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Protecting ECG Signals with Hybrid Swarm Intelligence Algorithm

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Artificial Intelligence in Healthcare

Part of the book series: Advanced Technologies and Societal Change ((ATSC))

Abstract

Protecting biomedical data on the internet has become utmost important. A proper scheme is required for the security of the biomedical data, ignoring data security can cause serious harm to the patient data. In recent times the hybrid swarm intelligence algorithms have gained popularity in the field of data security, owing to their efficient performance. In this Chapter, to resolve the issue of medical data security, a hybrid PSO (particle swarm optimization) based watermarking mechanism is investigated. The hybrid PSO algorithm is combination of Firefly algorithm and PSO algorithm (HFPSO). The HFPSO combine best of both the algorithms removing the flaws. The patient’s confidential information is embedded in the ECG signal. The main aim of this work is to identify the optimal embedding factor to embed the patient’s information in an ECG signal without disturbing the medical information of the ECG signal. The optimal embedding allows the successful extraction of embedded information even after various intentional and unintentional attacks. The patient’s data is converted to QR code. The patient QR code is embedded in ECG signal using QR decomposition and Discrete Cosine Transform (DCT). The ECG signal is decomposed using DCT before data embedding. The Hybrid Firefly-Particle Swarm Optimization algorithm is used to adaptively detect the best value for embedding factor for the given ECG signal.

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Author information

Authors and Affiliations

  1. Electronics and Communication Engineering, PDPM Indian Institute of Information Technology, Design and Manufacturing, Jabalpur, India

    Ayushi Kirar, Siddharth Bhalerao & Irshad Ahmad Ansari

  2. Department of Instrumentation and Control Engineering, Dr B R Ambedkar National Institute of Technology Jalandhar, Jalandhar, India

    Om Prakash Verma

Authors
  1. Ayushi Kirar
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  2. Siddharth Bhalerao
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  3. Om Prakash Verma
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  4. Irshad Ahmad Ansari
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Corresponding author

Correspondence to Irshad Ahmad Ansari .

Editor information

Editors and Affiliations

  1. Information and Communication Technology, University of Malta, Msida, Malta

    Lalit Garg

  2. Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, Ostrava, Czech Republic

    Sebastian Basterrech

  3. Amity Institute of Information Technology, Amity University Rajasthan, Jaipur, Rajasthan, India

    Chitresh Banerjee

  4. Department of Computer Science, Shobhit University Gangoh, Gangoh, India

    Tarun K. Sharma

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Kirar, A., Bhalerao, S., Verma, O.P., Ansari, I.A. (2022). Protecting ECG Signals with Hybrid Swarm Intelligence Algorithm. In: Garg, L., Basterrech, S., Banerjee, C., Sharma, T.K. (eds) Artificial Intelligence in Healthcare. Advanced Technologies and Societal Change. Springer, Singapore. https://doi.org/10.1007/978-981-16-6265-2_4

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