ENG  Vol.4 No.10 , October 2012
Towards a Methodology for the Differential Analysis in Human Locomotion: A Pilot Study on the Participation of Individuals with Multiple Sclerosis
ABSTRACT

Multiple sclerosis (MS) is an unpredictable disease of the central nervous system that can range from relatively benign to somewhat disabling to devastating, as communication between the brain and other parts of the body is disrupted. Scientists have learned a great deal about MS in recent years; yet still, its cause remains elusive. This paper intends to investigate the hypothesis that gait dynamics have meaning and may be useful in providing insight into the neural control of locomotion. It further seeks to explore the mutual interactions and influences of MS functions on gait, and vice versa, in a quantitative and robust fashion. Ground reaction forces (GRFs), muscle activities, and segmental accelerations within a gait cycle were analyzed in this study. Patterns of the signals from six relapsing-remitting multiple sclerosis (RRMS) patients were compared with the healthy subjects. This quantitative gait analysis aids to illuminate a better understanding of the mobility-related disease such as RRMS characteristics. An outcome of this study is a reproducible methodology for helping therapists make reliable and differentiable diagnosis, design a tailored therapeutic strategy, and comfortably evaluate the follow-ups on patient’s functional recovery.

Cite this paper
H. Yu and T. Sarkodie-Gyan, "Towards a Methodology for the Differential Analysis in Human Locomotion: A Pilot Study on the Participation of Individuals with Multiple Sclerosis," Engineering, Vol. 4 No. 10, 2012, pp. 20-26. doi: 10.4236/eng.2012.410B006.
References
[1]   Albrecht H., Wotzel C., Erasmus L.P., Kleinpeter M., Konig N., Pollmann W., “Day-to-day variability of maximum walking distance in MS patients can mislead to relevant changes in the Expanded Disability Status Scale (EDSS): average walking speed is a more constant parameter”, Mult Scler. 2001;7(2):105-109

[2]   Cappozzo A., Catani F., Leardini A., Benedetti M.G., Croce UD., “Position and orientation in space of bones during movement: experimental artifacts.” Clin Biomech,1996; 11(2):90-100

[3]   De Luca C.J. “The use of surface electromyography in biomechanics” Journal of Applied Biomechanics, 1997; 13(2): 135-163

[4]   Fischer J.S., Rudick R.A., Cutter G.R., Reingold S.C., “The Multiple Sclerosis Functional Composite measure (MSFC): an integrated approach to MS clinical outcome assessment”, Mult Scler August 1999; 5:244-250

[5]   Giansanti D., Macellari V., and Maccioni G. (2005) “The development and test of a device for the reconstruction of 3-D position and orientation by means of a kinematic sensor assembly with rate gyroscopes and accelerometers” IEEE Trans Biomed Eng, vol. 52, no. 7, pp. 1271-1277

[6]   Hausdorff J.M., “Gait variability: methods, modeling and meaning” Journal of NeuroEngineering and Rehabilitation, 2005; 2:19-27

[7]   Higginson J.S., Zajac F.E., Neptune R.R., Kautz S.A., Delp S.L., “Muscle contributions to support during gait in an individual with post-stroke hemiparesis”. J Biomech 2005

[8]   Hobart J.C., Riazi A., Lamping D.L., Fitzpatrick R., Thompson A.J., “Measuring the impact of MS on walking ability. The 12-item MS Walking Scale (MSWS-12)”, Neurology. 2003;60(1):31-36

[9]   Hohol M.J., Orav E.J., Weiner H.L., “Disease Steps in multiple sclerosis: A simple approach to evaluate disease progression”, Neurology February, 1995;45(2):251-255

[10]   Hoogervorst E.L., van Winsen L.M., Eikelenboom M.J., Kalkers N.F., Untdehaag B.M., Polman C.H., “Comparisons of patient self-report, neurologic examination, and functional impairment in MS”, Neurology. 2001; 56(7):934-937

[11]   Huiying Yu, Murad Alaqtash, Eric Spier, Thompson Sarkodie-Gyan, “Analysis of muscle activity during gait cycle using fuzzy rule-based reasoning”, Elsevier Journal of Measurement, April, 2010; 43(9):1106-1114

[12]   Kaufman M., Moyer D., Norton J., “The significant change for the Timed 25-Foot Walk in Multiple Sclerosis Functional Composite”, Mult Scler. 2000;6(4):286-290

[13]   Kelleher K.J., Spence W.D., Solomonidis S.E., Apatsidis D. “The characterization of gait patterns with multiple sclerosis”. Disabil Rehabil. 2010; 32(15): 1242-50

[14]   Kesselring J., “Multiple Sclerosis”. Cambridge University Press, 1997

[15]   Legters K., Whitney S.L., Porter R., Buczek F., “The relationship between the Activities-specific Balance Confidence Scale and the Dynamic Gait Index in peripheral vestibular dysfunction”, Physiotherapy Research International. 2005;10(1):10-22

[16]   Liu T., Inoue Y., Shibata K., “Development of a wearable sensor system for quantitative gait analysis”, Measurement. 2009; 42(7):978-988

[17]   Marchetti G.F., Whitney S.L., “Construction and Validation of the 4-Item Dynamic Gait Index”, Physical Therapy. 2006;86(12):1651-1660

[18]   McConvey J., Bennett S.E., “Reliability of the Dynamic Gait Index in Individuals with multiple sclerosis”, Archives of Physical Medicine and Rehabilitation. 2005; 86:130-133

[19]   McGuigan C., Hutchinson M., “Confirming the validity and responsiveness of the Multiple Sclerosis Walking Scale-12 (MSWS-12)”, Neurology. 2004;62(11):2103-2105

[20]   National Institute of Neurological Disorders and Stroke (NINDS). (2006a, last updated January). NINDS Multiple Sclerosis Information Page, 2006

[21]   Nieuwenhuis M.M., Tongeren H.V., Sorensen P.S., Ravnborg M., “The Six Spot Step Test: a new measurement for walking ability in multiple sclerosis”, Mult Scler. 2006;12(4):495-500

[22]   Noseworthy J.H., “Clinical scoring methods for multiple sclerosis”, Ann Neurol. 1994; 36 Suppl:S80-5

[23]   Pringle D., Seger A.M., and Ponichtera-Mulcare J., “Locomotive function in individuals with multiple sclerosis”, Biomedical Engineering Conference, 1996; pp 433-436

[24]   Pullman S.L., Goodin D.S., Marquinez A.I., Tabbal S., Rubin M., “Clinical utility of surface EMG” Report of the therapeutics and technology assessment subcommittee of the American Academy of Neurology, Neurology, 2000; 55:171-177

[25]   Rocon E., Moreno J.C., Ruiz A.F., Brunetti F., Miranda J.A., and Pons J.L., “Application of inertial sensors in rehabilitation robotics”, proceeding of the 2007 IEEE 10th International Conference on Rehabilitation Robotics, June 12-15, 2007, Noordwijk, The Netherlands

[26]   Ruth E. Mayagoitaia, Anand V. Nene, Peter H. Veltink (2002) “Accelerometer and rate gyroscope measurement of kinematics: an inexpensive alternative to optical motion analysis systems” Elsevier Journal of Biomechanics, pp. 537-542

[27]   Sutliff M.H., “Contribution of impaired mobility to patient burden in multiple sclerosis” Current Medical Research and Opinion, 2010; 26(1):109-119

[28]   Winter D.A. (1991) “Biomechanics and Motor control of Human Gait: Normal, Elderly and Pathological”. Waterloo Biomechanics Press. Waterloo, Ontario

[29]   World Health Organization, “Neurological Disorders: Public health challenges”, 2006

[30]   Wurdeman S.R., Huisinga J.M., Filipi M., and Stergiou N., “Multiple sclerosis affects the frequency content in the vertical ground reaction forces during walking”, Clinical Biomechanics, 2010; 26(2):207-212.

 
 
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