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Information Systems Design and Intelligent Applications pp 709–717Cite as

Automatic Gesture Recognition for Health Care Using ReliefF and Fuzzy kNN

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 340))

Abstract

This work describes a simple method to detect gestures revealing muscle and joint pain. The data is acquired using Kinect Sensor. For the purpose of feature extraction, the twenty joint coordinates are processed in three dimensional space. From each frame, 171 Euclidean distances are calculated and to reduce the dimension of the feature space, ReliefF algorithm is implemented. The classification stage is consists of fuzzy k-nearest neighbour classifier. The proposed method is employed to recognize 24 body gestures and yields a high recognition rate of 90.63 % which is comparatively higher than several other algorithms for young person gesture recognition works.

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References

  1. Saha, S., Pal, M., Konar, A., Janarthanan, R.: Neural network based gesture recognition for elderly health care using Kinect sensor. In: Swarm, Evolutionary, and Memetic Computing, pp. 376–386. Springer, Berlin (2013)

    Google Scholar 

  2. Pal, M., Saha, S., Konar, A.: A fuzzy C means clustering approach for gesture recognition in healthcare. Knee, 1, C7

    Google Scholar 

  3. Le, T.-L., Nguyen, M.-Q., Nguyen, T.-T.-M.: Human posture recognition using human skeleton provided by Kinect. In: 2013 International Conference on Computing, Management and Telecommunications (ComManTel), pp. 340–345. (2013)

    Google Scholar 

  4. Stone, E., Skubic, M.: Fall detection in homes of older adults using the Microsoft Kinect (2014)

    Google Scholar 

  5. Lai, K., Konrad, J., Ishwar, P.: A gesture-driven computer interface using Kinect. In: 2012 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI), pp. 185–188. (2012)

    Google Scholar 

  6. Keller, J.M., Gray, M.R., Givens, J.A.: A fuzzy k-nearest neighbor algorithm. Syst. Man Cybern. IEEE Trans. 4, 580–585 (1985)

    Article  Google Scholar 

  7. Ganea, D., Mereuta, E., Mereuta, C.: Human body kinematics and the kinect sensor. Appl. Mech. Mater. 555, 707–712 (2014)

    Article  Google Scholar 

  8. Kandil, A., Hastak, M., Dunston, P.S.: Analysis of XBOX Kinect sensor data for use on construction sites: depth accuracy and sensor interference assessment. Bridges 10, 9780784412329.086 (2014)

    Google Scholar 

  9. Robnik-Šikonja, M., Kononenko, I.: Theoretical and empirical analysis of ReliefF and RReliefF. Mach. Learn. 53(1–2), 23–69 (2003)

    Article  MATH  Google Scholar 

  10. Cunningham, P., Delany, S.J., “k-Nearest neighbour classifiers”. Mult. Classif. Syst. 1–17 (2007). Technical Report UCD-CSI-2007

    Google Scholar 

  11. Mitchell, T.M.: Machine learning and data mining. Commun. ACM 42(11), 30–36 (1999)

    Article  Google Scholar 

  12. Zar, J.H.: Biostatistical Analysis. Pearson Education India (1999)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Electronics and Tele-Communication Engineering Department, Jadavpur University, Kolkata, India

    Sriparna Saha, Monalisa Pal & Amit Konar

  2. Computer Science and Engineering Department, NIT Agartala, Agartala, India

    Diptendu Bhattacharya

Authors
  1. Sriparna Saha
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  2. Monalisa Pal
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  3. Amit Konar
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  4. Diptendu Bhattacharya
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Corresponding author

Correspondence to Sriparna Saha .

Editor information

Editors and Affiliations

  1. University of Kalyanai, Kalyanai, West Bengal, India

    J. K. Mandal

  2. Department of Computer Science and Engineering, Anil Neerukonda Institute of Technology and Sciences, Vishakapatnam, India

    Suresh Chandra Satapathy

  3. Dean, Faculty of Engineering, Technology, University of Kalyani, Kalyani, West Bengal, India

    Manas Kumar Sanyal

  4. Engineering and Technological Studies, University of Kalyani, Kalyani, West Bengal, India

    Partha Pratim Sarkar

  5. Department Computer Science and Engineering, University of Kalyani, Kalyani, West Bengal, India

    Anirban Mukhopadhyay

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© 2015 Springer India

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Saha, S., Pal, M., Konar, A., Bhattacharya, D. (2015). Automatic Gesture Recognition for Health Care Using ReliefF and Fuzzy kNN. In: Mandal, J., Satapathy, S., Kumar Sanyal, M., Sarkar, P., Mukhopadhyay, A. (eds) Information Systems Design and Intelligent Applications. Advances in Intelligent Systems and Computing, vol 340. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2247-7_72

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  • DOI: https://doi.org/10.1007/978-81-322-2247-7_72

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2246-0

  • Online ISBN: 978-81-322-2247-7

  • eBook Packages: EngineeringEngineering (R0)

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