DocumentCode
3706224
Title
DeepCough: A deep convolutional neural network in a wearable cough detection system
Author
Justice Amoh;Kofi Odame
Author_Institution
Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, USA
fYear
2015
Firstpage
1
Lastpage
4
Abstract
In this paper, we present a system that employs a wearable acoustic sensor and a deep convolutional neural network for detecting coughs. We evaluate the performance of our system on 14 healthy volunteers and compare it to that of other cough detection systems that have been reported in the literature. Experimental results show that our system achieves a classification sensitivity of 95.1% and a specificity of 99.5%.
Keywords
"Hidden Markov models","Feature extraction","Mel frequency cepstral coefficient","Speech","Training","Microphones","Neural networks"
Publisher
ieee
Conference_Titel
Biomedical Circuits and Systems Conference (BioCAS), 2015 IEEE
Type
conf
DOI
10.1109/BioCAS.2015.7348395
Filename
7348395
Link To Document