Detecting and rectifying anomalies in body sensor networks

Proceedings - 2011 International Conference on Body Sensor Networks, BSN 2011

Volumn , Issue , 2011, Pages 162-167

  Sagha, Hesam ^a   Del R Millan, Jose ^a   Chavarriaga, Ricardo ^a  

^a EPFL   (Switzerland)

Author keywords

Activity recognition; Anomaly detection and compensation; Classifier fusion; Intelligent sensor nodes; Onbody sensor network

Indexed keywords

ACTIVITY RECOGNITION; ANOMALY DETECTION; CLASSIFIER FUSION; INTELLIGENT SENSORS; ON-BODY;

DEGRADATION; DISTILLATION; SENSOR NETWORKS; SENSOR NODES; SENSORS; TELECOMMUNICATION EQUIPMENT;

BODY SENSOR NETWORKS;

EID: 80051983079     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BSN.2011.34     Document Type: Conference Paper

References (13)

1. V. Chandola, A. Banerjee, and V. Kumar, "Anomaly detection: A survey," ACM Comput. Surv., vol. 41, no. 3, pp. 1-58, 2009.
2. K. Kunze and P. Lukowicz, "Dealing with sensor displacement in motion-based onbody activity recognition systems," in Proceedings of the 10th international conference on Ubiquitous computing, 2008, pp. 20-29.
3. K. Förster, P. Brem, D. Roggen, and G. Troster, "Evolving discriminative features robust to sensor displacement for activity recognition in body area sensor networks," in 5th International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), 2009, pp. 43-48.
4. U. Steinhoff and B. Schiele, "Dead reckoning from the pocket - an experimental study," in IEEE Int Conf Pervasive Computing and Communications (PerCom 2010), Mannheim, Germany, 2010.
5. K. Förster, D. Roggen, and G. Tröster, "Unsupervised classifier self-calibration through repeated context occurences: is there robustness against sensor displacement to gain?" in Proceedings of the 13th International Symposium on Wearable Computing. IEEE Computer Society, 2009, pp. 77-84.
6. C. Alippi and M. Roveri, "An adaptive cusum-based test for signal change detection," in ISCAS. IEEE, 2006.
7. -, "Just-in-time adaptive classifiers, part I: Detecting non-stationary changes," IEEE Transactions on Neural Networks, vol. 19, no. 7, pp. 1145-1153, 2008.
8. H. Sagha, J. d. R. Millán, and R. Chavarriaga, "Detecting anomalies to improve classification performance in an opportunistic sensor network," in 7th IEEE International Workshop on Sensor Networks and Systems for Pervasive Computing, PerSens 2011, Seattle, March 2011.
9. -, "A probabilistic approach to handle missing data for multi-sensory activity recognition," in Workshop on Context Awareness and Information Processing in Opportunistic Ubiquitous Systems at 12th ACM International Conference on Ubiquitous Computing, 2010.
10. P. C. Mahalanobis, "On the generalized distance in statistics," 1936, pp. 49-55.
11. T. Stiefmeier, D. Roggen, G. Ogris, P. Lukowicz, and G. Tröster, "Wearable activity tracking in car manufacturing," IEEE Pervasive Computing Magazine, pp. 42-50, 2008. (Pubitemid 351575121)
12. P. Zappi, C. Lombriser, T. Stiefmeier, E. Farella, D. Roggen, L. Benini, and G. Tröster, "Activity recognition from on-body sensors: Accuracy-power trade-off by dynamic sensor selection," Wireless Sensor Networks, pp. 17-33, 2008.
13. D. Roggen, A. Calatroni, M. Rossi, T. Holleczek, K. Förster, G. Tröster, P. Lukowicz, D. Bannach, G. Pirkl, A. Ferscha, J. Doppler, C. Holzmann, M. Kurz, G. Holl, R. Chavarriaga, H. Sagha, H. Bayati, M. Creatura, and J. R. Millán, "Collecting complex activity data sets in highly rich networked sensor environments," in Seventh International Conference on Networked Sensing Systems, 2010.