Cerebral disorders diagnosis via a secure transmission of multichannel EEG signal based on IoMT

Hammad, Jamal A.; Hmeed, Assef Raad; Obaid, Ahmed J.

doi:10.47974/JDMSC-1676

Open Access Research Article

Cerebral disorders diagnosis via a secure transmission of multichannel EEG signal based on IoMT

^*Jamal A. HammadCorresponding authorjamal.ali@uoanbar.edu.iqCollege of PharmacyUniversity of AnbarAnbar, IraqView full profile → , Assef Raad Hmeedassef.raad@uoanbar.edu.iqDepartment of Students Affairs and RegistrationUniversity of AnbarAnbar, IraqView full profile → , Ahmed J. Obaidahmedj.aljanaby@uokufa.edu.iqDepartment of Computer ScienceFaculty of Computer Science and MathematicsUniversity of KufaNajaf, IraqView full profile →

* Corresponding author · click or hover a name for details

pp. 1865–1873Vol. 26Issue 7October 2023DOI: 10.47974/JDMSC-1676 Crossmark XML

Received:: 11 Oct 2022
Published Online:: 30 Oct 2023
Article type:: Research Article
Language:: EN
Article no.:: JDMSC-1676
Pages:: 1865–1873

Abstract

Electroencephalogram (EEG) data require a wider storage device setup due to its constant brainwave intensity logs and biosignal parameter. Therefore, effective compression systems are utilized before sending these signals to a medical station such as hospitals and therapy centres or through mobile medical instruments as one of the Internet medical things (IoMT) tools for real-time surveillance and analysis by specialists and anywhere. Conventional compression techniques can improve storage efficiency and help quickly transfer medical data from one computer to another because of their limited size. In addition, the received EEG (MCh-EEG) data are processed using various filtering methods to remove undesired noise and then compressed. The proposed method, which utilized buffer blocks, which is quite new in this field, was proposed. The smooth and safe transmission process of multichannel EEG signals from the sensor to the surveillance is achieved by using highly effective methods to detect brainwaves, remove noise, compress and encrypt those signals. This work utilizes the mode of AES 256 BCM, which is rarely utilized in embedded systems, proving to be very powerful and effective in information ciphering. Based on the proposed system’s PRD parameter, the findings come as 0.41% and CR as 0.35%, and it’s better than the current schemes. Experimental findings demonstrate the effectiveness of the proposed systems on 10 different records of MCH-EEG signals from the CHB-MIT Scalp EEG dataset.

Keywords

Multichannel electroencephalogram (MCh-EEG)Block-cipher mode (BCM-Operation)Advanced encryption standard (AES)Internet of medical things (IoT)

Subject Classifications

91G2093B17

References

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