HOME-BASED ANKLE REHABILITATION SYSTEM: LITERATURE REVIEW AND EVALUATION

Lim Ch ee Chin, Shafriza Nisha Basah, Marwan Affandi, Muhammad Nazrin Shah, Sazali Yaacob, Yeap Ewe Juan, Mohamad Yazid Din

Abstract


Ankle sprain Injury is one of the most common ankle injuries due to domestic or sporting accidents. There is a need for greater demand for quick and effective ankle rehabilitation system (ARS). Nowadays, research on ARS has gained a great attention than manual clinical method in medical areas such as orthopedic injuries, pediatrics sport medicine and industrial services. It can improve the treatment conditions by reducing the dependency of doctors’ supervision, help patient with less movable to have home-based rehab exercise and help to speeds up recovery. There are currently available ARS that can provide effective ankle rehabilitation treatment such as Visual, Non-Visual and Robot-aided. In this paper, the critical review of ARS is conducted to evaluate the effectiveness of ARS in terms of provided setting criteria. The strengths, weaknesses, opportunities and threats of each ARS is discussed and compared to identify the most suitable home application of ARS for ankle sprain patient. From the comparison, the most suitable home application ARS is the visual marker-less based ARS system which give user-friendly, efficiency, validity in performance and cheaper cost. 


Keywords


Ankle Injury, Ankle Rehabilitation System (ARS), Visual-Based Rehabilitation, Robot-based Ankle Rehabilitation System

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References


MedicineNet. 2012. Ankle Sprain Definition-MedicineNet-Health and Medical Information Produced by Doctors. Retrieved December 5, 2014, from http://www.medicinenet.com/script/main/art.asp?articlekey=24348.

Victor, I., Zinovy, M., & Andre, P. (n.d.). Ankle Sprains and the Athlete. Retrieved December 5, 2014, from https://www.acsm.org/docs/current-comments/anklesprainstemp.pdf.

Henry, J. H., Lareau, B., & Neigut, D. 1982. The Injury Rate in Professional Basketball. The American Journal of Sports Medicine. 10(1): 16-18. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/6797308.

Keyfitz, R. 2010. Design of a Range of Motion Sensor for Ankle Rehabilitation Monitor. Thesis. Department of Electrical and Biomedical Engineering, McMaster University; Hamilton, ON, Canada.

Diamond, J. E. 1989. Rehabilitation of Ankle Sprains. Clinics in Sports Medicine. 8(4): 877-91. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/2688911.

Fong, D. T.-P., Chan, Y.-Y., Hong, Y., Yung, P. S.-H., Fung, K.-Y., & Chan, K.-M. 2008. A Three-pressure-sensor (3PS) System for Monitoring Ankle Supination Torque During Sport Motions. Journal of Biomechanics. 41(11): 2562-6.

Lamb, S. E., Marsh, J. L., Hutton, J. L., Nakash, R., & Cooke, M. W. 2009. Mechanical supports for Acute, Severe Ankle Sprain: A Pragmatic, Multicentre, Randomised Controlled Trial. Lancet. 373(9663): 575-81.

Ekstrand, J., & Gillquist, J. 1983. Soccer Injuries and Their Mechanisms: A Prospective Study. Medicine and Science in Sports and Exercise. 15(3): 267-70. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/6621313.

Micheli, L. J. (Ed.). 2010. Encyclopedia of Sports Medicine (Vol. 17). United States, America: SAGE Publications. Retrieved from http://books.google.com/books?id=VxpzAwAAQBAJ&pgis=1.

American Orthopaedic Foot & Ankle Society. (n.d.). How to Care for a Sprained Ankle. Retrieved December 5, 2014, from http://www.aofas.org/footcaremd/how-to/foot-injury/Pages/How to Care for a Sprained Ankle.aspx.

Ding;, Y., Sivak;, M., Weinberg;, B., Mavroidis;, C., & Holderr;, M. K. 2010. NUVABAT: Northestern University Virtual Ankle and Balance Trainer. In IEEE Haptics Symposium 2010. IEEE. Retrieved from http://www.coe.neu.edu/Research/robots/papers/Haptics2010_1.pdf.

Hughes, R. G. (Ed.). (n.d.). Patient Safety and Quality: An Evidence-Based Handbook for Nurses. 540 Gaither Road Rockville, MD 20850: AHRQ Publication No. 08-0043. Rockville, MD: Agency for Healthcare Research and Quality. Retrieved from http://www.ahrq.gov/professionals/clinicians-providers/resources/nursing/resources/nurseshdbk/nurseshdbk.pdf.

Alcocer, W., Vela, L., Blanco, A., Gonzalez, J., & Oliver, M. 2012. Major Trends in the Development of Ankle Rehabilitation DeviceS. Dyna. 79(176): 45-55.

Zhang, M., Davies, T. C., & Xie, S. 2013. Effectiveness of Robot-assisted Therapy on Ankle Rehabilitation--a Systematic Review. Journal of Neuroengineering and Rehabilitation. 10(1): 30.

Zhou, H., Stone, T., Hu, H., & Harris, N. 2008. Use of Multiple Wearable Inertial Sensors in Upper Limb Motion Tracking. Medical Engineering & Physics. 30(1): 123-33.

Lenz, J. E. 1990. A Review of Magnetic Sensors. Proceedings of the IEEE. 78(6): 973-989.

Aiello, E., Gates, D. H., Patritti, B. L., Cairns, K. D., Meister, M., Clancy, E. A., … Hospital, S. R. 2005. Visual EMG Biofeedback to Improve Ankle Function in Hemiparetic Gait. Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference. 7703-7706). Shanghai, China: IEEE.

Clark, R. A., Pua, Y. H., Fortin, K., Ritchie, C., Webster, K. E., Denehy, L., & Bryant, A. L. 2012. Validity of the Microsoft Kinect for Assessment of Postural Control. Gait & Posture. 36(3): 372-377.

Tsoi, Y., Xie, S. Q., & Graham, A. E. (n.d.). Design, Modeling and Control of an Ankle Rehabilitation Robot. 377-399.

American College of Foot and Ankle Surgeons. 2009, December 18. Foot & Ankle Conditions: Ankle Sprain. American College of Foot and Ankle Surgeons. Retrieved December 5, 2014, from http://www.foothealthfacts.org/footankleinfo/ankle-sprain.htm.

Kim, H. Y., Wang, J., Chung, K., & Chung, J. M. 2008. A surgical Ankle Sprain Pain Model in the Rat: Effects of Morphine and Indomethacin. Neuroscience Letters. 442(2): 161-4.

Brown, C., Padua, D., Marshall, S. W., & Guskiewicz, K. 2008. Individuals with Mechanical Ankle Instability Exhibit Different Motion Patterns Than Those with Functional Ankle Instability and Ankle Sprain Copers. Clinical Biomechanics (Bristol, Avon). 23(6): 822-31.

Nawata, K., Nishihara, S., Hayashi, I., & Teshima, R. 2005. Plantar pressure Distribution During Gait in Athletes with Functional Instability of the Ankle Joint: Preliminary Report. Journal of Orthopaedic Science: Official Journal of the Japanese Orthopaedic Association. 10(3): 298-301.

Nasseri, N., Almasganj, F., Najarian, S., & Farkoush, S. H. 2009. An Embedded Insole, Applicable in Signal Processing: Sprained Ankle Assessment. International Journal of Intelligent Information Technology Application. 2(4).

Bó, A. P. L., Hayashibe, M., & Poignet, P. 2011. Joint Angle Estimation in Rehabilitation with Inertial Sensors and Its Integration With Kinect. Conference Proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference. 2011: 3479-83.

UHN Rehabilitaiton Solutions, & Network, U. H. 2009. Ankle Rehabilitation Protocol. Bathurst St., Toronto, Ontario.

Liu, D., Wang, L., & Tan, K. C. 2009. Design and Control of Intelligent Robotic Systems. Springer. Retrieved from http://ezproxy.unimap.edu.my:2259/book/10.1007/978-3-540-89933-4.

McNally, N., & Erhuy, I. 2009. The Trainer’s Room: Sprained Ankle Treatment, Rehab, and Recovery Time. Mountail View Pain Center in Denver, CO: Midwest Sports Fans. Retrieved from http://www.midwestsportsfans.com/2009/04/sprained-ankle-treatment-rehab-recovery-time-ankle-sprain-grade-ligaments-chronic-ankle-sprains-denver/.

Zhou, H., & Hu, H. 2004. A Survey-Human Movement Tracking and Stroke Rehabilitation. United Kingdom.

Zhou, H., & Hu, H. 2008. Human motion Tracking for Rehabilitation-A Survey. Biomedical Signal Processing and Control. 3(1): 1-18.

Barry, G., Galna, B., & Rochester, L. 2014. The Role of Exergaming in Parkinson’s Disease Rehabilitation: A Systematic Review of the Evidence. Journal of Neuroengineering and Rehabilitation. 11: 33.

Kikuchi, T., Xinghao, H., Fukushima, K., Oda, K., Furusho, J., & Inoue, A. 2007. Quasi-3-DOF Rehabilitation System for Upper Limbs : Its Force-Feedback Mechanism and Software for Rehabilitation. 2007 IEEE 10th International Conference on Rehabilitation Robotics, Noordwijk. 24-27.

Nordin, N., Xie, S. Q., & Wünsche, B. 2014. Assessment of Movement Quality in Robot-assisted Upper Limb Rehabilitation After Stroke: A Review. Journal of Neuroengineering and Rehabilitation. 11(1): 137.

Norouzi-Gheidari, N., Archambault, P. S., & Fung, J. 2012. Effects of Robot-assisted Therapy on Stroke Rehabilitation in Upper Limbs: Systematic Review and Meta-analysis of the Literature. Journal of Rehabilitation Research and Development. 49(4): 479-96. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/22773253.

Thomson, K., Pollock, A., Bugge, C., & Brady, M. 2014. Commercial Gaming Devices for Stroke Upper Limb Rehabilitation: A Systematic Review. International Journal of Stroke : Official Journal of the International Stroke Society. 9(4): 479-88.

Díaz, I., Gil, J. J., & Sánchez, E. 2011. Lower-Limb Robotic Rehabilitation: Literature Review and Challenges. Journal of Robotics. 2011(i): 1-11.

Martin, R. L., & Irrgang, J. J. 2007. A Survey of Self-reported Outcome Instruments for the Foot and Ankle. The Journal of Orthopaedic and Sports Physical Therapy. 37(2): 72-84.

Fodor, L., Sobec, R., Sita-alb, L., Fodor, M., & Ciuce, C. 2012. Mangled lower Extremity : Can We Trust the Amputation Scores. International Journal of Burns and Trauma. 2(1): 51-58.

Zoch, C., Fialka-Moser, V., & Quittan, M. 2003. Rehabilitation of Ligamentous Ankle Injuries: A Review of Recent Studies. British Journal of Sports Medicine. 37: 291-295.

Mattacola, C. G., & Dwyer, M. K. 2002. Rehabilitation of the Ankle After Acute Sprain or Chronic Instability. Journal of Athletic Training. 37(4): 413-429. Retrieved from http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=164373&tool=pmcentrez&rendertype=abstract.

Girone, M., Burdea, G., Bouzit, M., Popescu, V., & Deutsch, J. E. 2001. A Stewart Platform-Based System for Ankle Telerehabilitation. Autonomous Robots. 10(2): 203-212.

Liu, G., Gao, J., Yue, H., Zhang, X., & Lu, G. 2006. Design and Kinematics Simulation of Parallel Robots for Ankle Rehabilitation. 2006 International Conference on Mechatronics and Automation. 1109-1113.

Jungwon Yoon, & Ryu, J. 2005. A Novel Reconfigurable Ankle/Foot Rehabilitation Robot. Proceedings of the 2005 IEEE International Conference on Robotics and Automation). IEEE. 2290-2295.

Jamwal, P. K. 2011. Design Analysis and Control of Wearable Ankle Rehabilitation Robot. ResearchSpace@Auckland. Retrieved from https://researchspace.auckland.ac.nz/handle/2292/6868.

Tsoi, Y. H. 2011. Modelling and Adaptive Interaction Control of a Parallel Robot for Ankle Rehabilitation. ResearchSpace@Auckland. Retrieved from https://researchspace.auckland.ac.nz/handle/2292/6756.

Jungwon, Y., Jeha, R., Grigone, B., & Ranes, B. 2002. Control of The Rutgers Ankle Rehabilitation Interface. Proceedings of IMECE2002 ASME International Mechanical Engineering Congress & Exposition November 17-22, 2002 New Orleans, Louisian. New Orleans, Louisian: ASME. 1-8.

Deutsch, J. E., Latonio, J., Burdea, G. C., & Boian, R. 2001. Post-Stroke Rehabilitation with the Rutgers Ankle System: A Case Study. Presence: Teleoperators and Virtual Environments. 10(4): 416-430.

Boian, R. F., Bouzit, M., Burdea, G. C., Lewis, J., & Deutsch, J. E. 2005. Dual Stewart Platform Mobility Simulator. 9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005. IEEE. 550-555.

Muhammad Nazrin Shah, S. A. 2013. The Design and Development of Parallel Robot for Rehabilitation. University Malaysia Perlis.

Tsoi, Y. H., & Xie, S. Q. 2008. Design and Control of a Parallel Robot for Ankle Rehabiltation. 2008 15th International Conference on Mechatronics and Machine Vision in Practice. 515-520.

Tsoi, Y. H., Xie, S. Q., & Mallinson, G. D. 2009. Joint Force Control of Parallel Robot for Ankle Rehabilitation. 2009 IEEE International Conference on Control and Automation. 1856-1861.

Sun, J. G., Gao, J. Y., Zhang, J. H., & Tan, R. H. 2007. Teaching and Playback Control System for Parallel Robot for Ankle Joint Rehabilitation. 2007 IEEE International Conference on Industrial Engineering and Engineering Management. IEEE. 871-875.

Roy, A., Krebs, H. I., Member, S., Williams, D. J., Bever, C. T., Forrester, L. W., Hogan, N. 2009. Robot-aided Neurorehabilitation : A Novel Robot for Ankle Rehabilitation. IEEE Transactions on Robotics. 25(3): 569-582.

Jamwal, P. K., Xie, S. Q., Hussain, S., & Parsons, J. G. 2014. An Adaptive Wearable Parallel Robot for the Treatment of Ankle Injuries. IEEE/ASME Transactions on Mechatronics. 19(1): 64-75.

Saglia, J. A. 2010. Development of a High Performance Ankle Rehabilitation Robot-ARBOT. University of London. Retrieved from http://books.google.com.my/books/about/Development_of_a_High_Performance_Ankle.html?id=1HRaywAACAAJ&pgis=1.

Boonstra, M. C., van der Slikke, R. M. A., Keijsers, N. L. W., van Lummel, R. C., de Waal Malefijt, M. C., & Verdonschot, N. 2006. The Accuracy of Measuring the Kinematics of Rising from a Chair with Accelerometers and Gyroscopes. Journal of Biomechanics. 39(2): 354-8.

Uno, Y., Kawato, M., & Suzuki, R. 1989. Formation and Control of Optimal Trajectory in Human Multijoint Arm Movement. Biological Cybernetics. 61(2).

Zhao, J., & Badler, N. I. 1994. Inverse Kinematics Positioning Using Nonlinear Programming for Highly Articulated Figures. ACM Transactions on Graphics. 13(4): 313-336.

Neumann, U., & Azuma, R. 1999. Hybrid Inertial and Vision Tracking for Augmented Reality Registration. Proceedings IEEE Virtual Reality (Cat. No. 99CB36316). IEEE Comput. Soc. 260-267.

Nebot, E., & Durrant-Whyte, H. 1999. Initial Calibration and Alignment of Low-cost Inertial Navigation Units for Land Vehicle Applications. Journal of Robotic Systems. 16(2): 81-92.

Malkawi, A. M., & Srinivasan, R. S. 2004. Building Performance Visualization Using Augmented Reality. Proceedings of 14th International Conference on Computer Graphics.

Zhengrong Yao, & Haibo Li. 2004. Is A Magnetic Sensor Capable of Evaluating A Vision-based Face Tracking System? In Computer Vision and Pattern Recognition Workshop, 2004. CVPRW ’04. Conference on. IEEE. 74.

Zetu, D., Banerjee, P., & Thompson, D. 2000. Extended-range Hybrid Tracker and Applications to Motion and Camera Tracking in Manufacturing Systems. IEEE Transactions on Robotics and Automation. 16(3): 281-293.

Wang, Z., Kiryu, T., & Tamura, N. 2005. Personal Customizing Exercise with a Wearable Measurement and Control Unit. Journal Of Neuroengineering and Rehabilitation. 2: 14.

Mavroidis, C., Nikitczuk, J., Weinberg, B., Danaher, G., Jensen, K., Pelletier, P., Yasevac, D. 2005. Smart Portable Rehabilitation Devices. Journal of Neuroengineering and Rehabilitation. 2(1): 18.

Patten, C., Horak, F. B., & Krebs, D. E. 2003. Head and Body Center of Gravity Control Strategies: Adaptations Following Vestibular Rehabilitation. Acta oto-laryngologica. 123(1): 32-40. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/12625570.

Huang, M.-C., Xu, W., Su, Y., Lange, B., Chang, C.-Y., & Sarrafzadeh, M. 2012. SmartGlove for Upper Extremities Rehabilitative Gaming Assessment. Proceedings of the 5th International Conference on PErvasive Technologies Related to Assistive Environments-PETRA ’12. 1.

Geebelen, G., Cuypers, T., Maesen, S., & Bekaert, P. P. 2010. Real-time Hand Tracking with a Colored Glove. 3D Stereo media, Luik, Belgium. 1: 1-4.

Schr, M., Elbrechter, C., Maycock, J., Haschke, R., Botsch, M., & Ritter, H. (n.d.). Real-Time Hand Tracking with a Color Glove for the Actuation of Anthropomorphic Robot Hands.

Wang, R. Y., & Popović, J. 2009. Real-time Hand-tracking with a Color Glove. ACM SIGGRAPH 2009 Papers on-SIGGRAPH ’09. 1.

O’Donovan, K. J., Kamnik, R., O’Keeffe, D. T., & Lyons, G. M. 2007. An Inertial and Magnetic Sensor Based Technique for Joint Angle Measurement. Journal of Biomechanics. 40(12): 2604-2611.

Roetenberg, D. 2006. Inertial and Magnetic Sensing of Human Motion. Enschede: Twente University Press (TUP).

Sturman, D. J., & Zeltzer, D. 1994. A Survey of Glove-based Input. IEEE Computer Graphics and Applications. 14(1): 30-39.

Chang, C.-Y., Lange, B., Zhang, M., Koenig, S., Requejo, P., Somboon, N., Rizzo, A. 2012. Towards Pervasive Physical Rehabilitation Using Microsoft Kinect. Proceedings of the 6th International Conference on Pervasive Computing Technologies for Healthcare. IEEE. 2-5.

Cordella, F., Di Corato, F., Zollo, L., Siciliano, B., & van der Smagt, P. 2012. Patient performance Evaluation Using Kinect and Monte Carlo-based Finger Tracking. 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob). 1967-1972.

Lange, B., Chang, C.-Y., Suma, E., Newman, B., Rizzo, A. S., & Bolas, M. 2011. Development and Evaluation of Low Cost Game-based Balance Rehabilitation Tool Using the Microsoft Kinect Sensor. 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Boston, Massachusetts USA: IEEE. 2011: 1831-1834.

Huang, M., Chen, E., Xu, W., & Sarrafzadeh, M. 2011. Gaming for Upper Extremities Rehabilitation Categories and Subject Descriptors. Proceedings of the 2nd Conference on Wireless Health. ACM. 27.

Clarke, T. A., & Fryer, J. G. 1998. The Development of Camera Calibration. The Photogrammetric Record. 16(91): 51-66.

Tsai, Y. 2012. Kinempt : A Kinect-based Prompting System to Transition Autonomously Through Vocational Tasks for Individuals with Cognitive Impairments. Proceedings of the 14th international ACM SIGACCESS conference on Computers and accessibility). ACM. 299-300. Retrieved from http://dl.acm.org/citation.cfm?id=2385003.

WordPress.com, M. I. on. 2010. How Kinect Depth Sensor Works–Stereo Triangulation? Word Press.com. Retrieved December 6, 2014, from http://mirror2image.wordpress.com/2010/11/30/how-kinect-works-stereo-triangulation/.

Lim, C. C. 2016. A Visual Tracking Range of Motion Assessment System for Lower Limb Joint. Universiti Malaysia Perlis.

Roy, A., Krebs, H. I., Bever, C. T., Forrester, L. W., Macko, R. F., & Hogan, N. 2011. Measurement of Passive Ankle Stiffness iIn Subjects with Chronic Hemiparesis Using a Novel Ankle Robot. Journal Of Neurophysiology. 105(5): 2132-49.

Lim, C. C., Affandi, M., Basah, S. N., & Din, M. Y. 2017. Evaluating Lower Limb Joint Flexion by Computerized Visual Tacking System and Compared with Electrogoniometer and Universal Goniometer. 4th International Conference on Communication and Computer Engineering (ICOCOE 2017). Penang, Malaysia. 1-6.




DOI: http://dx.doi.org/10.11113/jt.v79.8468

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