Abstract
Tele-rehabilitation has been widely studied in recent year, although a number of crucial issues has not been addressed. Quantitatively assessing exercise performance is vital in monitoring the progress in exercise based rehabilitation. This allows physiotherapists not only to refine rehabilitation plans, but also provides instant feedback to patients and facilitate the exercise performance in non-clinical setting. In this paper, we propose to evaluate the performance of upper extremity reaching tasks with in a kinematic perspective by assessing the smoothness of motion trajectories with the entropy of shape model, including curvature and torsion. The simulation result confirms that approximate entropy of shape model is consistent with the change of the smoothness in motion trajectory while it is capable of classifying six levels of the ability to perform upper extremity reaching tasks with higher accuracy.
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References
Hailey, D., Roine, R., Ohinmaa, A., Dennett, L.: Evidence of benefit from telerehabilitation in routine care: a systematic review. Journal of Telemedicine and Telecare 17(6), 281–287 (2011)
Kairy, D., Lehoux, P., Vincent, C., Visintin, M.: A systematic review of clinical outcomes, clinical process, healthcare utilization and costs associated with telerehabilitation. Disability and Rehabilitation 31(6), 427–447 (2009)
Winters, J.M.: Telerehabilitation research: emerging opportunities. Annu. Rev. Biomed. Eng. 4, 287–320 (2002)
Natl. Inst. Disabil. Rehabil. Res. request for applications for Rehabilitation Engi neering Research Center on Telerehabilitation. Fed. Regist., 3252639 (June 12, 1998)
Gummesson, C., Atroshi, I., Ekdahl, C.: The disabilities of the arm, shoulder and hand (DASH) outcome questionnaire: longitudinal construct validity and measuring self-rated health change after surgery. BMC Musculoskeletal Disorders 4(1), 11 (2003)
Levine, D.W., Simmons, B.P., Koris, M.J., Daltroy, L.H., Hohl, G.G., Fossel, A.H., Katz, J.N.: A self-administered questionnaire for the assessment of severity of symptoms and functional status in carpal tunnel syndrome. (1993)
Roach, K.E., Budiman-Mak, E., Songsiridej, N., Lertratanakul, Y.: Development of a Shoulder Pain and Disability Index. Arthritis & Rheumatism 4(4), 143–149 (1991)
Dowrick, A.S., Gabbe, B.J., Williamson, O.D., Cameron, P.A.: Outcome instruments for the assessment of the upper extremity following trauma: a review. Injury 36(4), 468–476 (2005)
Wolf, S.L., Catlin, P.A., Ellis, M., Archer, A.L., Morgan, B., Piacentino, A.: Assessing Wolf Motor Function Test as Outcome Measure for Research in Patients After Stroke. Stroke 32(7), 1635–1639 (2001)
Goetz, C.G., Stebbins, G.T., Shale, H.M., Lang, A.E., Chernik, D.A., Chmura, T.A., Ahlskog, J.E., Dorflinger, E.E.: Utility of an objective dyskinesia rating scale for Parkinson’s disease: Inter- and intrarater reliability assessment. Movement Disorders 9(4), 390–394 (1994)
Aggarwal, A., Aggarwal, N., Nagral, A., Jankharia, G., Bhatt, M.: A novel Global Assessment Scale for Wilson’s Disease (GAS for WD). Movement Disorders 24(4), 509–518 (2009)
Feng, X., Johnson, M.J., Johnson, L.M., Winters, J.M.: A suite of computer-assisted techniques for assessing upper-extremity motor impairments. In: 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 (2005)
Olesh, E.V., Yakovenko, S., Gritsenko, V.: Automated Assessment of Upper Extremity Movement Impairment due to Stroke. PloS one 9(8), e104487 (2014)
Caviness, J.N., Brown, P.: Myoclonus: current concepts and recent advances. The Lancet Neurology 3(10), 598–607 (2004)
Clarke, J.M.: On Huntington’s Chorea (1897)
Sanger, T.D., Chen, D., Fehlings, D.L., Hallett, M., Lang, A.E., Mink, J.W., Singer, H.S., Alter, K., Ben-Pazi, H., Butler, E.E., Chen, R., Collins, A., Dayanidhi, S., Forssberg, H., Fowler, E., Gilbert, D.L., Gorman, S.L., Gormley, M.E., Jinnah, H.A., Kornblau, B., Krosschell, K.J., Lehman, R.K., MacKinnon, C., Malanga, C.J., Mesterman, R., Michaels, M.B., Pearson, T.S., Rose, J., Russman, B.S., Sternad, D., Swoboda, K.J., Valero-Cuevas, F.: Definition and classification of hyperkinetic movements in childhood. Movement Disorders 25(11), 1538–1549 (2010)
Shannon, C.E.: A mathematical theory of communication. SIGMOBILE Mob. Comput. Commun. Rev. 5(1), 3–55 (2001)
Pincus, S.: “Approximate entropy (ApEn) as a complexity measure.” Chaos: An Interdisciplinary. Journal of Nonlinear Science 5(1), 110–117 (1995)
Richman, J.S., Moorman, J.R: Physiological time-series analysis using approximate entropy and sample entropy (2000)
Freedman, D., Diaconis, P.: On the Histogram as a Density Estimator - L2 Theory. Zeitschrift Fur Wahrscheinlichkeitstheorie Und Verwandte Gebiete 57(4), 453–476 (1981)
Reynolds, D.: Gaussian mixture models. In: Li, S. Jain, A.(eds.) Encyclopedia of Biometrics. Springer, US, pp. 659–663 (2009)
Saiyi, L., Caelli, T., Ferraro, M., Pathirana, P.N.: A novel bio-kinematic encoder for human exercise representation and decomposition - part 1: indexing and modelling. In: 2013 International Conference on Control, Automation and Information Sciences (ICCAIS) (2013)
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Li, S., Pathirana, P.N. (2015). A Kinematic Based Evaluation of Upper Extremity Movement Smoothness for Tele-Rehabilitation. In: Geissbühler, A., Demongeot, J., Mokhtari, M., Abdulrazak, B., Aloulou, H. (eds) Inclusive Smart Cities and e-Health. ICOST 2015. Lecture Notes in Computer Science(), vol 9102. Springer, Cham. https://doi.org/10.1007/978-3-319-19312-0_18
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DOI: https://doi.org/10.1007/978-3-319-19312-0_18
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