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A dictionary matrix generation based compression and bitwise embedding mechanisms for ECG signal classification

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Abstract

The Electrocardiogram (ECG) signal processing is one of the exciting research areas in recent days. Ensuring security to the patient’s confidential information is a demanding critical task in many healthcare systems. So, the traditional works developed the security mechanisms for embedding the original ECG signal with the image, audio, or video. But, it does not focus on reducing the size of the original message before transmitting it to others. Also, it has significant limitations of inefficient security, increased complexity, and reduced classification accuracy. To rectify this issue, our research proposed the new embedding mechanism to improve the security of patient’s health information. In this system, the original ECG signals compressed at the initial stage by using the proposed Dictionary Matrix Generation (DMG) algorithm. Then, the compressed signals embedded within the cover image by using the Bitwise Embedding (BE) mechanism. At the receiver side, the bedded goal is de-embedded and decompressed by using the DMG and BE algorithms. The features such as spectral and peak values of the signal are extracted for increasing the efficiency of classification. Classification and detection of abnormality present in ECG signal of patient is the most essential part. To achieve this, we proposed the Modified Dynamic Classification (MDC) algorithm based on the features. In this work, the novelty is implemented in the compression, embedding, and classification stages. The proposed system reduces the data loss during transmission, memory storage and time complexity. The overall process evaluated by using PTB diagnostic ECG database. In experiments, the proposed classification technique provides the accuracy of 98.39% and it proved that the proposed method had highest performances than existing methods such as PNN, SVM and RF classification.

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Authors and Affiliations

  1. Department of Electrical Engineering, Delhi Technological University, Bawana Road, Delhi, 110042, India

    Dinesh Kumar Atal & Mukhtiar Singh

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  1. Dinesh Kumar Atal
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  2. Mukhtiar Singh
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Correspondence to Mukhtiar Singh.

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Atal, D.K., Singh, M. A dictionary matrix generation based compression and bitwise embedding mechanisms for ECG signal classification. Multimed Tools Appl 79, 13139–13159 (2020). https://doi.org/10.1007/s11042-020-08671-6

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  • DOI: https://doi.org/10.1007/s11042-020-08671-6

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