کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6950800 | 1451636 | 2018 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Assistive technology using regurgitation fraction and fractional-order integration to assess pulmonary valve insufficiency for pre-surgery decision making and post-surgery outcome evaluation
ترجمه فارسی عنوان
تکنولوژی کمک کننده با استفاده از کریستال رگورژیتی و یکپارچگی تقسیم بندی جهت ارزیابی نارسایی شیر ریوی برای تصمیم گیری قبل از جراحی و ارزیابی نتیجه پس از جراحی
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کلمات کلیدی
نارسایی دریچه ریوی، کسری رگورژیتی، بهره وری پمپ قلب، یکپارچگی جزئی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
پردازش سیگنال
چکیده انگلیسی
Valvular heart diseases in pulmonary valves may exhibit different degrees of aortic stenosis or congenital defects. Valve repair or replacement surgery is one of the important procedures commonly performed to relieve valvular dysfunction and improve the significant regurgitation. Hence, it is necessary to assess pulmonary valve insufficiency for pre-surgery decision-making and post-surgery outcome evaluation. This study proposes an assistive technology to quantify regurgitation using the regurgitation fraction (RF) and heart pump efficiency (HPE). In signal preprocessing stage, the detrending and zero-crossing processes are used to remove the unwanted flow fluctuations and identify the end-systolic and end-diastolic periods per each cardiac cycle. The fractional-order integrations are employed to calculate the stroke volume (SV) and regurgitation volume (RV). Then, the regurgitation flow can be quantified that indicates the high correlation with HPE. For a mimicking pulmonary circulation loop system, the proposed screening model can be validated to assess the valve stent efficacy. Experimental results also indicate that pulmonary valve replacement, such as handmade trileaflet valves, can improve severe pulmonary regurgitations. Combining the noninvasive measurement device and the proposed screening model can provide an accurate assessment in clinical applications.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biomedical Signal Processing and Control - Volume 44, July 2018, Pages 247-257
Journal: Biomedical Signal Processing and Control - Volume 44, July 2018, Pages 247-257
نویسندگان
Wei-Ling Chen, Chia-Hung Lin, Jieh-Neng Wang, Pong-Jeu Lu, Ming-Yao Chan, Jui-Te Wu, Chung-Dann Kan,