Senior health monitoring using Kinect

2012 4th International Conference on Communications and Electronics, ICCE 2012

Volumn , Issue , 2012, Pages 309-312

  Parajuli, Monish ^a   Tran, Dat ^a   Ma, Wanli ^a   Sharma, Dharmendra ^a  

^a UNIVERSITY OF CANBERRA   (Australia)

Author keywords

gait recognition; Kinect; senior health monitoring; support vector machine

Indexed keywords

ELDERLY PEOPLE; GAIT RECOGNITION; HEALTH MONITORING; HEALTH MONITORING SYSTEM; KINECT; RESEARCH EXPERIENCE;

SUPPORT VECTOR MACHINES;

EID: 84869171943     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CCE.2012.6315918     Document Type: Conference Paper

References (34)

1. L. Menon and G. Menon, G. "Clinical: Falls in the elderly. GP: General Practitioner", Retrieved from http://ezproxy.canberra.edu.au/login? url=http://search.ebscohost.com/login.aspx?direct=true&db=hch&AN= 67609963&site=ehost-live, 2011
2. P. Kannus, K. M. Khan and S. R. Lord, "Preventing falls among elderly people in the hospital environment". The Medical Journal of Australia, vol. 184, no. 8, pp. 379-382, 2006.
3. G. Andonegi, " HEBE: Detection of falls and monitoring of the elderly". Retrieved from http://www.eurekalert.org/pub-releases/2006-04/ efhdo042406.php, 2011.
4. H. Umegaki, Y. Suzuki, M., Yanagawa, Z. Nonogaki, and H. Endo, "Falls in elderly at high risk of requiring care", Geriatrics & Gerontology International, vol. 12, no. 1, pp. 147-148, 2012.
5. F. E. Pollo, "AbnormGait analysis: Techniques and recognition of al gait", retrieve from http://anatomy.org/Files2/Gait%20Analysis %20Techniques%20and%20Abnormal%20Patterns-AAA.ppt, 2011.
6. Y. Lajoie & S. P. Gallagher, "Predicting falls within the elderly community: Comparison of postural sway, reaction time, the berg balance scale and the activities-specific balance confidence (ABC) scale for comparing fallers and non-fallers". Archives of Gerontology and Geriatrics, vol. 38, no. 1, pp. 11-26, 2004.
7. H. M., Clayton, & H. C. Schamhard, "Measurement techniques for Gait Analysis", retrieved from http://www.elsevierhealth.co.uk/media/us/ samplechapters/9780702024832/9780702024832.pdf, 2011.
8. Ö. D., Incel, & H. Alemdar, "Pervasive visual sensor networks for elderly care", in Proc. the 5th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2009.
9. J. Bae, K. Kong, N. Byl, & M. Tomizuka, "A mobile gait monitoring system for gait analysis", in Proceedings of the IEEE International Conference on Rehabilitation Robotics, pp. 73-79, 2009.
10. A., Bagnasco, A. M., Scapolla, & V. Spasova, "Design, implementation and experimental evaluation of a wireless fall detector", Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, 2011.
11. R., Paoli, F. J., Fernández-Luque, G., Doménech, F., Martínez, J., Zapata, & R. Ruiz, "A system for ubiquitous fall monitoring at home via a wireless sensor network and a wearable mote", Expert Systems with Applications, vol. 39, no. 5, pp. 5566-5575, 2012.
12. R. Y. W., Lee, & A. J. Carlisle, "Detection of falls using accelerometers and mobile phone technology", Age & Ageing, vol. 40, no. 6, pp. 690-696, 2011.
13. S. J., Morris, & J. A. Paradiso, "A compact wearable sensor packagefor clinical gait monitoring", Offspring, vol. 1, no. 1, pp. 7-15, 2003.
14. A. Sixsmith & N. Johnson, "A smart sensor to detect the falls of the elderly". Pervasive Computing, IEEE, vol. 3, no. 2, pp. 42-47, 2004.
15. Kinect for windows SDK beta. Retrieved 12/08, 2011, from http://research.microsoft.com/en-us/collaboration/focus/nui/kinectwindows.aspx
16. Guiness World Records. Fastest-selling gaming peripheral. Retrieved 12/14, 2011, from http://www.guinnessworldrecords.com/records-9000/fastest- selling-gaming-peripheral/.
17. M. Fisher, Kinect. http://graphics.stanford.edu/~mdfisher/Kinect.html
18. J. Han & M. Kambe, In Stephan A. (Ed.), Data mining: Concepts and techniques (Second Edition ed.). Morgan Kaufmann Publishers, 2011.
19. J. Shotton, A. Fitzgibbon, M. Cook, T. Sharp, M. Finocchio, R. Moore, "Real-time human pose recognition in parts from a single depth image", Retrieved from http://research.microsoft.com/apps/pubs/?id=145347
20. A. Ben-Hur & J. Weston, "A user's guide to support vector machines", Retrieved 12/09, 2011, from http://pyml.sourceforge.net/doc/ howto.pdf
21. C.-C. Chang and C.-J. Lin., "LIBSVM: A library for support vector machines", ACM Trans. Intell. Syst. Technol., vol. 2, no. 3, pp.1-27, 2011.
22. C. J. C. Burges, "A tutorial on support vector machines for pattern recognition," Knowledge Discovery and Data Mining, vol. 2, no. 2, pp.121-167, 1998.
23. I. H. Witten and E. Frank. Data Mining: Practical machine learning tools and techniques. Morgan Kaufmann, San Francisco, 2nd edition, 2005.
24. C.-C. Chang and C.-J. Lin. LibSVM: a library for sup-port vector machines, 2001. Software available at http://www.csie.ntu.edu.tw/cjlin/libsvm
25. C. E. Colvin, J. H. Babcock, J. H. Forrest, C. M. Stuart, M. J. Tonnemacher, & W.-S. Wang, "Multiple user motion capture and systems engineering", in Proceedings of IEEE Conf. on Systems and Information Engineering Design Symposium (SIEDS), pp. 137-140, 2011.
26. R. B., Davis III, S., Õunpuu, D., Tyburski, & J. R. Gage, "A gait analysis data collection and reduction technique", Human Movement Science, vol. 10, no. 5, pp.575-587, 1991.
27. Hsu, C. W., Chang, C. C. & Lin, C. J. (2010). A practical guide to support vector classification. Retrieved 12/18, 2011, from http://www.csie.ntu. edu.tw/~cjlin/papers/guide/guide.pdf
28. M. J. W. She, S. Nahavandi & A. Kouzani, "A review of vision-based gait recognition methods for human identification", in Proceedings of the International Conference on Digital Image Computing: Techniques and Applications (DICTA), pp.320-327, 2010.
29. J. K. Tan, S. Houman & S. Ishikawa, "Human motion representation using eigenspaces", in Proceedings of the IEEE TENCON 2005, pp. 1-4, 2005.
30. T. Leyvand, C. Meekhof, Yi-Chen Wei, Jian Sun, & Baining Guo, "Kinect identity: Technology and experience", Computer, vol. 44, no. 4, pp. 94-96, 2011.
31. Prevent falls to stop deaths. Australian Nursing Journal, vol. 19, no. 4, pp. 15-15, 2011.
32. M. Tang, "Recognizing hand gestures with Microsoft's kinect", Retrieved from http://www.stanford.edu/class/ee368/Project-11/Reports/Tang-Hand- Gesture-Recognition.pdf
33. R. Urtasun, "Human motion analysis," Retrieved 19/12/2011, from http://ttic.uchicago.edu/~rurtasun/courses/ETH10/human-motion-analys is.html2010
34. T. Wall, "Fall monitoring system add to seniors' independence", Retrieved 12/08, 2011, from http://engineering.missouri.edu/2011/04/fall- monitoring-systems-add-to-seniors%E2%80%99-independence/