On the use of ensemble of classifiers for accelerometer-based activity recognition

Applied Soft Computing Journal

Volumn 37, Issue , 2015, Pages 1018-1022

  Catal, Cagatay ^a   Tufekci, Selin ^a   Pirmit, Elif ^a   Kocabag, Guner ^a  

^a ISTANBUL KULTUR UNIVERSITY   (Turkey)

Author keywords

Accelerometer; Activity recognition; Ensemble of classifiers; Machine learning; Mobile computing; Sensor mining

Indexed keywords

ACCELEROMETERS; ARTIFICIAL INTELLIGENCE; DECISION TREES; LEARNING SYSTEMS; MOBILE COMPUTING; MOBILE DEVICES; PATTERN RECOGNITION;

ACTIVITY PREDICTIONS; ACTIVITY RECOGNITION; ADVANCED APPLICATIONS; BETTER PERFORMANCE; ENSEMBLE OF CLASSIFIERS; LOGISTIC REGRESSIONS; MULTI-LAYER PERCEPTRONS; WIRELESS SENSOR DATA;

DATA MINING;

EID: 84947128497     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2015.01.025     Document Type: Article

References (22)

1. A. Bulling, U. Blanke, and B. Schiele A tutorial on human activity recognition using body-worn inertial sensors ACM Comput. Surv. 46 3 2014 33
2. Y.-S. Lee, and S.-B. Cho Activity recognition using hierarchical hidden Markov models on a smartphone with 3D accelerometer Proceedings of the 6th International Conference on Hybrid Artificial Intelligent Systems - Volume Part I (HAIS'11) 2011 Springer-Verlag Berlin, Heidelberg 460 467
3. T. Phan Improving activity recognition via automatic decision tree pruning Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication (UbiComp'14 Adjunct) 2014 ACM New York, NY, USA 827 832
4. D. Anguita, A. Ghio, L. Oneto, X. Parra, and J.L. Reyes-Ortiz Human activity recognition on smartphones using a multiclass hardware-friendly support vector machine J. Bravo, R. Hervás, M. Rodríguez, Proceedings of the 4th International Conference on Ambient Assisted Living and Home Care (IWAAL'12) 2012 Springer-Verlag Berlin, Heidelberg 216 223
5. D.L. Vail, M.M. Veloso, and J.D. Lafferty Conditional random fields for activity recognition Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS'07) 2007 ACM New York, NY, USA 8
6. M.A. Ayu, S.A. Ismail, A.F.A. Matin, and T. Mantoro A comparison study of classifier algorithms for mobile-phone's accelerometer based activity recognition Procedia Eng. 41 2012 224 229
7. J.R. Kwapisz, G.M. Weiss, and S.A. Moore Activity recognition using cell phone accelerometers SIGKDD Explor. Newsl. 12 March (2) 2011 74 82
8. Y.E. Ustev, O.D. Incel, and C. Ersoy User, device and orientation independent human activity recognition on mobile phones: challenges and a proposal Proceedings of the 2013 ACM Conference on Pervasive and Ubiquitous Computing Adjunct Publication (UbiComp'13 Adjunct) 2013 ACM New York, NY, USA 1427 1436
9. S. Dernbach, B. Das, N.C. Krishnan, and B.L. Thomas Simple and complex activity recognition through smart phones 8th International Conference on Intelligent Environments Guanajuato, Mexico 2012 214 221
10. E. Miluzzo, N.D. Lane, K. Fodor, R. Peterson, H. Lu, M. Musolesi, S.B. Eisenman, X. Zheng, and A.T. Campbell Sensing meets mobile social networks: the design, implementation and evaluation of the CenceMe application Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems (SenSys'08) 2008 ACM New York, NY, USA 337 350
11. F. Al-Bin-Ali, and N. Davies Applying logistic regression for activity recognition The Sixth International Conference on Ubiquitous Computing. Poster 2004
12. J. Mantyjarvi, J. Himberg, and T. Seppanen Recognizing human motion with multiple acceleration sensors IEEE International Conference on System, Man, and Cybernetics Tuczon, AZ 2001 747 752
13. S.R. Ke, L.U.T. Hoang, Y.-J. Lee, J.-N. Hwang, J.-H. Yoo, and K.-H. Choi A review on video-based human activity recognition Computers 2 2 2013 88 131
14. N. Jajac, B. Predic, and D. Stojanovic A method for activity recognition partially resilient on mobile device orientation Proceedings of IMMoA'13 Trento, Italy 2013 15 20
15. J.W. Lockhart, T. Pulickal, and G.M. Weiss Applications of mobile activity recognition Proceedings of the 2012 ACM Conference on Ubiquitous Computing (UbiComp'12) 2012 ACM New York, NY 1054 1058
16. G.M. Weiss, and J.W. Lockhart The impact of personalization on smartphone based activity recognition Proceedings of the AAAI Workshop on Activity Context Representation: Techniques and Languages 2012 98 104
17. J.W. Lockhart, and G.M. Weiss Limitations with activity recognition methodology & datasets Proceedings of the UbiComp'14 Seattle, WA 2014
18. A. Bayat, M. Pomplun, and D.A. Tran A study on human activity recognition using accelerometer data from smartphones Proceedings of the MobiSPC-2014 Procedia Computer Science vol. 34 2014 450 457
19. J. Wang, R. Chen, X. Sun, M.F.H. She, and Y. Wu Recognizing human daily activities from accelerometer signal Procedia Eng. 15 2011 1780 1786
20. Y. Kwon, K. Kang, and C. Bae Unsupervised learning for human activity recognition using smartphone sensors Expert Syst. Appl. 41 14 2014 6067 6074
21. L. Gao, A.K. Bourke, and J. Nelson Evaluation of accelerometer based multi-sensor versus single-sensor activity recognition systems Med. Eng. Phys. 36 6 2014 779 785
22. Y.-J. Hong, I.-J. Kim, S.C. Ahn, and H.-G. Kim Mobile health monitoring system based on activity recognition using accelerometer Simul. Model. Pract. Theory 18 4 2010 446 455