Mean Pressure Gradient Prediction Based on Chest Angular Movements and Heart Rate Variability Parameters

Arash Shokouhmand, Chenxi Yang, Nicole D. Aranoff, Elissa Driggin, Philip Green, Negar Tavassolian

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

This study presents our recent findings on the classification of mean pressure gradient using angular chest movements in aortic stenosis (AS) patients. Currently, the severity of aortic stenosis is measured using ultra-sound echocardiography, which is an expensive technology. The proposed framework motivates the use of low-cost wearable sensors, and is based on feature extraction from gyroscopic readings. The feature space consists of the cardiac timing intervals as well as heart rate variability (HRV) parameters to determine the severity of disease. State-of-the-art machine learning (ML) methods are employed to classify the severity levels into mild, moderate, and severe. The best performance is achieved by the Light Gradient-Boosted Machine (Light GBM) with an F1-score of 94.29% and an accuracy of 94.44%. Additionally, game theory-based analyses are employed to examine the top features along with their average impacts on the severity level. It is demonstrated that the isovolumetric contraction time (IVCT) and isovolumetric relaxation time (IVRT) are the most representative features for AS severity.Clinical Relevance - The proposed framework could be an appropriate low-cost alternative to ultra-sound echocardiography, which is a costly method.

Original languageEnglish
Title of host publication43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
Pages7170-7173
Number of pages4
ISBN (Electronic)9781728111797
DOIs
StatePublished - 2021
Event43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021 - Virtual, Online, Mexico
Duration: 1 Nov 20215 Nov 2021

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021
Country/TerritoryMexico
CityVirtual, Online
Period1/11/215/11/21

Fingerprint

Dive into the research topics of 'Mean Pressure Gradient Prediction Based on Chest Angular Movements and Heart Rate Variability Parameters'. Together they form a unique fingerprint.

Cite this