A PCA/ICA based Fetal ECG Extraction from Mother Abdominal Recordings by Means of a Novel Data-driven Approach to Fetal ECG Quality Assessment
محل انتشار: مجله فیزیک و مهندسی پزشکی، دوره: 7، شماره: 1
سال انتشار: 1396
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 89
فایل این مقاله در 14 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_JBPE-7-1_005
تاریخ نمایه سازی: 30 دی 1402
چکیده مقاله:
Background: Fetal electrocardiography is a developing field that provides valuable information on the fetal health during pregnancy. By early diagnosis and treatment of fetal heart problems, more survival chance is given to the infant.Objective: Here, we extract fetal ECG from maternal abdominal recordings and detect R-peaks in order to recognize fetal heart rate. On the next step, we find a better and more qualified extracted fetal ECG by using a novel approach.Materials and Methods: In this paper, a PCA/ICA-based algorithm is proposed for extracting fetal ECG, and fetal R-peaks are detected as well. The method validates the quality of extracted ECGs and selects the best candidate fetal ECG to provide the required morphological ECG features such as fetal heart rate and RR interval for more clinical examinations. The method was evaluated using the dataset which was provided by PhysioNet/Computing in Cardiology Challenge ۲۰۱۳. The dataset consists of ۷۵ recordings of ۴-channel ECGs each containing ۱-minute length for training and ۱۰۰ similar recordings for testing.Results: When the proposed algorithm was applied to the test set, the scores of ۸۵.۸۵۳ bpm۲ for fetal heart rate and an error of ۹.۷۲۵ ms RMS for fetal RR-interval estimation were obtained.Conclusion: The results obtained with the mentioned algorithm shows the robustness of the research, and it is suggested to be used in practical fetal ECG monitoring systems.
کلیدواژه ها:
Fetal Electrocardiography (fECG) ، Fetal Heart Rate (FHR) ، Abdominal Electrocardiography ، Principal Component Analysis (PCA) ، Independent Component Analysis (ICA) ، Best Quality fECG
نویسندگان
A Karimi Rahmati
Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
S K Setarehdan
Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
B N Araabi
Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
مراجع و منابع این مقاله:
لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :