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دوره 9، شماره 3 - ( فصلنامه تخصصی انجمن ارگونومی و مهندسی عوامل انسانی ایران 1400 )                   جلد 9 شماره 3 صفحات 18-1 | برگشت به فهرست نسخه ها

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Zakerian S A, Kouhnavard B. Application of Electroencephalography (EEG) in Ergonomics: A systematic review study. Iran J Ergon. 2022; 9 (3) :1-18
URL: http://journal.iehfs.ir/article-1-833-fa.html
ذاکریان سید ابوالفضل، کوهنورد بهرام. کاربرد الکتروانسفالوگرافی (EEG) در ارگونومی: مطالعه مروری نظام‌مند. مجله ارگونومی. 1400; 9 (3) :18-1

URL: http://journal.iehfs.ir/article-1-833-fa.html


1- استاد، گروه مهندسی بهداشت حرفه‌ای، دانشکده بهداشت، دانشگاه علوم پزشکی تهران، تهران، ایران.
2- مرکز پژوهش‌های علمی دانشجویان، دانشگاه علوم پزشکی تهران، تهران، ایران ، bahramk2011@gmail.com
چکیده:   (906 مشاهده)
زمینه و هدف: الکتروآنسفالوگرافی ازجمله روش‌های غیرتهاجمی و نسبتاً ارزان است که می‌تواند جهت ارزیابی نوروفیزیولوژی و عملکردهای شناختی مورداستفاده قرار گیرد. این مطالعه مروری سیستماتیک باهدف کاربرد الکتروانسفالوگرافی (EEG) در علم ارگونومی انجام شد.
 
روش ­کار: در این مطالعه مروری، کلیه مقالات چاپ‌شده به زبان فارسی و انگلیسی درزمینه کاربرد الکتروانسفالوگرافی در ارگونومی از بازه زمانی 1 فروردین 1389 لغایت 1 فروردین 1400 (march 2010  20تا 21 march 2021) موردبررسی قرار گرفتند. برای این منظور جستجوی نظام‌مند مقالات با استفاده از کلمات کلیدی ارگونومی شناختی، خستگی ذهنی، الکتروانسفالوگرافی، EEG و امواج مغزی در پایگاه‌های اطلاعاتی PubMed, Google Scholar, Web of science, SID, Scopus, Magiran Iran Medex انجام گردید.
 
یافته‌ها: بیشتر مطالعات طی سال‌های 2015 تا 2020 صورت گرفته است (41 مقاله) و اکثر افراد موردمطالعه نیز رانندگان خودرو بودند. مقالات انتخاب‌شده در هفت حیطه خستگی ذهنی، بارکاری ذهنی، تلاش ذهنی، خستگی دیداری، بار حافظه کاری، احساسات و استرس و تشخیص خطا مورد بررسی قرار گرفتند. مجله Perceptual and Motor Skills و بعد از آن Applied Ergonomics بیشترین تعداد مقالات مربوطه را منتشر کرده بودند.
 
نتیجه گیری: در مطالعات بررسی‌شده ارزیابی حالات روانی فرد، به‌ویژه هنگام رانندگی با یک وسیله نقلیه، بیشتر موردمطالعه قرارگرفته است و از طریق آن کارهای ردیابی، نظارت و کارهای مختلف حافظه کاری دنبال شده است. تحقیقات آینده باید بر استفاده از روش‌های محاسباتی متمرکز باشد که ماهیت پویا و غیرثابت داده‌های EEG را در نظر می‌گیرند. چنین رویکردی می‌تواند توسعه سیستم‌های تشخیص خستگی و سیستم‌های تطبیقی خودکار را تسهیل کند.
متن کامل [PDF 885 kb]   (237 دریافت)    
نوع مطالعه: پژوهشي | موضوع مقاله: سایر موارد
دریافت: 1400/5/10 | پذیرش: 1400/10/14 | انتشار الکترونیک: 1400/11/10

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