DocumentCode :
1056021
Title :
An Automated System for 24-h Monitoring of Cough Frequency: The Leicester Cough Monitor
Author :
Matos, Sergio ; Birring, Surinder S. ; Pavord, Ian D. ; Evans, David H.
Author_Institution :
Univ. Hosp. of Leicester, Leicester
Volume :
54
Issue :
8
fYear :
2007
Firstpage :
1472
Lastpage :
1479
Abstract :
The objective monitoring of cough for extended periods of time has long been recognized as an important step towards a better understanding of this symptom, and a better management of chronic cough patients. In this paper, we present a system for the automatic analysis of 24-h, continuous, ambulatory recordings of cough. The system uses audio recordings from a miniature microphone and the detection algorithm is based on statistical models of the time-spectral characteristics of cough sounds. We validated the system against manual counts obtained by a trained observer on 40 ambulatory recordings and our results show a median sensitivity value of 85.7%, median positive predictive value of 94.7% and median false positive rate of 0.8 events/h. An analysis application was developed, with a graphical user interface, allowing the use of the system in clinical settings by technical or medical staff. The result of the analysis of a recording session is presented as a concise, graphical-based report. The modular nature of the system interface facilitates its enhancement with the integration of further modules.
Keywords :
audio recording; biomedical measurement; graphical user interfaces; hidden Markov models; medical signal detection; patient monitoring; pneumodynamics; statistical analysis; Leicester cough monitor; ambulatory recordings; audio recordings; automated monitoring system; biomedical signal detection; cough frequency monitoring; cough sounds; graphical user interface; hidden Markov models; miniature microphone; respiratory system; statistical models; time 24 h; time-spectral characteristics; Audio recording; Cardiology; Computerized monitoring; Detection algorithms; Electromyography; Frequency measurement; Hospitals; Microphones; Patient monitoring; Physics; Algorithms; biomedical monitoring; biomedical signal detection; cough; hidden Markov models; respiratory system; Algorithms; Auscultation; Cough; Diagnosis, Computer-Assisted; Equipment Design; Equipment Failure Analysis; Humans; Monitoring, Ambulatory; Signal Processing, Computer-Assisted; Sound Spectrography;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2007.900811
Filename :
4273612
Link To Document :
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