نشریه علمی مهندسی پزشکی زیستی
Iranian Journal of Biomedical Engineering (IJBME)

بررسی عمل‌کرد الگوریتم‌های فراابتکاری در استخراج پارامترهای مدل دینامیکی سیگنال ECG

نوع مقاله : مقاله کامل پژوهشی

نویسندگان

جواد دلاورمتنق 1
حامد داننده حصار 2
محمدهادی احمدی‌فام 1

1 دانشجوی کارشناسی، دانشکده‌ی مهندسی پزشکی، دانشگاه صنعتی سهند، تبریز، ایران

2 استادیار، گروه بیوالکتریک، دانشکده‌ی مهندسی پزشکی، دانشگاه صنعتی سهند، تبریز، ایران

https://doi.org/10.22041/ijbme.2023.1999546.1838
چکیده
در سال‌های اخیر استفاده از الگوریتم‌های مدل-پایه برای پردازش سیگنال ECG رواج گسترده‌ای یافته است. استخراج مدل دینامیکی ECG یکی از مراحل مهم در این الگوریتم­ها است که تاثیر مستقیمی بر عمل‌کرد آن‌ها دارد. پارامترهای موجود در این مدل را می­توان با استفاده از الگوریتم‌های بهینه­سازی محاسبه کرد. یکی از متداول‌ترین الگوریتم­ها در این زمینه یک الگوریتم غیرخطی آفلاین است که برای تقریب خوب مدل و پارامترهای آن به نقاطی از سیگنال ECG نیاز دارد که باید توسط کاربر به صورت دستی انتخاب شود. علاوه بر مشکل فوق، تابع هدف در این الگوریتم یک تابع پیچیده است که در صورت انتخاب نادرست نقاط مناسب برای بهینه‌سازی، خروجی مناسبی نخواهد داشت. در این مقاله یک الگوریتم جدید خودکار مبتنی بر الگوریتم‌های فراابتکاری معرفی شده است که نیازی به انتخاب دستی نقاط برای مدل‌سازی ECG ندارد. این الگوریتم پیشنهادی به دلیل ساده‌سازی فرایند بهینه‌سازی از دقت بالایی نسبت به الگوریتم بهینه­سازی غیرخطی آفلاین مورد اشاره برخوردار است. از آن‌جا که یک الگوریتم فراابتکاری ممکن است در برخی از مسائل بهینه‌سازی موفق و در برخی دیگر ناموفق عمل کند، در این مقاله عمل‌کرد 9 الگوریتم فراابتکاری متداول مانند ازدحام ذرات، کلونی زنبور عسل، جست‌وجوی فاخته و ... در استخراج پارامترهای مدل دینامیکی ECG مورد بررسی قرار گرفته است. جهت ارزیابی الگوریتم­ها از 200 سیگنال­ 30 ثانیه­ای مستخرج از پایگاه داده‌ی ریتم سینوس نرمال فیزیونت استفاده شده است. به منظور ارزیابی عمل‌کرد الگوریتم­ها، شباهت سیگنال‌های اصلی با سیگنال‌های مصنوعی ECG که توسط الگوریتم‌های بهینه­سازی ساخته­ شده مورد بررسی قرار گرفته است. نتایج بررسی­ها نشان داده است که سه الگوریتم جست‌وجوی فاخته، بهینه‌سازی مبتنی بر یادگیری و آموزش و بهینه‌سازی تبخیر آب بهترین عمل‌کرد را در استخراج پارامترهای مدل دینامیکی ECG دارند. نتایج حاصل از این مطالعه نشان داده که خطای میانگین مربعات (MSE) الگوریتم پیشنهادی با استفاده از سه الگوریتم فراابتکاری فوق  به ترتیب 50/1، 43/1 و 40/1 بوده در حالی که این مقدار برای الگوریتم بهینه­سازی غیرخطی آفلاین برابر با 82/4 است.

کلیدواژه‌ها

بهینه‌سازی فراابتکاری
پردازش سیگنال ECG
مدل دینامیکی ECG

موضوعات

عنوان مقاله English

Performance Investigation of Meta-Heuristic Algorithms in Estimation of ECG Dynamic Model Parameters

نویسندگان English

Javad Delavar Matanaq 1
Hamed Danandeh Hesar 2
Mohammad Hadi Ahmadi Fam 1
1 B.Sc. Student, Faculty of Biomedical Engineering, Sahand Univercsity of Technology, Tabriz, Iran
2 Assistant Professor, Faculty of Biomedical Engineering, Sahand University of Technology, Tabriz, Iran
چکیده English

In recent years, model-based ECG processing algorithms have been successfully developed in various fileds of ECG processing. The calculation of ECG dynamic model (EDM) is a crucial step for these methods. The EDM parameters can be calculated using optimization algorithms. One of the popular optimization methods in this field is an offline nonlinear method in which users have to manually select points on ECG signal in order to calculate EDM parameters. The objective function used in this algorithm is a complex function which is hard to optimize. In this paper an automatic optimization algorithm is proposed which uses meta-heuristic optimization algorithms to calculate EDM parameters. In this algorithm, we don’t need to select points manually. In addition, the objective function in this algorithm is broken in to several simple objective functions which makes the optimization more accurate. Meta-heuristic optimization algorithms may perform successfully on some optimization problems while failing on others. As a result, a specific algorithm cannot be considered the best optimizer for all optimization problems. For this reason, in this paper, the performances of nine popular meta-heuristic algorithms such as particle swarm optimization, artificial bee colony, cucko search, etc are investigated. In this paper, 200 ECG segments from different records of the MIT-BIH Normal Sinus Rhythm Database (NSRDB) have been selected for evaluation. The duration of each segment was 30 seconds. The EDM parameters for each segment were calculated using the aforemetinoned optimization algorithms. For evaluation, the similarities between the original signals and the synthetic ECG signals were inspected for each optimization algorithm. These synthetic signals were created using the calculated EDM parameters. The similarity results showed that the water evaporation optimization (WEO), teaching learning-based optimization (TLBO), and cucko’s search (CS) algorithms achived better results compared with other methods.

کلیدواژه‌ها English

Metaheuristic Optimization
ECG Processing
ECG Dynamic Model
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نشریه علمی مهندسی پزشکی زیستی
دوره 17، شماره 1
بهار 1402
صفحه 25-46

  • تاریخ دریافت 16 فروردین 1402
  • تاریخ بازنگری 12 مرداد 1402
  • تاریخ پذیرش 21 مرداد 1402

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