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      An overview on state-of-the-art electrocardiogram signal processing methods: Traditional to AI-based approaches

      , , ,
      Expert Systems with Applications
      Elsevier BV

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          The impact of the MIT-BIH Arrhythmia Database

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            A real-time QRS detection algorithm.

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              Dry-contact and noncontact biopotential electrodes: methodological review.

              Recent demand and interest in wireless, mobile-based healthcare has driven significant interest towards developing alternative biopotential electrodes for patient physiological monitoring. The conventional wet adhesive Ag/AgCl electrodes used almost universally in clinical applications today provide an excellent signal but are cumbersome and irritating for mobile use. While electrodes that operate without gels, adhesives and even skin contact have been known for many decades, they have yet to achieve any acceptance for medical use. In addition, detailed knowledge and comparisons between different electrodes are not well known in the literature. In this paper, we explore the use of dry/noncontact electrodes for clinical use by first explaining the electrical models for dry, insulated and noncontact electrodes and show the performance limits, along with measured data. The theory and data show that the common practice of minimizing electrode resistance may not always be necessary and actually lead to increased noise depending on coupling capacitance. Theoretical analysis is followed by an extensive review of the latest dry electrode developments in the literature. The paper concludes with highlighting some of the novel systems that dry electrode technology has enabled for cardiac and neural monitoring followed by a discussion of the current challenges and a roadmap going forward.
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                Author and article information

                Journal
                Expert Systems with Applications
                Expert Systems with Applications
                Elsevier BV
                09574174
                May 2023
                May 2023
                : 217
                : 119561
                Article
                10.1016/j.eswa.2023.119561
                7e51580e-34a8-4a75-9a50-cac32f3fe6eb
                © 2023

                https://www.elsevier.com/tdm/userlicense/1.0/

                https://doi.org/10.15223/policy-017

                https://doi.org/10.15223/policy-037

                https://doi.org/10.15223/policy-012

                https://doi.org/10.15223/policy-029

                https://doi.org/10.15223/policy-004

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