Abstract
Recently, snore signals (SS) have been demonstrated carrying significant information about the obstruction site and degree in the upper airway of Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) suffers. To make this acoustic based method more accurate and robust, big SS data processing and analysis are necessary. Cloud computing has the potential to enhance decision agility and productivity while enabling greater efficiencies and reducing costs. We look to cloud computing as the structure to support processing big SS data. In this paper, we focused on the aspects of a Cloud environment that processing big SS data using software services hosted in the Cloud. Finally, we set up a group of comparable experiments to evaluate the performance of our proposed system with different system scales.
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Guo, J., Qian, K., Zhu, Z., Zhang, G., Xu, H. (2013). A Cloud Computing System for Snore Signals Processing. In: Wu, C., Cohen, A. (eds) Advanced Parallel Processing Technologies. APPT 2013. Lecture Notes in Computer Science, vol 8299. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45293-2_27
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DOI: https://doi.org/10.1007/978-3-642-45293-2_27
Publisher Name: Springer, Berlin, Heidelberg
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