Human activity recognition using inertial/magnetic sensor units

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6219 LNCS, Issue , 2010, Pages 38-51

  Altun, Kerem ^a   Barshan, Billur ^a  

^a BILKENT UNIVERSITY   (Turkey)

Author keywords

feature selection and reduction; human activity recognition and classification; inertial sensors; magnetometers

Indexed keywords

ARTIFICIAL NEURAL NETWORK; BAYESIAN DECISION; CLASSIFICATION RATES; CLASSIFICATION TECHNIQUE; COMPARATIVE STUDIES; COMPUTATIONAL COSTS; CROSS-VALIDATION TECHNIQUE; DYNAMIC TIME WARPING; FEATURE REDUCTION; FEATURE SELECTION; FEATURE SELECTION AND REDUCTION; HUMAN ACTIVITIES; HUMAN ACTIVITY RECOGNITION; INERTIAL SENSOR; K-NEAREST NEIGHBOR ALGORITHM; LEAST SQUARES METHODS; REAL-TIME APPLICATION; SENSOR UNITS; SPORTS ACTIVITY; TRI-AXIAL MAGNETOMETER; TRIAXIAL ACCELEROMETER;

BAYESIAN NETWORKS; BEHAVIORAL RESEARCH; CLASSIFIERS; DECISION MAKING; INERTIAL NAVIGATION SYSTEMS; INTELLIGENT AGENTS; MAGNETOMETERS; NEURAL NETWORKS; PRINCIPAL COMPONENT ANALYSIS; SENSORS; SUPPORT VECTOR MACHINES;

FEATURE EXTRACTION;

EID: 77958470516     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-14715-9_5     Document Type: Conference Paper

References (31)

1. Aggarwal, J. K., Cai, Q.: Human motion analysis: a review. Comput. Vis. Image Und. 73(3), 428-440 (1999)
2. Moeslund, T. B., Granum, E.: A survey of computer vision-based human motion capture. Comput. Vis. Image Und. 81(3), 231-268 (2001)
3. Moeslund, T. B., Hilton, A., Krüger, V.: A survey of advances in vision-based human motion capture and analysis. Comput. Vis. Image Und. 104 (2-3), 90-126 (2006)
4. Kern, N., Schiele, B., Schmidt, A.: Multi-sensor activity context detection for wearable computing. In: Aarts, E., Collier, R. W., van Loenen, E., de Ruyter, B. (eds.) EUSAI 2003. LNCS, vol. 2875, pp. 220-232. Springer, Heidelberg (2003) (Pubitemid 137631976)
5. Zijlstra, W., Aminian, K.: Mobility assessment in older people: new possibilities and challenges. Eur. J. Ageing 4(1), 3-12 (2007)
6. Mathie, M. J., Coster, A. C. F., Lovell, N. H., Celler, B. G.: Accelerometry: providing an integrated, practical method for long-term, ambulatory monitoring of human movement. Physiol. Meas. 25(2), R1-R20 (2004)
7. Sabatini, A. M.: Inertial sensing in biomechanics: a survey of computational techniques bridging motion analysis and personal navigation. In: Computational Intelligence for Movement Sciences: Neural Networks and Other Emerging Techniques, pp. 70-100. Idea Group Publishing, USA (2006)
8. Mathie, M. J., Celler, B. G., Lovell, N. H., Coster, A. C. F.: Classification of basic daily movements using a triaxial accelerometer. Med. Biol. Eng. Comput. 42(5), 679-687 (2004)
9. Lindemann, U., Hock, A., Stuber, M., Keck, W., Becker, C.: Evaluation of a fall detector based on accelerometers: a pilot study. Med. Biol. Eng. Comput. 43(5), 548-551 (2005)
10. Kangas, M., Konttila, A., Lindgren, P., Winblad, I., Jämsä, T.: Comparison of low-complexity fall detection algorithms for body attached accelerometers. Gait Posture 28(2), 285-291 (2008)
11. Wu, W. H., Bui, A. A. T., Batalin, M. A., Liu, D., Kaiser, W. J.: Incremental diagnosis method for intelligent wearable sensor system. IEEE T. Inf. Technol. B. 11(5), 553-562 (2007)
12. Jovanov, E., Milenkovic, A., Otto, C., de Groen, P.: A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation. J. Neuroeng. Rehabil. 2 (6) (2005)
13. Pärkkä, J., Ermes, M., Korpipää, P., Mäntyjärvi, J., Peltola, J., Korhonen, I.: Activity classification using realistic data from wearable sensors. IEEE T. Inf. Technol. B. 10(1), 119-128 (2006)
14. Ermes, M., Pärkkä, J., Mäntyjärvi, J., Korhonen, I.: Detection of daily activities and sports with wearable sensors in controlled and uncontrolled conditions. IEEE T. Inf. Technol. B. 12(1), 20-26 (2008)
15. Aylward, R., Paradiso, J. A.: Sensemble: A wireless, compact, multi-user sensor system for interactive dance. In: Proc. Conf. New Interfaces Musical Expression, Paris, France, June 4-8, pp. 134-139 (2006)
16. Shiratori, T., Hodgins, J. K.: Accelerometer-based user interfaces for the control of a physically simulated character. ACM T. Graphic. 27 (5) (2008)
17. Aminian, K., Robert, P., Buchser, E. E., Rutschmann, B., Hayoz, D., Depairon, M.: Physical activity monitoring based on accelerometry: validation and comparison with video observation. Med. Biol. Eng. Comput. 37(1), 304-308 (1999)
18. Roetenberg, D., Slycke, P. J., Veltink, P. H.: Ambulatory position and orientation tracking fusing magnetic and inertial sensing. IEEE T. Bio-med. Eng. 54(5), 883-890 (2007)
19. Najafi, B., Aminian, K., Paraschiv-Ionescu, A., Loew, F., Büla, C. J., Robert, P.: Ambulatory system for human motion analysis using a kinematic sensor: monitoring of daily physical activity in the elderly. IEEE T. Bio-med. Eng. 50(6), 711-723 (2003)
20. Tao, Y., Hu, H., Zhou, H.: Integration of vision and inertial sensors for 3D arm motion tracking in home-based rehabilitation. Int. J. Robot. Res. 26(6), 607-624 (2007)
21. Zhu, R., Zhou, Z.: A real-time articulated human motion tracking using tri-axis inertial/magnetic sensors package. IEEE T. Neur. Sys. Reh. 12(2), 295-302 (2004)
22. Bao, L., Intille, S. S.: Activity recognition from user-annotated acceleration data. In: Ferscha, A., Mattern, F. (eds.) PERVASIVE 2004. LNCS, vol. 3001, pp. 1-17. Springer, Heidelberg (2004)
23. Karantonis, D. M., Narayanan, M. R., Mathie, M., Lovell, N. H., Celler, B. G.: Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring. IEEE T. Inf. Technol. B. 10(1), 156-167 (2006)
24. Allen, F. R., Ambikairajah, E., Lovell, N. H., Celler, B. G.: Classification of a known sequence of motions and postures from accelerometry data using adapted Gaussian mixture models. Physiol. Meas. 27(10), 935-951 (2006)
25. Xsens Technologies B. V. Enschede, Holland: MTi and MTx User Manual and Technical Documentation (2009), http://www.xsens.com
26. Webb, A.: Statistical Pattern Recognition. John Wiley & Sons, New York (2002)
27. Tunçel, O., Altun, K., Barshan, B.: Classifying human leg motions with uniaxial piezoelectric gyroscopes. Sensors 9(11), 8508-8546 (2009)
28. Altun, K., Barshan, B., Tunçel, O.: Comparative study on classifying human activities with miniature inertial and magnetic sensors. Pattern Recogn. 43(10), 3605-3620 (2010), doi:10.1016/j.patcog.2010.04.019
29. Preece, S. J., Goulermas, J. Y., Kenney, L. P. J., Howard, D., Meijer, K., Crompton, R.: Activity identification using body-mounted sensors-a review of classification techniques. Physiol. Meas. 30(4), R1-R33 (2009)
30. Chang, C. C., Lin, C. J.: LIBSVM: a library for support vector machines (2001), Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm
31. Preece, S. J., Goulermas, J. Y., Kenney, L. P. J., Howard, D.: A comparison of feature extraction methods for the classification of dynamic activities from accelerometer data. IEEE T. Bio-med. Eng. 56(3), 871-879 (2009)