Hierarchical multiple sensor fusion using structurally learned Bayesian network

Proceedings - Wireless Health 2010, WH'10

Volumn , Issue , 2010, Pages 174-183

  Zhang, Lei ^a   Tamminedi, Tejaswi ^a   Ganguli, Anurag ^a   Yosiphon, Guy ^a   Yadegar, Jacob ^a  

^a UTOPIACOMPRESSION CORPORATION   (United States)

Author keywords

Bayesian network; classification; feature extraction; hierarchical sensor fusion; structure learning; wireless networking

Indexed keywords

BAYESIAN CLASSIFIER; CLASSIFICATION; CONVENTIONAL APPROACH; FEATURE LEVEL; FEATURE SELECTION; HEALTH CONDITION; HEALTH MONITORING; HIERARCHICAL SENSOR FUSION; HILL CLIMBING; HYBRID STRUCTURE; LOCAL OPTIMA; LOCAL STRUCTURE; MULTIPLE SENSOR FUSION; MULTIPLE SENSORS; RANDOM PERTURBATIONS; RANDOM STRUCTURES; SENSOR FUSION; STRUCTURE LEARNING; WIRELESS NETWORKING;

CLASSIFIERS; DISTRIBUTED PARAMETER NETWORKS; FEATURE EXTRACTION; HEALTH; INFERENCE ENGINES; INTELLIGENT NETWORKS; SENSORS; SPEECH RECOGNITION; WIRELESS NETWORKS;

BAYESIAN NETWORKS;

EID: 79951597455     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1921081.1921102     Document Type: Conference Paper

References (31)

1. David L Hall and James Llinas 2001. Handbook of multisensor data fusion, Boca Raton, FL : CRC Press.
2. Rick S. Blum and Zheng Liu 2005. Multi-Sensor Image Fusion and Its Applications, CRC, 1 edition.
3. D. Strömberg 2000. A multi-level approach to sensor management, In Sensor Fusion: Architectures, Algorithms and Applications IV, Proceedings of SPIE 4051, 456-461.
4. J. Braun 2000. Dempster-Shafer theory and Bayesian reasoning in multisensor data fusion, In Sensor Fusion: Architectures, Algorithms and Applications IV; Proceedings of SPIE 4051, 255-266.
5. Jahn, E., M. Hatch, and J. Kaina 1999. Fusion of Multi- Sensor Information from an Autonomous Undersea Distributed Field of Sensors, In Proceedings of Fusion '99 Conference, July, Sunnyvale, CA.
6. H.B. Mitchell 2007. Multi-Sensor Data Fusion: An Introduction, Springer, 1 edition.
7. Martin E. Liggins, David L. Hall, James Llinas, Eds., 2008. Handbook of Multisensor Data Fusion: Theory and Practice, CRC Press, 2 edition.
8. David L. Hall, Sonya A. H. McMullen 2004. Mathematical Techniques in Multisensor Data Fusion (Artech House Information Warfare Library), Artech Print on Demand, 2 edition.
9. Don Koks, Subhash Challa 2003. An introduction to bayesian and dempster-shafer data fusion. Defence Science and Tech Org. DOI = http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.111.739&rep= rep1&type=pdf .
10. Dempster, A. P. 1967. Upper and lower probabilities induced by a multivalued mapping. The Annals of Mathematical Statistics, 38 (2): 325-339.
11. Pearl, Judea 1988. Probabilistic reasoning in intelligent systems: networks of plausible inference, Morgan-Kaufmann Publishers Inc.
12. Jensen, Finn V. 2001. Bayesian networks and decision graphs, Springer-Verlag, New York.
13. Jingyuan Li, Tejaswi Tamminedi, Guy Yosiphon, Anurag Ganguli, Lei Zhang, Jacob Yadegar, John Stankovic 2010. Remote Physiological Monitoring of First Responders with Intermittent Network Connectivity, accepted by Wireless Health 2010.
14. Goldberger AL, Amaral LAN, Glass L, Hausdorff JM, Ivanov PCh, Mark RG, Mietus JE, Moody GB, Peng C-K, Stanley HE 2000. PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals. Circulation, Vol. 101, No. 23, e215-e220 [Circulation Electronic Pages; DOI = http://circ.ahajournals.org/cgi/content/full/101/23/e215].
15. Jennifer A. Healey. Stress Recognition in Automobile Drivers, DOI = http://physionet.org/physiobank/database/drivedb/.
16. Y Ichimaru, GB Moody 1999. Development of the polysomnographic database on CD-ROM. Psychiatry and Clinical Neurosciences, Vol. 53, 175-177. DOI = http://www.physionet.org/physiobank/database/slpdb/.
17. Healey JA 2000. Wearable and automotive systems for affect recognition from physiology. MIT Dept. of Electrical Engineering and Computer Science, Ph.D. thesis.
18. Welch, P.D. 1967. The Use of Fast Fourier Transform for the Estimation of Power Spectra: A Method Based on Time Averaging Over Short, Modified Periodograms. IEEE Trans. Audio Electroacoust. Vol. AU-15, 70-73.
19. Philip de Chazal, M. O'Dwyer, R. B. Reilly 2004. Automatic classification of heartbeats using ECG morphology and heartbeat interval features, Biomedical Engineering, IEEE Transactions on, Vol. 51, No. 7, 1196-1206. (Pubitemid 38787925)
20. Gari D. Clifford, Francisco Azuaje, Patrick McSharry 2006. Advanced Methods And Tools for ECG Data Analysis, Artech House Publishers, 1 edition.
21. J. Pan and Willis J. Tompkins 1985, A Real-Time QRS Detection Algorithm, IEEE Transactions on Biomedical Engineering, Vol. BME-32, No. 3, 230-236.
22. Peng, C.-K.; Buldyrev, S. V.; Havlin, S.; Simons, M.; Stanley, H. E.; Goldberger, A. L. 1994. Mosaic organization of DNA nucleotides, Physical Review E (Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics), Vol. 49, No. 2, 1685-1689.
23. Bunde A. and Havlin S., Eds., 1996. Fractals and Disordered Systems, Springer, Berlin, Heidelberg, New York.
24. Feng Tan, Xuezheng Fu, Yanqing Zhang, Anu G. Bourgeois 2009. A genetic algorithm-based method for feature subset selection, Soft Computing - A Fusion of Foundations, Methodologies and Applications, Vol. 12, No. 2, 111-120.
25. Hassan Chouaib, Oriol Ramos-Terrades, Salvatore Tabbone, Florence Cloppet, Nicole Vincent 2008, Feature selection combining genetic algorithm and Adaboost classifier, In Proceedings of 19th International Conference on Pattern Recognition, 1-4.
26. Hanchuan Peng, Fuhui Long, Chris Ding 2005. Feature selection based on mutual information: Criteria of max-dependency, max-relevance, and min-redundancy. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 27, 1226-1238.
27. E.J. Keogh and M.J. Pazzani 1999. Learning Augmented Bayesian Classifiers: A Comparison of Distribution-Based and Classification-Based Approaches, In Proc. Int'l Workshop Artificial Intelligence and Statistics, 225-230.
28. Hanchuan Peng, Chris Ding 2003. Structure Search and Stability Enhancement of Bayesian Networks, In Proceedings of the Third IEEE International Conference on Data Mining (ICDM'03), 621-624.
29. Gregory F. Cooper, Edward Herskovits 1992. A Bayesian Method for the Induction of Probabilistic Networks from Data, Machine Learning, Vol. 9, 309-347.
30. Mark Hall, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, Ian H. Witten 2009. The WEKA Data Mining Software: An Update, SIGKDD Explorations, Vol. 11, No. 1, DOI = http://www.cs.waikato.ac.nz/ml/weka/.
31. J. Platt 1998. Fast Training of Support Vector Machines using Sequential Minimal Optimization. Advances in Kernel Methods - Support Vector Learning, B. Schölkopf, C. Burges, and A. Smola, eds., MIT Press.