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Massachusetts Institute of Technology

Assisted auscultation : creation and visualization of high dimensional feature spaces for the detection of mitral regurgitation

Abstract

dc:description.abstract

Cardiac auscultation, listening to the heart using a stethoscope, often constitutes the first step in detection of common heart problems. Unfortunately, primary care physicians, who perform this initial screening, often lack the experience to correctly evaluate what they hear. False referrals are frequent, costing hundreds of dollars and hours of time for many patients. We report on a system we have built to aid medical practitioners in diagnosing Mitral Regurgitation (MR) based on heart sounds. Our work builds on the "prototypical beat" introduced by Syed in [17] to extract two different feature sets characterizing systolic acoustic activity. One feature set is derived from current medical knowledge. The other is based on unsupervised learning of systolic shapes, using component Analysis. Our system employs self-organizing maps (SOMs) to depict the distribution of patients in each feature space as labels within a two-dimensional colored grid. A user screens new patients by viewing their projections onto the SOM, and determining whether they are closer in space, and thus more similar, to patients with or without MR. We evaluated our system on 46 patients. Using a combination of the two feature sets, SOM-based diagnosis classified patients with accuracy similar to that of a cardiologist.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2006

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Leeds, Daniel Demeny
Advisor dc:contributor.advisor
  • John V. Guttag.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/36806
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/36806

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Leeds, Daniel Demeny. Assisted auscultation : creation and visualization of high dimensional feature spaces for the detection of mitral regurgitation. Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/36806