AI-driven biomedical perspectives on mental fatigue in the post-COVID-19 Era: trends, research gaps, and future directions
Abstract Mental fatigue is a complex condition arising from various neurological processes and influenced by external factors such as stress and cognitive demands. This comprehensive review elucidates the primary neurological mechanisms underlying mental fatigue, particularly emphasizing how it was...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-08-01
|
| Series: | Journal of Big Data |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40537-025-01200-y |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849234466033106944 |
|---|---|
| author | Saba Parveen Md Belal Bin Heyat Umair Tariq Faijan Akhtar Hafiz Muhammad Zeeshan Seth Christopher Yaw Appiah Shang-Ming Zhou Huang Lei |
| author_facet | Saba Parveen Md Belal Bin Heyat Umair Tariq Faijan Akhtar Hafiz Muhammad Zeeshan Seth Christopher Yaw Appiah Shang-Ming Zhou Huang Lei |
| author_sort | Saba Parveen |
| collection | DOAJ |
| description | Abstract Mental fatigue is a complex condition arising from various neurological processes and influenced by external factors such as stress and cognitive demands. This comprehensive review elucidates the primary neurological mechanisms underlying mental fatigue, particularly emphasizing how it was elevated or otherwise affected during the COVID-19 pandemic. We explore the intricate relationship between prolonged cognitive tasks, chronic stress, and the development of mental fatigue, emphasizing the impacts that mental fatigue has on mental health across diverse populations. Utilizing advanced artificial intelligence techniques, including machine learning and deep learning, this study identifies and quantifies the patterns of mental fatigue. The innovative approach deployed in this study enhances our understanding of the complex interplay between mental fatigue and psychological disorders, uncovering potential predisposing factors and underlying mechanisms. A thorough bibliometric analysis highlights global research trends, key contributors, and emerging interdisciplinary methods in mental fatigue research. This paper identifies gaps in knowledge and methodological challenges. It proposes promising avenues for future investigations that emphasize multidisciplinary approaches and the development of novel diagnostic and treatment tools tailored to address mental fatigue. By integrating insights from neurological studies with the psychological implications of mental fatigue, this study aims to inform better interventions to improve mental health outcomes. Our findings have significant implications for healthcare professionals, researchers, and policymakers working to mitigate the impact of mental fatigue in various contexts. |
| format | Article |
| id | doaj-art-9bc5f1791c4a46199d3eaa6cab66e211 |
| institution | Kabale University |
| issn | 2196-1115 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Big Data |
| spelling | doaj-art-9bc5f1791c4a46199d3eaa6cab66e2112025-08-20T04:03:07ZengSpringerOpenJournal of Big Data2196-11152025-08-0112115010.1186/s40537-025-01200-yAI-driven biomedical perspectives on mental fatigue in the post-COVID-19 Era: trends, research gaps, and future directionsSaba Parveen0Md Belal Bin Heyat1Umair Tariq2Faijan Akhtar3Hafiz Muhammad Zeeshan4Seth Christopher Yaw Appiah5Shang-Ming Zhou6Huang Lei7College of Electronics and Information Engineering, Shenzhen UniversityCenBRAIN Neurotech Center of Excellence, School of Engineering, Westlake UniversityDepartment of Digital Media Technology, Faculty of Computing, Engineering and the Built Environment, Birmingham City UniversitySchool of Computer Science and Engineering, University of Electronic Science and Technology of ChinaDepartment of Computer Science, National College of Business Administration and EconomicsDepartment of Sociology and Social Work, Kwame Nkrumah University of Science and TechnologyCentre for Health Technology, Faculty of Health, University of PlymouthCollege of Electronics and Information Engineering, Shenzhen UniversityAbstract Mental fatigue is a complex condition arising from various neurological processes and influenced by external factors such as stress and cognitive demands. This comprehensive review elucidates the primary neurological mechanisms underlying mental fatigue, particularly emphasizing how it was elevated or otherwise affected during the COVID-19 pandemic. We explore the intricate relationship between prolonged cognitive tasks, chronic stress, and the development of mental fatigue, emphasizing the impacts that mental fatigue has on mental health across diverse populations. Utilizing advanced artificial intelligence techniques, including machine learning and deep learning, this study identifies and quantifies the patterns of mental fatigue. The innovative approach deployed in this study enhances our understanding of the complex interplay between mental fatigue and psychological disorders, uncovering potential predisposing factors and underlying mechanisms. A thorough bibliometric analysis highlights global research trends, key contributors, and emerging interdisciplinary methods in mental fatigue research. This paper identifies gaps in knowledge and methodological challenges. It proposes promising avenues for future investigations that emphasize multidisciplinary approaches and the development of novel diagnostic and treatment tools tailored to address mental fatigue. By integrating insights from neurological studies with the psychological implications of mental fatigue, this study aims to inform better interventions to improve mental health outcomes. Our findings have significant implications for healthcare professionals, researchers, and policymakers working to mitigate the impact of mental fatigue in various contexts.https://doi.org/10.1186/s40537-025-01200-yPsychological disorderMental fatigueArtificial intelligenceCOVID-19SignalBibliometric analysis |
| spellingShingle | Saba Parveen Md Belal Bin Heyat Umair Tariq Faijan Akhtar Hafiz Muhammad Zeeshan Seth Christopher Yaw Appiah Shang-Ming Zhou Huang Lei AI-driven biomedical perspectives on mental fatigue in the post-COVID-19 Era: trends, research gaps, and future directions Journal of Big Data Psychological disorder Mental fatigue Artificial intelligence COVID-19 Signal Bibliometric analysis |
| title | AI-driven biomedical perspectives on mental fatigue in the post-COVID-19 Era: trends, research gaps, and future directions |
| title_full | AI-driven biomedical perspectives on mental fatigue in the post-COVID-19 Era: trends, research gaps, and future directions |
| title_fullStr | AI-driven biomedical perspectives on mental fatigue in the post-COVID-19 Era: trends, research gaps, and future directions |
| title_full_unstemmed | AI-driven biomedical perspectives on mental fatigue in the post-COVID-19 Era: trends, research gaps, and future directions |
| title_short | AI-driven biomedical perspectives on mental fatigue in the post-COVID-19 Era: trends, research gaps, and future directions |
| title_sort | ai driven biomedical perspectives on mental fatigue in the post covid 19 era trends research gaps and future directions |
| topic | Psychological disorder Mental fatigue Artificial intelligence COVID-19 Signal Bibliometric analysis |
| url | https://doi.org/10.1186/s40537-025-01200-y |
| work_keys_str_mv | AT sabaparveen aidrivenbiomedicalperspectivesonmentalfatigueinthepostcovid19eratrendsresearchgapsandfuturedirections AT mdbelalbinheyat aidrivenbiomedicalperspectivesonmentalfatigueinthepostcovid19eratrendsresearchgapsandfuturedirections AT umairtariq aidrivenbiomedicalperspectivesonmentalfatigueinthepostcovid19eratrendsresearchgapsandfuturedirections AT faijanakhtar aidrivenbiomedicalperspectivesonmentalfatigueinthepostcovid19eratrendsresearchgapsandfuturedirections AT hafizmuhammadzeeshan aidrivenbiomedicalperspectivesonmentalfatigueinthepostcovid19eratrendsresearchgapsandfuturedirections AT sethchristopheryawappiah aidrivenbiomedicalperspectivesonmentalfatigueinthepostcovid19eratrendsresearchgapsandfuturedirections AT shangmingzhou aidrivenbiomedicalperspectivesonmentalfatigueinthepostcovid19eratrendsresearchgapsandfuturedirections AT huanglei aidrivenbiomedicalperspectivesonmentalfatigueinthepostcovid19eratrendsresearchgapsandfuturedirections |