Deep learning Algorithm for image classification of waveforms obtained from electrically stimulated hypoxic skeletal muscle bundles

Weston Upchurch, Alex Deakyne, David A. Ramirez, Paul A. Iaizzo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Acute compartment syndrome is a serious condition that requires urgent surgical treatment. While the current emergency treatment is straightforward - relieve intra-compartmental pressure via fasciotomy - the diagnosis is often a difficult one. A deep neural network is presented here that has been trained to detect whether isolated muscle bundles were exposed to hypoxic conditions and became ischemic.

Original languageEnglish (US)
Title of host publicationFrontiers in Biomedical Devices, BIOMED - 2020 Design of Medical Devices Conference, DMD 2020
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791883549
DOIs
StatePublished - 2020
Event2020 Design of Medical Devices Conference, DMD 2020 - Minneapolis, United States
Duration: Apr 6 2020Apr 9 2020

Publication series

NameFrontiers in Biomedical Devices, BIOMED - 2020 Design of Medical Devices Conference, DMD 2020

Conference

Conference2020 Design of Medical Devices Conference, DMD 2020
CountryUnited States
CityMinneapolis
Period4/6/204/9/20

Bibliographical note

Publisher Copyright:
Copyright © 2020 ASME

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Keywords

  • Compartment syndrome
  • Deep learning
  • Ischemia

Fingerprint Dive into the research topics of 'Deep learning Algorithm for image classification of waveforms obtained from electrically stimulated hypoxic skeletal muscle bundles'. Together they form a unique fingerprint.

Cite this