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Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 6, Issue 3, Pages 1,230-1,266, DOI: https://doi.org/10.21307/ijssis-2017-588
License : (CC BY-NC-ND 4.0)
Received Date : 23-February-2013 / Accepted: 30-April-2013 / Published Online: 05-June-2013
It is of little surprise that falling is often accepted as a natural part of the aging process. In fact, it is the impact rather than the occurrence of falls in the elderly, which is of most concern. Aging people are typically frailer, more unsteady, and have slower reactions, thus are more likely to fall and be injured than younger individuals. Typically, research and industry presented various practical solutions for assisting the elderly and their caregivers against falls via detecting falls and triggering notification alarms calling for help as soon as falls occur in order to diminish fall consequences. Furthermore, fall likelihood prediction systems have been emerged lately based on the manipulation of the medical and behavioral history of elderly patients in order to predict the possibility of falls occurrence. Accordingly, response from caregivers may be triggered prior to most fall occurrences and accordingly prevent falls from taking place. This paper presents an extensive review for the state-of-the-art trends and technologies of fall detection and prevention systems assisting the elderly people and their caregivers. Furthermore, this paper discusses the main challenges, facing elderly fall prevention, along with suggestions for future research directions.
 M.E. Tinetti and M. Speechley, ―Prevention of Falls Among the Elderly‖, The New England Journal of Medicine, vol. 320, no. 16, 1989, pp. 1055-1059.
 A.K. Bourke, P.V.D. Ven, M. Gamble, R. OConnor, K. Murphy, E. Bogan, E. McQuade, P. Finucane, G. Olaighin, and J. Nelson, ―Evaluation of Waist-mounted Tri-axial Accelerometer Based Fall-detection Algorithms During Scripted and Continuous Unscripted Activities‖, Journal of Biomechanics, vol. 43, no. 15, 2010, pp. 3051-3057.
 C.E. Coogler, ―Falls and Imbalance‖, Rehab Management, vol. 5, 1992, pp. 53-117.
 K.M. Pocinki, ―Studies Aim at Reducing Risk of Falls‖, P. T. Bulletin, 1990, pp. 13.
 S. Sadigh, A. Reimers, R. Andersson, and L. Laflamme, ―Falls and Fall-related Injuries Among the Elderly: a Survey of Residential-care Facilities in a Swedish Municipality‖, Journal of Community Health, vol. 29, no. 2, 2004, pp. 129-140.
 V. Spasova and I. Iliev, ―Computer Vision and Wireless Sensor Networks in Ambient Assisted Living: State of the Art and Challenges‖, Journal of Emerging Trends in Computing and Information Sciences, vol. 3, no. 4, 2012, pp. 585-595.
 J. Dai, X. Bai, Z. Yang, Z. Shen, and D. Xuan, ―PerFallD: A Pervasive Fall Detection System Using Mobile Phones‖, In Proc. 8thIEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), pp. 292-297, Germany, 2010.
 A.J. Bell, J.K. Talbot-Stern, and A. Hennessy, ―Characteristics and Outcomes of Older Patients Presenting to the Emergency Department After a Fall: a Retrospective Analysis‖, Medical Journal of Australia, vol. 73, no. 4, 2000.
 A. Bueno-Cavanillas, F. Padilla-Ruiz, J.J. Jimnez-Molen, C.A. Peinado-Alonso, and R. Glvez-Vargas, ―Risk Factors in Falls Among the Elderly According to Extrinsic and Intrinsic Precipitating Causes‖, European Journal of Epidemiology, vol. 16, no. 9, 2000, pp. 849-859.
 G.F. Fuller, ―Falls in the Elderly‖, American Family Physician, vol. 6, no. 7, 2000, pp. 2159-2168.
 K. James, D. Eldemire-Shearer, J. Gouldbourne, and C. Morris, ―Falls and Fall Prevention in the Elderly: The Jamaican Perspective‖, West Indian Medical Journal, vol. 56, no. 6, 2007, pp. 534-539.
 J. Tomkun and B. Nguyen, ―Design of a Fall Detection and Prevention System for the Elderly‖, In EE 4BI6 Electrical Engineering Biomedical Capstones, Department of Electrical and Computer Engineering, McMaster University, Hamilton, Ontario, Canada, April 23, 2010.
 Q. Li, J.A. Stankovic, M.A. Hanson, A.T. Barth, J. Lach, and G. Zhou, ―Accurate, Fast Fall Detection Using Gyroscopes and Accelerometer- Derived Posture Information‖, In Proc. Sixth International Workshop on Wearable and Implantable Body Sensor Networks, (BSN 2009), pp. 138-143, Berkeley, CA, USA, 2009.
 Q. Li, UVA, WSN — AlarmNet — Fall Detection, 2009. http://www.cs.virginia.edu/wsn/medical/projects/fall-detection (last accessed November 20, 2012).
 E.E. Sabelman, D. Schwandt, and D.L. Jaffe, ―The WAMAS Wearable Accelerometric Motion Analysis System: Combining Technology Development and Research in Human Mobility‖, In Proc. Conf. Intellectual Property in the VA: Changes, Challenges and Collaborations, Arlington, VA, United States, 2001.
 T. Degen and H. Jaeckel, ―SPEEDY: a Fall Detector in a WristWatch‖, In Proc. Seventh IEEE International Symposium on Wearable Computing (ISWC 2003), pp. 184-189, White Plains, NY, USA, 21-23 October, 2003.
 Y. Schutz, S. Weinsier, P. Terrier, and D. Durrer, ―A New Accelerometric Method to Assess the Daily Walking Practice‖, International Journal of Obesity, vol. 26, no. 1, 2002, pp. 111-118.
 J. Chen, K. Kwong, D. Chang, J. Luk, and R. Bajcsy, ―Wearable Sensors for Reliable Fall Detection‖, In Proc. 27th Annual International Conference of The Engineering in Medicine and Biology Society (IEEE-EMBS 2005), pp. 3551-3554, Shanghai, China, 2005.
 K. Pister, B. Hohlt, J. Jeong, L. Doherty, and J.P. Vainio, Ivy - A Sensor Network Infrastructure for the Berkeley College of Engineering, University of California, 2003. http://wwwbsac. eecs.berkeley.edu/projects/ivy/ (last accessed November 20, 2012).
 K. Doughty, R. Lewis, and A. McIntosh, ―The Design of a Practical and Reliable Fall Detector for Community and Institutional Telecare‖, Journal of Telemedicine and Telecare, vol. 6, no. Suppl 1, 2000, pp. S150-154.
 J. Hill, R. Szewczyk, A. Woo, S. Hollar, D. Culler, and K. Pister, ―System Architecture Directions for Networked Sensors‖, SIGPLAN Not., vol. 35, no. 11, 2000, pp. 93-104.
 CMT Consulting Measurement Technology GmbH. Mica2Dot Platform. http://www.cmt-gmbh.de/Mica2dot.pdf (last accessed November 20, 2012).
 N.K. Suryadevara, A.Gaddam, R.K. Rayudu, and S.C. Mukhopadhyay, ―Wireless sensors network based safe home to care elderly people: Behaviour detection‖, In Proc. Eurosensors XXV, September 4-7, 2011, Athens, Greece, Elsivier Procedia Engineering, vol. 25, 2011, pp. 96 – 99.
 N.K. Suryadevara, M.T. Quazi, and S.C. Mukhopadhyay, ―Intelligent sensing systems for measuring wellness indices of the daily activities for the elderly‖, Proc. 8th International Conference on Intelligent Environments (IE 2012), 26-29 June 2012, pp. 347-350, Guanajuato, Mexico, 2012.
 Y.-M. Huang, M.Y. Hsieh, H.C. Chao, S.H. Hung, and J.H. Park, ―Pervasive, secure access to a hierarchical sensor-based healthcare monitoring architecture in wireless heterogeneous networks‖, IEEE Journal on Selected Areas in Communications, vol. 27, no. 4, 2009, pp. 400-411.
 C.-F. Lai, Y.-M. Huang, J.H. Park, and H.-C. Chao, ―Adaptive Body Posture Analysis for Elderly-Falling Detection with Multisensors‖, IEEE Intelligent Systems, vol. 25, no. 2, 2010, pp. 20-30.
 B.U. Toreyin, Y. Dedeoglu, and A.E. Cetin, ―HMM Based Falling Person Detection Using Both Audio and Video‖, In Proc. IEEE 14th Signal Processing and Communications Applications, pp. 1-4, Antalya, Turkey, 2006.
 S.G. Miaou, P.H. Sung, and C.Y. Huang, ―A Customized Human Fall Detection System Using Omni-Camera Images and Personal Information‖, In Proc. 1st Transdisciplinary Conference on Distributed Diagnosis and Home Healthcare (D2H2), pp. 39-42, Virginia, USA, 2006.
 H. Nait-Charif, and S.J. McKenna, ―Activity Summarisation and Fall Detection in a Supportive Home Environment‖, In Proc. 17th International Conference on Pattern Recognition (ICPR 2004), vol. 4, pp. 323-326, Cambridge, UK, 2004.
 H. Foroughi, B.S. Aski, and H. Pourreza, ―Intelligent Video Surveillance for Monitoring Fall Detection of Elderly in Home Environments‖, In Proc. 11th International Conference on Computer and Information Technology (ICCIT 2008), pp. 219-224, Khulna, Bangladesh, 2008.
 A.H. Nasution and S. Emmanuel, ―Intelligent Video Surveillance for Monitoring Elderly in Home Environments‖, In Proc. IEEE 9th Workshop on Multimedia Signal Processing (MMSP 2007), pp. 203-206, Greece, 2007.
 G. Sannino and G.D. Pietro, ―An Advanced Mobile System for Indoor Patients Monitoring‖, In Proc. 2nd International Conference on Networking and Information Technology (ICNIT 2011), pp. 17, Singapore, IACSIT Press, 2011.
 Alive Technologies Products, Alive Monitoring Sensors, 2003. http://www.alivetec.com/ (last accessed November 21, 2012).
 T.R. Burchfield and S. Venkatesan, ―Accelerometer-based Human Abnormal Movement Detection in Wireless Sensor Networks‖, In Proc. 1st ACM SIGMOBILE International Workshop on Systems and Networking Support for Healthcare and Assisted Living Environments (HealthNet 07), pp. 67-69, New York, USA, ACM, 2007.
 A. Williams, D. Xie, S. Ou, R. Grupen, A. Hanson, and E. Riseman, ―Distributed Smart Cameras for Aging in Place‖, In Proc. ACM SenSys Workshop on Distributed Smart Cameras, 2006, Colorado, USA, ACM.
 F. Sposaro and G. Tyson, ―iFall: An Android Application for Fall Monitoring and Response‖, In Proc. Annual International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 6119-6122, Minneapolis, Minnesota, USA, 3-6 Sept., 2009.
 T. Zhang, J. Wang, P. Liu, and J. Hou, ―Fall Detection by Embedding an Accelerometer in Cellphone and Using KFD Algorithm‖, International Journal of Computer Science and Network Security, vol. 6, no. 10, 2006, pp. 277-283.
 AlertOne Services, Inc., iLifeR Fall Detection Sensor, 2004. http://www.falldetection.com/iLifeFDS.asp (last accessed November 21, 2012).
 Halo Monitoring, Inc., myHaloR Medical Alert Systems, 2009. http://www.halomonitoring.com/ (last accessed November 21, 2012).
 Life Alert Emergency Response, Inc., LIFE ALERTR Classic, 2009. http://www.lifealert.com/ (last accessed November 21, 2012).
 S. Khawandi, B. Daya, and P. Chauvet, ―Automated Monitoring System for Fall Detection in the Elderly‖, International Journal of Image Processing, vol. 4, no. 5, 2010, pp. 476-483.
 M.J. Mathie, A.C.F. Coster, N.H. Lovell, and B.G. Celler, ―Accelerometry: Providing an Integrated, Practical Method for Longterm, Ambulatory Monitoring of Human Movement‖, Physiological Measurement, vol. 25, no. 2, 2004, pp. R1-R20.
 A.K. Bourke, C.N. Scanaill, K.M. Culhane, J.V. OBrien, and G.M. Lyons, ―An Optimum Accelerometer Configuration and Simple Algorithm for Accurately Detecting Falls‖, In Proc. 24th IASTED International Conference on Biomedical Engineering, (BioMed06), pp. 156-160, Anaheim, CA, USA, ACTA Press, 2006.
 M. Kangas, A. Konttila, P. Lindgren, I. Winblad, and T. Jms, ―Comparison of Low-complexity Fall Detection Algorithms for Body Attached Accelerometers‖, Gait & Posture, vol. 28, no. 2, 2008, pp. 285- 291.
 P.-K. Chao, H.-L. Chan, F.-T. Tang, Y.-C. Chen, and M.-K. Wong, ―A Comparison of Automatic Fall Detection by the Cross-product and Magnitude of Tri-axial Acceleration‖, Physiological Measurement, vol. 30, no. 10, 2009, pp. 1027-1037.
 A.K. Bourke and G.M. Lyons, ―A Threshold-based Fall-detection Algorithm Using a Bi-axial Gyroscope Sensor‖, Medical Engineering & Physics, vol. 30, no. 1, 2008, pp. 84-90.
 M. Lustrek and B. Kaluza, ―Fall Detection and Activity Recognition with Machine Learning‖, Informatica (Slovenia), vol. 33, no. 2, 2009, pp. 197-204.
 T. Tamura, ―Home Geriatric Physiological Measurements‖, Physiological Measurement, vol. 33, no. 10, 2012, pp. R47-65.
 T. Tamura, T. Yoshimura, M. Sekine, ―Uchida M., and Tanaka O. A Wearable Airbag to Prevent Fall Injuries‖, IEEE Transactions on Information Technology in Biomedicine, vol. 13, no. 6, 2009, pp. 910-914.
 Smart Caregiver Corporation. Fall Monitoring and Anti-Wandering Facilities. http://www.smartcaregivercorp.com/ (last accessed November 21, 2012).
 R. Cucchiara, A. Prati, and R. Vezzani, ―An Intelligent Surveillance System for Dangerous Situation Detection in Home Environments‖, Intelligenza Artificiale, vol. 1, no. 1, 2004, pp. 11-15.
 T. Lee and A. Mihailidis, ―An Intelligent Emergency Response System: Preliminary Development and Testing of Automated Fall Detection‖, Journal of Telemedicine and Telecare, vol. 11, no. 4, 2005, pp. 194-198.
 J. Tao, M. Turjo, M.-F. Wong, M. Wang, and Y.-P. Tan, ―Fall Incidents Detection for Intelligent Video Surveillance‖, In Proc. Fifth International Conference on Information, Communications and Signal Processing (ICICS ’05), pp. 1590-1594, Bangkok, Thailand, 2005.
 C. Rougier, J. Meunier, A. St-Arnaud, and J. Rousseau, ―Monocular 3D Head Tracking to Detect Falls of Elderly People‖, In Proc. 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 06), pp. 6384-6387, New York City, New York, USA, 2006.
 M. Kangas, A. Konttila, I. Winblad, and T. Jamsa, ―Determination of Simple Thresholds for Accelerometry-based Parameters for Fall Detection‖, In Proc. 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 2007), pp. 1367-1370, Lyon, France, 2007.
 P.-C. Chung and C.-D. Liu, ―A Daily Behavior Enabled Hidden Markov Model for Human Behavior Understanding‖, Pattern Recogn., vol. 41, no. 5, 2008, pp. 1589-1597.
 C. Thurau, ―Behavior Histograms for Action Recognition and Human Detection‖, In Proc. 2nd Workshop (Human Motion 2007), October 20, 2007, Rio de Janeiro, Brazil, Lecture Notes in Computer Science, Berlin, Heidelberg: Springer-Verlag, vol. 4814, pp. 299-312.
 M. Giersich, P. Forbrig, G. Fuchs, T. Kirste, D. Reichart, and H. Schumann, ―Towards an Integrated Approach for Task Modeling and Human Behavior Recognition‖, In Proc. 12th International Conference on Human-computer Interaction: Interaction Design and Usability (HCI07), pp. 1109-1118, Beijing, China, July 22-27, 2007.
 M. Grassi, A. Lombardi, G. Rescio, P. Malcovati, A. Leone, G. Diraco, C. Distante, P. Siciliano, M. Malfatti, L. Gonzo, V. Libal, J. Huang and G. Potamiano, ―A Multisensor System for High Reliability People Fall Detection in Home Environment‖, In Lecture Notes in Electrical Engineering, Sensors and Microsystems, P. Malcovati, A. Baschirotto, A. D’Amico and C. Di Natale, Ed., Springer, Dordrecht, The Netherlands, 2010, vol. 54, pp. 391-394.
 M. Redzic, C. Brennan, and N.E. OConnor, ―Indoor Localisation Based on Fusing WLAN and Image Data‖, In Proc. IEEE International Conference on Indoor Positioning and Indoor Navigation (IPIN 2011), Guimaraes, Portugal, 21-23 Sept., 2011.
 M. Dibitonto, A. Buonaiuto, G.L. Marcialis, D. Muntoni, C.M. Medaglia, and F. Roli, ―Fusion of Radio and Video Localization for People Tracking‖, In Proc. the Second International Conference on Ambient Intelligence (AmI’11), pp. 258-263, Amsterdam, The Netherlands, 16-18 November, 2011.