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Journal ArticleDOI

A reversible and multipurpose ECG data hiding technique for telemedicine applications

TLDR
A completely reversible data hiding method for ECG (Electrocardiogram) data that can find out false ownership claims as well as detect the tampered region of ECG data and 100% reversibility is proposed.
About
This article is published in Pattern Recognition Letters.The article was published on 2019-07-01. It has received 42 citations till now. The article focuses on the topics: Information hiding & Signal-to-noise ratio.

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Citations
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Journal ArticleDOI

An Intelligent Cognitive-Inspired Computing with Big Data Analytics Framework for Sentiment Analysis and Classification

TL;DR: New cognitive computing with the big data analysis tool for Sentiment Analysis is presented and improved classification performance of the proposed BBSO-FCM model is highlighted in terms of different measures.
Journal ArticleDOI

An Intelligent Cognitive-Inspired Computing with Big Data Analytics Framework for Sentiment Analysis and Classification

TL;DR: In this paper , Sentiment Analysis (SA) is employed to understand such linguistic based tweets, feature extraction, compute subjectivity and sentimental texts placed in these tweets, which is useful for businesses to take commercial benefits insight from textoriented content.
Journal ArticleDOI

A Comprehensive Study of Reversible Data Hiding (RDH) Schemes Based on Pixel Value Ordering (PVO)

TL;DR: A comprehensive study of all the existing PVO based RDH schemes along with comparative analysis of different PVO-based RDH scheme using two key parameters—embedding capacity and marked image quality, is presented.
Journal ArticleDOI

Encryption of ECG signals for telemedicine applications

TL;DR: The paper presents three cryptosystems for ECG signal encryption based on the fusion of ECG signals with other masking signals that are rich in activities such as speech signals, which saves much time and is more immune to both noise and hacking scenarios.
Journal ArticleDOI

ECG steganography based on tunable Q‐factor wavelet transform and singular value decomposition

TL;DR: The article presents a novel ECG steganography scheme based on the tunable Q‐factor wavelet transformation (TQWT) and also singular value decomposition (SVD) techniques that ensure better safety and confidentiality of patient information.
References
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Journal ArticleDOI

PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals.

TL;DR: The newly inaugurated Research Resource for Complex Physiologic Signals (RRSPS) as mentioned in this paper was created under the auspices of the National Center for Research Resources (NCR Resources).
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The impact of the MIT-BIH Arrhythmia Database

TL;DR: The history of the database, its contents, what is learned about database design and construction, and some of the later projects that have been stimulated by both the successes and the limitations of the MIT-BIH Arrhythmia Database are reviewed.
Journal ArticleDOI

Reversible data embedding using a difference expansion

TL;DR: The redundancy in digital images is explored to achieve very high embedding capacity, and keep the distortion low, in a novel reversible data-embedding method for digital images.
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Expansion Embedding Techniques for Reversible Watermarking

TL;DR: The experimental results for many standard test images show that prediction-error expansion doubles the maximum embedding capacity when compared to difference expansion, and there is a significant improvement in the quality of the watermarked image, especially at moderate embedding capacities.
Journal ArticleDOI

Deep learning for healthcare applications based on physiological signals: A review.

TL;DR: This review paper depicts the application of various deep learning algorithms used till recently, but in future it will be used for more healthcare areas to improve the quality of diagnosis.
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