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
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"
Conference_Titel :
Biomedical Circuits and Systems Conference (BioCAS), 2015 IEEE
DOI :
10.1109/BioCAS.2015.7348395