Authors: Kun Qian Jian Guo Huijie Xu Zhaomeng Zhu Gongxuan Zhang
Publish Date: 2014/09/11
Volume: 6, Issue: 3, Pages: 216-221
Abstract
Snore related signals SRS have been demonstrated to carry important information about the obstruction site and degree in the upper airway of Obstructive Sleep ApneaHypopnea Syndrome OSAHS patients in recent years To make this acoustic signal analysis method more accurate and robust big SRS data processing is inevitable As an emerging concept and technology cloud computing has motivated numerous researchers and engineers to exploit applications both in academic and industry field which could have an ability to implement a huge blue print in biomedical engineering Considering the security and transferring requirement of biomedical data we designed a system based on private cloud computing to process SRS Then we set the comparable experiments of processing a 5hour audio recording of an OSAHS patient by a personal computer a server and a private cloud computing system to demonstrate the efficiency of the infrastructure we proposed
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