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ECG Signal Analysis based on the Spectrogram and Spider Monkey Optimisation Technique

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Abstract

Heart is responsible for circulation of the blood throughout the human body. The conduction of the heart is nonlinear in nature and hence needs appropriate utilisation of technological advancements. The activity of the heart is assessed through an electrocardiogram (ECG) signal that consists of three different types of waves viz. P-wave, QRS-wave (also called QRS complex), and T-wave. But these waves are non-stationary, and hence, investigation of effective tools is essential for their accurate analysis. In this paper, the spectrogram technique is proposed to be used for feature extraction to analyse different segments of heartbeats (energy change) through colour contrasts of various frequency components with respect to time unlike the existing techniques where it was not possible. The features are extracted after the pre-processing accomplished using a digital bandpass filter (DBPF). The extracted features are further proposed to be optimised using the spider monkey optimisation technique due to its acclaimed effectiveness in solving the real-world optimisation problems. The robustness of the proposed methodology is established in fulfilling the ever-increasing demand of modern health care.

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Abbreviations

ECG:

Electrocardiogram

MECG:

Maternal ECG

fECG:

Foetal ECG

Se:

Sensitivity

PP:

Positive predictivity

IFIR:

Interpolated finite impulse response

SVM:

Support vector machine

DR:

Detection rate

HRV:

Heart rate variability

ANS:

Autonomic nervous system

PCA:

Principal component analysis

ANN:

Artificial neural networks

KNN:

K-nearest neighbour

Acc:

Accuracy

SSA:

Salp swarm algorithm

ICA:

Independent component analysis

DER:

Detection error rate

SMO:

Spider monkey optimisation

MIT:

Massachusetts Institute of Technology

BIH:

Beth Israel Hospital

EC:

Entropy criterion

ISC:

Improved So and Chan

RLE:

Run-length encoding

SampEn:

Sample entropy

ANCs:

Adaptive noise cancellers

SNR:

Signal-to-noise ratio

WT:

Wavelet transform

SA:

Sino-atrial

AV:

Atrio-ventricular

PLI:

Power line interference

BLW:

Base line wander

EMG:

Electromyogram

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  1. Department of Electrical and Electronics Engineering, KIET Group of Institutions, Delhi-NCR, Ghaziabad, 201206, India

    Varun Gupta, Sourav Diwania & Nitin Kumar Saxena

  2. Department of Electrical Engineering, National Institute of Technology, Kurukshetra, 136119, India

    Monika Mittal

  3. Department of Electronics and Communication Engineering, National Institute of Technology, Kurukshetra, 136119, India

    Vikas Mittal

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Gupta, V., Mittal, M., Mittal, V. et al. ECG Signal Analysis based on the Spectrogram and Spider Monkey Optimisation Technique. J. Inst. Eng. India Ser. B 104, 153–164 (2023). https://doi.org/10.1007/s40031-022-00831-6

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