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Vision Based Fall Detection

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Vision Based Fall Detection
COMSATS Institute of Information Technology, Park Road, Chak Shahzad, Islamabad Pakistan

Vision based fall detection

By
Taqi Mustafa Ahmed Javed
CIIT/SP10-BCS-069/ISB CIIT/SP10-BCS-084/ISB

Supervisor
Dr. Majid Iqbal

Bachelor of Science in Computer Science (2010-2014)

The candidates confirm that the work submitted is his own and appropriate credit has been given where reference has been made to the work of others.

COMSATS Institute of Information Technology, Park Road, Chak Shahzad, Islamabad Pakistan

Vision based fall detection

A project presented to

COMSATS Institute of Information Technology, Islamabad

In partial fulfillment of the requirement for the degree of

Bachelors of Science in Computer Science (2010-2014) By

Taqi Mustafa Ahmed Javed

CIIT/SP10-BCS-069/ISB CIIT/SP10-BCS-084/ISB

ii

Declaration
We hereby declare that this software, neither whole nor as a part has been copied out from any source. It is further declared that we have developed this software and accompanied report entirely on the basis of our personal efforts. If any part of this project is proved to be copied out from any source or found to be reproduction of some other. We will stand by the consequences. No Portion of the work presented has been submitted of any application for any other degree or qualification of this or any other university or institute of learning.

_________________ Ahmed Javed

__________________ Taqi Mustafa

iii

Certificate of Approval
It is to certify that the final year project of BS (CS) “Vision Based Fall Detection” was developed by “Ahmed Javed (CIIT/SP10-BCS-084)” and “Taqi Mustafa (CIIT/SP10-BCS-069)” under the supervision of “Dr. Majid Iqbal” and that in his opinion it is fully adequate, in scope and quality for the degree of Bachelors of Science in Computer Sciences.

________________________ Supervisor

________________________ External Examiner

________________________ Head of Department



References: [1] Abbate S., Avvenuti M., Corsini P., Vecchio A., & Light J., (14th December 2010), Monitoring of human movements for fall detection and activities recognition in elderly care using wireless sensor network: a survey, http://cdn.intechopen.com/pdfs/12472/InTechMonitoring_of_human_movements_for_fall_detectio n_and_activities_recognition_in_elderly_care_using_wireless_sensor_network_a_survey.pdf. [2] Yoshida, S., (2007), A global report on falls prevention epidemiology of falls, http://www.who.int/ageing/projects/1.Epidemiologyoffallsinolderage.pdf, by the World Health Organization (WHO). [3] Noury, N., Rumeau, P., Bourke, A., ÓLaighin, G., & Lundy, J., (2008), a proposal for the classification and evaluation of fall detectors. IRBM, 29(6), 340 – 349. [4] Charles Brown, Carol Lehtola, W. J. B., (2009), Preventing injuries from slips, trips and falls, http://edis.ifas.ufl.edu/as042, by the University of Florida. [5] Stalenhoef, P. A., and. J André Knottnerus and. Luc P de Witteb, J. P. D., & Crebolder, H. F., (2000), The construction of a patient record-based risk model for recurrent falls among elderly people living in the community, http://fampra.oxfordjournals.org/content/17/6/490.abstract, by Oxford University. [6] Dai, J., Bai, X., Yang, Z., Shen, Z., & Xuan, D. 29,(2010), Perfalld: A pervasive fall detection system using mobile phones, In Pervasive Computing and Communications Workshops(PERCOM Workshops), 2010 8th IEEE International Conference on. [7] Li, Q., Stankovic, J., Hanson, M., Barth, A., Lach, J., & Zhou, G.,(2009), Accurate, fast fall detection using gyroscopes and accelerometer-derived posture information, In Wearable and Implantable Body Sensor Networks, (2009). BSN 2009, Sixth International Workshop on,138 –143. [8] Bourke, A., van de Ven, P., Gamble, M., O’Connor, R., Murphy, K., Bogan, E., McQuade, E., Finucane, P., ÓLaighin, G., & Nelson, J.,(2010), Evaluation of waist mounted tri-axial accelerometer based fall-detection algorithms during scripted and continuous unscripted activities, Journal of Biomechanics, 43(15), 3051 – 3057. 38 [9] Degen, T. & Jaeckel, H.,(2003). Speedy: a fall detector in a wrist watch, In Proceedings, Seventh IEEE International Symposium on Wearable Computing, 184–189. [10] Bourke, A. & Lyons, G.,(2008), A threshold-based fall-detection algorithm using a bi-axial gyroscope sensor, Medical Engineering Physics, 30(1), 84 – 90. [11] Popescu, M., Li, Y., Skubic, M., & Rantz, M.,(2008), An acoustic fall detector system that uses sound height information to reduce the false alarm rate, In Engineering in Medicine and Biology Society, (2008), EMBS 2008, 30th Annual International Conference of the IEEE,4628 –4631. [12] Perry, J., Kellog, S., Vaidya, S., Youn, J.-H., Ali, H., & Sharif, H.,(2009), Survey and evaluation of real-time fall detection approaches, In High-Capacity Optical Networks and Enabling Technologies (HONET), 2009 6th International Symposium on, 158 –164. [13] Ketabdar, H. Detecting physical shock by a mobile phone and its applications in security and emergency. [14] Aud, M. A., Abbott, C. C., Tyrer, H. W., Neelgund, R. V., Shriniwar, U. G., Mohammed, A.,& Devarakonda, K. K.,(2010), Smart carpet: Developing a sensor system to detect falls and summon assistance, J Gerontol Nurs, 36(7), 8–12. [15] Alwan, M., Rajendran, P., Kell, S., Mack, D., Dalal, S., Wolfe, M., & Felder, R.,(2006), A smart and passive floor-vibration based fall detector for elderly, In Communication Technologies, (2006), ICTTA ’06. 2nd. [16] A. Sixsmith, N. Johnson, & R. Whatmore.,(2005), Pyroelectric ir sensor arrays for fall detection in the older population, J. Phys. IV France, 128, 153–160. [17] G. Debard, P. Karsmakers, M. Deschodt, E. Vlaeyen, J. Van Den Bergh, E. Dejaeger, K. Milisenb, T. Goedemé, T. Tuytelaars, B. Vanrumste,(2010), Camera based fall detection using multiple features validated with real life video, Biosciences and Technology Department, K.H.Kempen, Belgium. [18] M. Mubashir, L. Shao, L. Seed.,(2012), A survey on fall detection: Principles and approaches , TheUniversityofSheffield,UK. 39 Information and

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