• OpenAccess
  • Motion Classification Using Proposed Principle Component Analysis Hybrid K-Means Clustering  [ICBE 2013]
  • DOI: 10.4236/eng.2013.55B006   PP.25 - 30
  • Author(s)
  • Ching Yee Yong, Rubita Sudirman, Nasrul Humaimi Mahmood, Kim Mey Chew
  • This study investigates and acts as a trial clinical outcome for human motion and behaviour analysis in consensus of health related quality of life in Malaysia. The proposed technique was developed to analyze and access the quality of human motion that can be used in hospitals, clinics and human motion researches. It aims to establish how to widespread the quality of life effects of human motion. Reliability and validity are needed to facilitate subject outcomes. An experiment was set up in a laboratory environment with conjunction of analyzing human motion and its behaviour. Five classifiers and algorithms were used to recognize and classify the motion patterns. The proposed PCA-K-Means clustering took 0.058 seconds for classification process. Resubstitution error for the proposed technique was 0.002 and achieved 94.67% of true positive for total confusion matrix of the classification accuracy. The proposed clustering algorithm achieved higher speed of processing, higher accuracy of performance and reliable cross validation error.
  • Accelerometer; Gyroscope; Fuzzy; Bayes; Decision Tree
  • References
  • [1]
    F. Tian, “Leveraging Psychophysical Data in Monitoring and Analyzing the States of Badminton Players,” ACM. Atlanta, Georgia, USA, 2010, pp. 930-935.
    Nasrul Humaimi Mahmood, Ching Yee Yong, Rubita Sudirman, Camallil Omar and Kim Mey Chew, “Functional And Health Related Analysis In The Discipline Of Posthetics,” International Journal of Advances in Engineering & Technology, 2011, Vol. 1, No. 3, pp. 171-179.
    C. Y. Yong, K. M. Chew, N. H. Mahmood, R. Sudirman and C. Omar, “Development and Measurement Properties of Prosthetics Users’ Survey”, 2011 IEEE Symposium on Business, Engineering and Industrial Applications (ISBEIA2011), 25-29 September 2011, Langkawi, Malaysia, pp. 570-575.
    R. Nalma and J. Canny, “The Berkeley Trocoder: Ambulatory Health Monitoring,” 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks, 2009, pp. 53-58.
    U. Maurer, A. Smailagic and D. P. Siewiorek, “Activity Recognition and Monitoring Using Multiple Sensors on Different Body Positions,” International Workshop on Wearable and Implantable Body Sensor Networks, 2006.
    C. Y. Yong, Rubita Sudirman and Kim Mey Chew, “Motion Detection and Analysis with Four Different Detectors,” 2011 Third International Conference on Computational Intelligence, Modelling & Simulation (CIMSim 2011), Langkawi, Malaysia, 20-22 September 2011, pp. 46-50.
    C. Ni Scanail, B. Ahearne and G. M. Lyons, “Long-term Telemonitoring of Mobility Trends of Elderly People Using SMS Messaging,” IEEE Trans Inform Tech Biomed, 2006, Vol. 10, pp. 34-37.
    A. Godfrey, K. M. Culhane and G. M. Lyons, “Comparison of the Performance of the Active PALTM Trio Professional Physical Activity Logger to a Discrete Accelerometer-Based Activity Monitor,” Medical Engineering & Physic, 2006.
    A. C. Bovik, M. Clark and W. S. Geisler, “Multichannel Texture Analysis Using Localized Spatial Filters,” IEEE Trans. On Pattern Analysis and Machine Intelligence, 1990, Vol. 12, No. 1, pp. 55-73.
    G. R. Cross and A. K. Jain, “Markov Random Field Texture Models,” IEEE Trans. On Pattern Analysis and Machine Intelligence, Vol. 5, 1983, pp. 25-39.
    R. O. Duda, P. E. Hart and D. G. Stork, “Pattern Classification,” John Wiley & Sons, 2 edition, 2001.
    D. G. Lowe, “Object Recognition from Local Sclae-Invariant Features,” In Proc. Int. Conf. on Computer Vision, Vol. 2, 1999, pp. 1150-1157.
    M. Vangelis, A. Ion and P. Geogios, “Spam Filtering with Naive Bayes-Which Naive Bayes?” Third Conference on Email and Anti-Spam, 2006.
    H. Spath, “Cluster Dissection and Analysis: Theory,” FORTRAN Programs, Examples. Translated by J. Goldschmidt, New York: Halsted Press, 1985.
    J.-S. R. Jang and C.-T. Sun, “Neuro-Fuzzy Modeling and Control,” Proceedings of the IEEE, 1995.
    L. Breiman, J. Friedman, R. Olshen and C. Stone, Classification and Regression Trees. Boca Raton, FL: CRC Press, 1984.
    Ching Yee Yong, K. M. Chew, N. H. Mahmood and I. Ariffin, “Image Processing Tools Package in Medical Imaging in MATLAB,” International Journal of Education and Information Technologies, North Atlantic University Union, NAUN, Vol. 6, No. 3, 2012, pp. 260 -268.
    Ching Yee Yong, R. Sudirman, N. H. Mahmood, K. M. Chew, A. H. AB Rahim and M. N. H. Zainudin,“Time-Frequency Domain and Spectrogram Distribution for Human Motion and Movement Behaviour Analysis,” icbeb 2012 International Conference on Biomedical Engineering and Biotechnology, 2012, pp. 943-946.

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