دوره 13، شماره 2 - ( 1-1401 )                   جلد 13 شماره 2 صفحات 0-0 | برگشت به فهرست نسخه ها


XML English Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Ahmadieh H, Ghassemi F. Assessing the Effects of Alzheimer’s disease on EEG Signals Using the Entropy Measure: a Meta-Analysis. BCN. 2022; 13 (2)
URL: http://bcn.iums.ac.ir/article-1-1869-fa.html
Assessing the Effects of Alzheimer’s disease on EEG Signals Using the Entropy Measure: a Meta-Analysis. مجله علوم اعصاب پایه و بالینی. 1401; 13 (2)

URL: http://bcn.iums.ac.ir/article-1-1869-fa.html


چکیده:  
Introduction and Aims: Alzheimer’s disease is the most prevalent neurodegenerative disorder and a type of dementia. 80% of dementia in older adults is because of Alzheimer’s disease. According to multiple research articles, Alzheimer's has several changes in EEG signals such as slowing of rhythms, reduction in complexity and reduction in functional associations, and disordered functional communication between different areas of the brain. This research focuses on the entropy parameter.
Materials and Methods: In this study, the keywords Entropy, EEG, and Alzheimer's were used. In the initial search, 102 research articles were found. In the first stage, after investigating the abstract of articles, the number of them was reduced to 62, and upon further review of the remaining articles, the number of articles was reduced to 18. Some papers have used more than one entropy of EEG signals for comparing and some of them have used more than one database. So 25 entropy measures were considered in this Meta-Analysis. We used the standardized mean difference (SMD) for finding the effect size to compare the effects of Alzheimer’s disease on the entropy of the EEG signal with healthy people. Funnel plots were used to investigate the bias of Meta-Analysis.
Conclusion:According to the articles, results and funnel plots of this Meta-Analysis, entropy seems to be a good benchmark for comparing the EEG signals in healthy people and people who have Alzheimer’s disease. It can be concluded that Alzheimer’s disease can significantly affect EEG signals and reduce the entropy of EEG signals.
 
نوع مطالعه: Original | موضوع مقاله: Computational Neuroscience
دریافت: 1399/5/2 | پذیرش: 1399/7/12 | انتشار: 1401/1/8

ارسال نظر درباره این مقاله : نام کاربری یا پست الکترونیک شما:
CAPTCHA

بازنشر اطلاعات
Creative Commons License این مقاله تحت شرایط Creative Commons Attribution-NonCommercial 4.0 International License قابل بازنشر است.

کلیه حقوق این وب سایت متعلق به Basic and Clinical Neuroscience می باشد.

طراحی و برنامه نویسی : یکتاوب افزار شرق

© 2022 CC BY-NC 4.0 | Basic and Clinical Neuroscience

Designed & Developed by : Yektaweb