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A High Precision Real-time Premature Ventricular Contraction Assessment Method based on the Complex Feature Set

  • Mobile & Wireless Health
  • Published:
Journal of Medical Systems Aims and scope Submit manuscript

Abstract

This paper presents a high precision and low computational complexity premature ventricular contraction (PVC) assessment method for the ECG human-machine interface device. The original signals are preprocessed by integrated filters. Then, R points and surrounding feature points are determined by corresponding detection algorithms. On this basis, a complex feature set and feature matrices are obtained according to the position feature points. Finally, an exponential Minkowski distance method is proposed for PVC recognition. Both public dataset and clinical experiments were utilized to verify the effectiveness and superiority of the proposed method. The results show that our R peak detection algorithm can substantially reduce the error rate, and obtained 98.97% accuracy for QRS complexes. Meanwhile, the accuracy of PVC recognition was 98.69% for the MIT-BIH database and 98.49% for clinical tests. Moreover, benefiting from the lightweight of our model, it can be easily applied to portable healthcare devices for human-computer interaction.

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Acknowledgements

Our research is supported by the National Key R&D Program of China (No. 2018YFB1307005).

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Authors and Affiliations

  1. School of Mechanical Engineering, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240, People’s Republic of China

    Haoren Wang, Haotian Shi, Xiaojun Chen, Yixiang Huang & Chengliang Liu

  2. Department of Cardiology, Shanghai First People’s Hospital Affiliated to Shanghai Jiao Tong University, 100, Haining Road, Shanghai, 200080, People’s Republic of China

    Liqun Zhao

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  1. Haoren Wang
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  2. Haotian Shi
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  3. Xiaojun Chen
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  4. Liqun Zhao
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  5. Yixiang Huang
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  6. Chengliang Liu
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Correspondence to Chengliang Liu.

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All authors declare that there is no conflict of interest in this work.

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All the procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and the 1964 Helsinki declaration and its later amendments or comparable ethical standards. We have obtained the ethical approval for ECG data from Shanghai First People’s Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, China.

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Wang, H., Shi, H., Chen, X. et al. A High Precision Real-time Premature Ventricular Contraction Assessment Method based on the Complex Feature Set. J Med Syst 44, 3 (2020). https://doi.org/10.1007/s10916-019-1443-x

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