RA-SAX: Resource-aware symbolic aggregate approximation for mobile ECG analysis

Proceedings - IEEE International Conference on Mobile Data Management

Volumn 1, Issue , 2011, Pages 289-290

  Tayebi, Hossein ^a   Krishnaswamy, Shonali ^a   Waluyo, Augustinus Borgy ^a   Sinha, Abhijat ^a   Gaber, Mohamed Medhat ^b  

^a MONASH UNIVERSITY   (Australia)

^b UNIVERSITY OF PORTSMOUTH   (United Kingdom)

Author keywords

ECG; Mobile Devices; Time Series

Indexed keywords

CARDIAC MONITORING; COMMERCIAL-OFF-THE-SHELF; ECG ANALYSIS; ENERGY EFFICIENT; REAL-TIME ECG ANALYSIS; RESOURCE AWARE; SERIES ANALYSIS; SIGNAL PROCESSING TECHNIQUE; STATE OF THE ART;

BIOSENSORS; ELECTROCARDIOGRAPHY; ENERGY EFFICIENCY; INFORMATION MANAGEMENT; MOBILE DEVICES; SIGNAL PROCESSING; TIME SERIES;

TIME SERIES ANALYSIS;

EID: 82055185235     PISSN: 15516245     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/MDM.2011.67     Document Type: Conference Paper

References (4)

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2. C. Bill, K. Eamonn, and L. Stefano, "Probabilistic discovery of time series motifs," in 9th ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining, Washington, DC, USA, 2003, pp. 493 - 498.
3. M. Gaber, S. Krishnaswamy, and A. Zaslavsky, "On-board Mining of Data Streams in Sensor Networks," in Advanced Methods for Knowledge Discovery from Complex Data, L. Jain and X. Wu, Eds.: Springer London, 2005, pp. 307-335.
4. Sinha, A., Tayebi, S., Krishnaswamy, S., Waluyo, A, B., and Gaber, M, M., (2011), "Resource-Aware ECG Analysis on Mobile Devices", Proc. of the ACM Symposium on Applied Computing - Data Streams Track, Tawain, Mar 22-25, ACM.