Poster abstract: a mobile-cloud service for physiological anomaly detection on smartphones

Authors:
Dezhi Hong;Shahriar Nirjon;John A. Stankovic;David J. Stone;Guobin Shen
Affiliations:
University of Virginia, Charlottesville, VA, USA;University of Virginia, Charlottesville, VA, USA;University of Virginia, Charlottesville, VA, USA;University of Virginia, Charlottesville, VA, USA;Microsoft Research Asia, Beijing, China
Venue:
Proceedings of the 12th international conference on Information processing in sensor networks
Year:
2013

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Abstract

There is a growing number of examples that use the microphones in phone for various acoustic processing tasks as mobile phones become increasingly computationally powerful. However, there is no general physiological acoustic anomaly detection service on smartphones. To this end, we propose a physiological acoustic anomaly detection service which contains classifiers that can be used to detect irregularity and anomalies in lung sounds and notifies the user. We also present and discuss on some preliminary results.