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CoughLoc: Location-Aware Indoor Acoustic Sensing for Non-Intrusive Cough Detection
International Workshop on Emerging Mobile Sensing Technologies, Systems, and Applications (2011)
  • Zheng Sun, Carnegie Mellon University
  • Aveek Purohit, Carnegie Mellon University
  • Kathleen Yang
  • Neha Pattan, Carnegie Mellon University
  • Dan Siewiorek, Carnegie Mellon University
  • Asim Smailagic, Carnegie Mellon University
  • Ian Lane, Carnegie Mellon University
  • Pei Zhang, Carnegie Mellon University
Abstract

Pervasive medical monitoring has become an ideal alter- native to nursing care for elderly people and patients in hospitals. Existing systems using single body-worn sensors are often intrusive and less reliable. By contrast, ubiqui- tous acoustic sensing techniques can support non-intrusive and robust medical monitoring. In this paper, we describe CoughLoc, a ubiquitous acoustic sensing system for con- tinuous cough detection using a wireless sensor network. We show how knowledge of sound source locations can be leveraged to improve the detection accuracy of sound events caused by mobile users. Experiments in indoor environ- ments show our system achieves over 90% cough detection performance under quiet backgrounds, and 1.6 times higher performance compared to a baseline approach with no loca- tion information.

Publication Date
Summer June 21, 2011
Citation Information
Zheng Sun, Aveek Purohit, Kathleen Yang, Neha Pattan, et al.. "CoughLoc: Location-Aware Indoor Acoustic Sensing for Non-Intrusive Cough Detection" International Workshop on Emerging Mobile Sensing Technologies, Systems, and Applications (2011)
Available at: http://works.bepress.com/zhengs/2/