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Massachusetts Institute of Technology

Waveform-to-patient matching across room transfers in the emergency department

Abstract

dc:description.abstract

In the emergency department (ED), patients are often continuously monitored for physiologic deterioration. Signals used include electrocardiograms (ECGs), blood pressure waveforms, and respiratory waveforms. Due to the fast-paced and ambulatory nature of care in the ED, patient location is not always synchronized with waveform collection. The aim of our work is to link disparate waveforms belonging to the same patient. We utilize approximate admission and discharge times available from the ED administration database to delineate patient stays. We then use waveform-derived features of the ECG to link together sequential signals which are separated by variable time delays. The ultimate goal is to construct an openly available database of ED records with linked waveforms to stimulate research in emergency medicine.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2018

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Li, Andrea (Andrea Shao-Yin)
Advisor dc:contributor.advisor
  • Roger Mark.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/119739
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/119739

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

Li, Andrea (Andrea Shao-Yin). Waveform-to-patient matching across room transfers in the emergency department. Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/119739