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      Bio-signal data sharing security through watermarking: a technical survey

      research-article
      , ,
      Computing
      Springer Vienna
      Data hiding, Watermarking, Steganography, Bio signals, Security, 68U10

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          Abstract

          Due to smart healthcare systems highly connected information and communications technologies, sensitive medical information and records are easily transmitted over the networks. However, stealing of healthcare data is increasing crime every day to greatly impact on financial loss. In order to this, researchers are developing various cost-effective bio-signal based data hiding techniques for smart healthcare applications. In this paper, we first introduce various aspects of data hiding along with major properties, generic embedding and extraction process, and recent applications. This survey provides a comprehensive survey on data hiding techniques, and their new trends for solving new challenges in real-world applications. Then, we survey the various notable bio-signal based data hiding techniques. The summary of some notable techniques in terms of their objective, type of data hiding, methodology and database used, performance metrics, important features, and limitations are also presented in tabular form. At the end, we discuss the major issues and research directions to explore the promising areas for future research.

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          Most cited references54

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          Fast Discrete Curvelet Transforms

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            Is Open Access

            A review on wearable photoplethysmography sensors and their potential future applications in health care

            Photoplethysmography (PPG) is an uncomplicated and inexpensive optical measurement method that is often used for heart rate monitoring purposes. PPG is a non-invasive technology that uses a light source and a photodetector at the surface of skin to measure the volumetric variations of blood circulation. Recently, there has been much interest from numerous researchers around the globe to extract further valuable information from the PPG signal in addition to heart rate estimation and pulse oxymetry readings. PPG signal’s second derivative wave contains important health-related information. Thus, analysis of this waveform can help researchers and clinicians to evaluate various cardiovascular-related diseases such as atherosclerosis and arterial stiffness. Moreover, investigating the second derivative wave of PPG signal can also assist in early detection and diagnosis of various cardiovascular illnesses that may possibly appear later in life. For early recognition and analysis of such illnesses, continuous and real-time monitoring is an important approach that has been enabled by the latest technological advances in sensor technology and wireless communications. The aim of this article is to briefly consider some of the current developments and challenges of wearable PPG-based monitoring technologies and then to discuss some of the potential applications of this technology in clinical settings.
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              Removal of Artifacts from EEG Signals: A Review

              Electroencephalogram (EEG) plays an important role in identifying brain activity and behavior. However, the recorded electrical activity always be contaminated with artifacts and then affect the analysis of EEG signal. Hence, it is essential to develop methods to effectively detect and extract the clean EEG data during encephalogram recordings. Several methods have been proposed to remove artifacts, but the research on artifact removal continues to be an open problem. This paper tends to review the current artifact removal of various contaminations. We first discuss the characteristics of EEG data and the types of different artifacts. Then, a general overview of the state-of-the-art methods and their detail analysis are presented. Lastly, a comparative analysis is provided for choosing a suitable methods according to particular application.
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                Author and article information

                Contributors
                amit_245singh@yahoo.com
                Journal
                Computing
                Computing
                Springer Vienna (Vienna )
                0010-485X
                1436-5057
                6 January 2021
                : 1-35
                Affiliations
                GRID grid.444650.7, ISNI 0000 0004 1772 7273, Department of CSE, , NIT Patna, ; Patna, Bihar India
                Author information
                http://orcid.org/0000-0001-7359-2068
                Article
                881
                10.1007/s00607-020-00881-y
                7786322
                4a7f41a4-6cb1-4083-82b7-1947176dede5
                © The Author(s), under exclusive licence to Springer-Verlag GmbH, AT part of Springer Nature 2021

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                History
                : 14 August 2020
                : 23 November 2020
                Categories
                Special Issue Article

                data hiding,watermarking,steganography,bio signals,security,68u10

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