3
views
0
recommends
+1 Recommend
2 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Retracted: A Modified LSTM Framework for Analyzing COVID-19 Effect on Emotion and Mental Health during Pandemic Using the EEG Signals

      retraction
      Journal of Healthcare Engineering
      Hindawi

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          This article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process: Discrepancies in scope Discrepancies in the description of the research reported Discrepancies between the availability of data and the research described Inappropriate citations Incoherent, meaningless and/or irrelevant content included in the article Peer-review manipulation The presence of these indicators undermines our confidence in the integrity of the article's content and we cannot, therefore, vouch for its reliability. Please note that this notice is intended solely to alert readers that the content of this article is unreliable. We have not investigated whether authors were aware of or involved in the systematic manipulation of the publication process. In addition, our investigation has also shown that one or more of the following human-subject reporting requirements has not been met in this article: ethical approval by an Institutional Review Board (IRB) committee or equivalent, patient/participant consent to participate, and/or agreement to publish patient/participant details (where relevant). Wiley and Hindawi regrets that the usual quality checks did not identify these issues before publication and have since put additional measures in place to safeguard research integrity. We wish to credit our own Research Integrity and Research Publishing teams and anonymous and named external researchers and research integrity experts for contributing to this investigation. The corresponding author, as the representative of all authors, has been given the opportunity to register their agreement or disagreement to this retraction. We have kept a record of any response received.

          Related collections

          Most cited references1

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          A Modified LSTM Framework for Analyzing COVID-19 Effect on Emotion and Mental Health during Pandemic Using the EEG Signals

          COVID-19, a WHO-declared public health emergency of worldwide concern, is quickly spreading over the world, posing a physical and mental health hazard. The COVID-19 has resulted in one of the world's most significant worldwide lockdowns, affecting human mental health. In this research work, a modified Long Short-Term Memory (MLSTM)-based Deep Learning model framework is proposed for analyzing COVID-19 effect on emotion and mental health during the pandemic using electroencephalogram (EEG) signals. The participants of this study were volunteers that recovered from COVID-19. The EEG dataset of 40 people is collected to predict emotion and mental health. The results of the MLSTM model are also compared with the other literature classifiers. With an accuracy of 91.26%, the MLSTM beats existing classifiers when using the 70–30 partitioning technique.
            Bookmark

            Author and article information

            Contributors
            Journal
            J Healthc Eng
            J Healthc Eng
            JHE
            Journal of Healthcare Engineering
            Hindawi
            2040-2295
            2040-2309
            2023
            11 October 2023
            11 October 2023
            : 2023
            : 9816968
            Affiliations
            Article
            10.1155/2023/9816968
            10584423
            37860372
            c920fbbc-8f61-4bff-89d1-b3da04033772
            Copyright © 2023 Journal of Healthcare Engineering.

            This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

            History
            : 10 October 2023
            : 10 October 2023
            Categories
            Retraction

            Comments

            Comment on this article