Related Experiment Video
Updated: Jun 3, 2025
08:22
Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
Published on: April 26, 2024
1.7K
Fused Multi-Domains and Adaptive Variational Mode Decomposition ECG Feature Extraction for Lightweight Bio-Inspired
Israel Edem Agbehadji1, Richard C Millham2, Emmanuel Freeman3
1Honorary Research Fellow, Faculty of Accounting and Informatics, Durban University of Technology, P.O. Box 1334, Durban 4000, South Africa.
Sensors (Basel, Switzerland)
|January 8, 2025
Summary
This study introduces a novel ECG-based security system using fused multi-domain features and adaptive Variational Mode Decomposition. It enhances data encryption robustness for the Internet of Medical Things.
Area of Science:
- Biometrics and Cybersecurity
- Signal Processing and Data Encryption
Background:
- Increasing security concerns with interconnected devices, especially in healthcare (Internet of Medical Devices).
- Limitations of traditional security methods (fingerprints, passwords) and existing ECG feature extraction techniques (time/frequency domains).
- The challenge of preserving intra-leading correlations in Variational Mode Decomposition for robust encryption.
Purpose of the Study:
- To develop a robust and lightweight encryption technique for sensitive data.
- To leverage unique human physiological signals (ECG) for secure key generation and data protection.
- To address the limitations of existing ECG feature extraction methods by incorporating multi-domain analysis.
Main Methods:
- Utilizing fused multi-domain Electrocardiogram (ECG) features.
- Applying adaptive Variational Mode Decomposition (VMD) to capture intra-leading correlations.
- Developing a lightweight encryption scheme using fused ECG features and a bio-inspired key generation technique.
- Evaluating performance with metrics like mean, standard deviation, skewness, kurtosis, and execution time (e.g., Chacha20 at 27µs).
Main Results:
- Successfully extracted ECG features with specific statistical properties (mean: 0.0004, std dev: 0.0391, skewness: 0.1562, kurtosis: 1.2205).
- Demonstrated the effectiveness of fused ECG features and adaptive VMD in mitigating the loss of intra-leading correlations.
- Proposed a lightweight encryption scheme with a bio-inspired key generation method.
Conclusions:
- The proposed method offers a robust and efficient approach to data encryption using ECG signals.
- Fusing multi-domain ECG features with adaptive VMD enhances the security and reliability of encryption algorithms.
- This bio-inspired encryption technique is suitable for securing data in the Internet of Medical Things and other sensitive applications.
Keywords:
ECG feature extractionadaptive variational mode decompositionbio-inspired key generationlightweight encryptiontime-domain feature extractionMore Related Videos
Related Concept Videos
01:28Electrocardiogram Fundamentals
502
Introduction
An electrocardiogram (ECG) is a diagnostic tool for identifying cardiac conditions such as arrhythmias, conduction abnormalities, and myocardial ischemia.
Definition
An electrocardiogram (ECG) visualizes the heart's electrical activity by tracing the electrical movement associated with each heartbeat on a graph or monitor. As the heart beats, an electrical wave passes through it, correlating with the cardiac cycle events.
Parts of an ECG
An ECG utilizes electrodes on the skin...
An electrocardiogram (ECG) is a diagnostic tool for identifying cardiac conditions such as arrhythmias, conduction abnormalities, and myocardial ischemia.
Definition
An electrocardiogram (ECG) visualizes the heart's electrical activity by tracing the electrical movement associated with each heartbeat on a graph or monitor. As the heart beats, an electrical wave passes through it, correlating with the cardiac cycle events.
Parts of an ECG
An ECG utilizes electrodes on the skin...
502
01:29Electrocardiogram
2.2K
An electrocardiogram (ECG or EKG) is a critical diagnostic tool that records the electrical signals produced by the heart during each heartbeat. This recording is achieved through electrodes placed strategically on the arms, legs, and chest. The electrocardiograph amplifies these signals and produces 12 distinct tracings, offering a comprehensive understanding of the heart's electrical activity.
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and...
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and...
2.2K
01:25Instrumentation Amplifier
441
An electrocardiography (ECG) machine is an essential piece of medical equipment used to monitor the electrical activity of the heart. It operates by detecting small electrical changes on the skin that result from the depolarization of the heart muscle during each heartbeat. However, these signals are in the microvolt range and can be easily overwhelmed by noise or interference.
To overcome this challenge, an ECG machine utilizes an instrumentation amplifier. This specialized amplifier is...
To overcome this challenge, an ECG machine utilizes an instrumentation amplifier. This specialized amplifier is...
441
01:25Correlation between ECG and Cardiac Cycle
3.4K
The electrical signals recorded on an electrocardiogram (ECG) occur before the mechanical processes of contraction and relaxation during the cardiac cycle.
A cardiac action potential originates in the SA node and spreads throughout the atria and the AV node in approximately 0.03 seconds. This results in the P wave in an ECG and triggers atrial contraction. The action potential is then briefly slowed at the AV node, allowing the atria to contract and fill the ventricles with blood before...
A cardiac action potential originates in the SA node and spreads throughout the atria and the AV node in approximately 0.03 seconds. This results in the P wave in an ECG and triggers atrial contraction. The action potential is then briefly slowed at the AV node, allowing the atria to contract and fill the ventricles with blood before...
3.4K