Assistive technology using regurgitation fraction and fractional-order integration to assess pulmonary valve insufficiency for pre-surgery decision making and post-surgery outcome evaluation

Wei Ling Chen, Chia Hung Lin, Jieh Neng Wang, Pong Jeu Lu, Ming Yao Chan, Jui Te Wu, Chung Dann Kan

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)247-257
Number of pages11
JournalBiomedical Signal Processing and Control
Volume44
DOIs
Publication statusPublished - 2018 Jul

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Health Informatics

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