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Cough detection algorithm for monitoring patient recovery from pulmonary tuberculosis

  • Brian H. Tracey(corresponding author)
    ,
  • Germán Comina
    ,
  • Sandra Larson
    ,
  • Marjory Bravard
    ,
  • ,
  • Robert H. Gilman
*Corresponding author for this work
  • Tufts University
    ,
  • Universidad Nacional de Ingeniería
    ,
  • Michigan State University
    ,
  • Massachusetts General Hospital
    ,
  • ,
  • Hospital Nacional Dos de Mayo
Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
Peer-review

Publication Information

Output type

Research Output:
Chapter in Book/Report/Conference proceeding
Conference contribution
Peer-review

Original language

English

Article number

6091487

Pages from-to (Number of pages)

Pages 6017-6020 (4 pages)

Publication milestones

  • Published - 2011

Publication status

Published - 2011

Publication series

  • Publication series name: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
    ISSN (Print): 1557-170X
9781424441211

Publication IDs

  • Scopus: 84862294342
  • PubMed: 22255711

Host publication title

33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011

Abstract

In regions of the world where tuberculosis (TB) poses the greatest disease burden, the lack of access to skilled laboratories is a significant problem. A lab-free method for assessing patient recovery during treatment would be of great benefit, particularly for identifying patients who may have drug-resistant tuberculosis. We hypothesize that cough analysis may provide such a test. In this paper we describe algorithm development in support of a pilot study of TB patient coughing. We describe several approaches to event detection and classification, and show preliminary data which suggest that cough count decreases after the start of treatment in drug-responsive patients. Our eventual goal is development of a low-cost ambulatory cough analysis system that will help identify patients with drug-resistant tuberculosis.

Funding Details

FundersFunding numbers
FIC
D43TW006581

Publication metrics

Metrics

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Citations
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Captures
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Sustainable Development Goals

  • SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well

Related Event

Title

33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011

Event type

Conference

Date

30/08/2011 - 03/09/2011

Location

Boston, MAUnited States