ECG-Based Secure Healthcare Monitoring System in Body Area Networks

Shanthapriya, R; Vaithianathan,

doi:10.1109/icbsii.2018.8524714

Cited by 9 publications

(3 citation statements)

References 9 publications

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“…Faust et al Journal of Healthcare Engineering [2] summarized the application of deep learning algorithms in physiological signals and pointed out that deep learning methods performed better than classical analysis and machine classification methods for large and diverse datasets. Shanthapriya and Vaithianathan [3] proposed the health monitoring system for human regional network. e steganography technologies monitor patients' health safety and provide patients with data confidentiality and identity authentication.…”

Section: Related Workmentioning

confidence: 99%

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[Retracted] Merging RFID and Blockchain Technologies to Accelerate Big Data Medical Research Based on Physiological Signals

Chen

Hong

Geng

et al. 2020

Journal of Healthcare Engineering

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The proliferation of physiological signals acquisition and monitoring system, has led to an explosion in physiological signals data. Additionally, RFID systems, blockchain technologies, and the fog computing mechanisms have significantly increased the availability of physiological signal information through big data research. The driver for the development of hybrid systems is the continuing effort in making health-care services more efficient and sustainable. Implantable medical devices (IMD) are therapeutic devices that are surgically implanted into patients’ body to continuously monitor their physiological parameters. Patients treat cardiac arrhythmia due to IMD therapeutic and life-saving benefits. We focus on hybrid systems developed for patient physiological signals for collection, storage protection, and monitoring in critical care and clinical practice. In order to provide medical data privacy protection and medical decision support, the hybrid systems are presented, and RFID, blockchain, and big data technologies are used to analyse physiological signals.

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Section: Related Workmentioning

confidence: 99%

“…e hospitals applications are adopting physiological signals to realize a quicker way to visit these records. e physiological signals are responsible to offer patient care, enhance the clinical performances, and promote the clinical data research [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Merging RFID and Blockchain Technologies to Accelerate Big Data Medical Research Based on Physiological Signals

Chen

Hong

Geng

et al. 2020

Journal of Healthcare Engineering

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“…Among all, ECG is essential as a result of its capacity to analyze cardiovascular illnesses that is the significant reason for deaths according to the report of WHO [4]. Given the significance of ECG signal examination from the health point of view, this work concentrates just around ECG signals [5,6]. Probably the greatest challenge in WBSN is to send the sensed ECG data safely to the medical server because any progressions of this delicate data may cause wrong diagnosis and wrong treatment of the patient.…”

Section: Introductionmentioning

confidence: 99%

Secured ECG Signal Transmission Using Optimized EGC with Chaotic Neural Network in WBSN

Mishra¹,

Jain²,

Maik³

2023

Computer Systems Science and Engineering

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In wireless body sensor network (WBSN), the set of electrocardiogram (ECG) data which is collected from sensor nodes and transmitted to the server remotely supports the experts to monitor the health of a patient. While transmitting these collected data some adversaries may capture and misuse it due to the compromise of security. So, the major aim of this work is to enhance secure transmission of ECG signal in WBSN. To attain this goal, we present Pity Beetle Swarm Optimization Algorithm (PBOA) based Elliptic Galois Cryptography (EGC) with Chaotic Neural Network. To optimize the key generation process in Elliptic Curve Cryptography (ECC) over Galois field or EGC, private key is chosen optimally using PBOA algorithm. Then the encryption process is enhanced by presenting chaotic neural network which is used to generate chaotic sequences or cipher data. Results of this work show that the proposed cryptography algorithm attains better encryption time, decryption time, throughput and SNR than the conventional cryptography algorithms.

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ECG signals-based security and steganography approaches in WBANs: A comprehensive survey and taxonomy

Masdari,

Band,

Qasem

et al. 2024

Sustainable Computing: Informatics and Systems

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ECG-Based Secure Healthcare Monitoring System in Body Area Networks

Cited by 9 publications

References 9 publications

[Retracted] Merging RFID and Blockchain Technologies to Accelerate Big Data Medical Research Based on Physiological Signals

[Retracted] Merging RFID and Blockchain Technologies to Accelerate Big Data Medical Research Based on Physiological Signals

Secured ECG Signal Transmission Using Optimized EGC with Chaotic Neural Network in WBSN

ECG signals-based security and steganography approaches in WBANs: A comprehensive survey and taxonomy

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