using PPG signals is unexplored. In this research work, DTW is utilized to extract automated generated warping features. A feed-forward artificial neural network (ANN) has been used to classify the arrhythmia among four arrhythmia classes. The evaluation of the results has been carried out on 670 PPG signals of 8-s duration available on the PhysioNet MIMIC-II public database. The proposed model obtains an accuracy, sensitivity, specificity, F1 score, and precision of 95.97%, 97%, 97%, 96%, and 96%, respectively. The results show that the proposed approach has been able to detect multiple types of arrhythmias with significant performance.

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PhysioNet MIMIC-II.

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Acknowledgements

The research work has been funded by CSIR HQ under Intelligent Systems Mission HCP0013 WP 1.3 at CSIR-CSIO, Chandigarh. Neha is thankful to the Council of Scientific and Industrial Research – Senior Research Fellow (CSIR-SRF), grant no. 31/31/(0053)/2k19-EMR-I.

Funding

The research work has been funded by the Council of Scientific and Industrial Research – Senior Research Fellow (CSIR-SRF), grant no. 31/31/(0053)/2k19-EMR-1.

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Authors and Affiliations

  1. Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh, 201002, India

    Neha, H. K. Sardana & R. Kanawade

  2. Central Scientific Instruments Organisation, Chandigarh, 160030, India

    H. K. Sardana & R. Kanawade

  3. Postgraduate Institute of Medical Education and Research, Chandigarh, 160012, India

    N. Dogra

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  1. Neha
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  2. H. K. Sardana
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  3. N. Dogra
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  4. R. Kanawade
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Contributions

Neha: Conceptualization, data analysis, algorithm development, written original draft. H K Sardana: Supervision, conceptualization, data analysis, manuscript editing. ND: Data annotation, conceptualization, manuscript editing. Rajesh Kanawade: Supervision, conceptualization, data analysis, manuscript editing.

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Correspondence to H. K. Sardana.

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Neha, Sardana, H.K., Dogra, N. et al. Dynamic time warping based arrhythmia detection using photoplethysmography signals. SIViP 16, 1925–1933 (2022). https://doi.org/10.1007/s11760-022-02152-z

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  • DOI: https://doi.org/10.1007/s11760-022-02152-z

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