Evaluation of a New Gait Assessment for Clinical Practice

Volume 1, Issue 2, December 2016     |     PP. 41-65      |     PDF (863 K)    |     Pub. Date: January 2, 2017
DOI:    380 Downloads     7935 Views  

Author(s)

Patric Schubert, Hochschule Fresenius, University of Applied Sciences, Institute for Complex Health Research, Idstein, Germany
Magnus Liebherr, Hochschule Fresenius, University of Applied Sciences, Institute for Complex Health Research, Idstein, Germany
Stephanie Kersten, Hochschule Fresenius, University of Applied Sciences, Institute for Complex Health Research, Idstein, Germany
Christian T Haas, Hochschule Fresenius, University of Applied Sciences, Institute for Complex Health Research, Idstein, Germany

Abstract
Objectives: Gait is often affected in people with motor disorders. Obtaining feasible parameters from gait measurements is a central issue in clinical reasoning. A key problem is that practicable tests lack sensitivity of underlying parameters and vice versa. To examine gait impairments or to evaluate interventions aimed at improving gait disorders, efficient measurements are necessary. Therefore, we developed a new device-independent gait assessment which allows the quantification of spatiotemporal parameters from over ground walking.Methods: 37 healthy subjects (CG), 14 patients with multiple sclerosis (MS) and 20 patients with Parkinson’s disease (PD) walked along a corridor at their self-paced velocity. A standardized new gait assessment without any technical devices was conducted. Subjects performed five walking trials of different lengths. Trespassing of predefined lines was used to determine real walking distance. Spatiotemporal gait parameters comprised gait velocity, stride length, and stride duration. Validity and reliability analyses were conducted.Results: The gait assessment showed highly valid and reliable results for each parameter and for each distance. Shorter walking distances showed a higher coefficient of variation which was however consistent for distances above 20m. We found significant differences between CG and MS, but no significance between CG and PD. Specific reference data for each parameter is presented.Conclusions: It is demonstrated that relevant biomechanical gait parameters could be derived from this new gait assessment with minimal effort. Hence, it could be easily implemented into clinical routines. We recommend performing at least five gait trials with at least 20m walking distance to achieve best results.

Keywords
Gait analysis, Biomechanical parameters, Parkinson’s disease, Multiple sclerosis

Cite this paper
Patric Schubert, Magnus Liebherr, Stephanie Kersten, Christian T Haas, Evaluation of a New Gait Assessment for Clinical Practice , SCIREA Journal of Health. Volume 1, Issue 2, December 2016 | PP. 41-65.

References

[ 1 ] Öberg T, Karsznia A and Öberg K. Basic gait parameters: reference data for normal sub-jects, 10-79 years of age. J Rehabil Res Dev 1993; 30(2): 210-223.
[ 2 ] Coutts F. Gait analysis in the therapeutic environment. Man Ther 1999; 4(1): 2-10.
[ 3 ] Yogev-Seligmann G, Hausdorff JM and Giladi N. The role of executive function and attention in gait. Mov Disord 2008; 23(3):329-342.
[ 4 ] Bohannon RW and Williams Andrews. A Normal walking speed: a descriptive meta-analysis. Physiotherapy 2011; 97(3): 182-189.
[ 5 ] Peel NM, Kuys SS and Klein K. Gait speed as a measure in geriatric assessment in clinical settings: a systematic review. J Gerontol A Biol Sci Med Sci 2012; 68(1): 39-46.
[ 6 ] Fransz DP, Huurnink A, Kingma I, Verhagen EA and van Dieën JH. A systematic review and meta-analysis of dynamic tests and related force plate parameters used to evaluate neuromusculoskeletal function in foot and ankle pathology. Clin Biomech 2013; 28(6): 591-601.
[ 7 ] Wren TA, Gorton GE 3rd, Ounpuu S and Tucker CA. Efficacy of clinical gait analysis: A systematic review. Gait Posture 2011; 34(2): 149-153.
[ 8 ] Podsiadlo D and Richardson S. The timed „Up & Go“: a test of basic functional mobility of frail elderly persons. J Am Geriatr Soc 1991; 39(2): 142-148.
[ 9 ] Tinetti ME. Performance-oriented assessment of mobility problems in elderly patients. J Am Geriatr Soc 1986; 34(2): 119-126.
[ 10 ] Shumway-Cook A and Woollacott M. Motor control: theory and practical applications. Baltimore (MD). Wilkins & Wilkins; 1995.
[ 11 ] Wrisley DM, Marchetti GF, Kuharsky DK and Whitney SL. Reliability, internal con-sistency, and validity of data obtained with the functional gait assessment. Phys Ther 2004; 84(10): 906-918.
[ 12 ] Harada ND, Chiu V and Stewart AL. Mobility-related function in older adults: assess-ment with a 6-minute walk test. Arch Phys Med Rehabil 1999; 80(7): 837-841.
[ 13 ] Rossier P and Wade DT. Validity and reliability comparison of 4 mobility measures in patients presenting with neurologic impairment. Arch Phys Med Rehabil 2001; 82(1): 9-13.
[ 14 ] Kieseier BC and Pozzilli C. Assessing walking disability in multiple sclerosis. Mult Scler 2012; 18(7): 914-924.
[ 15 ] Geroin, C. Mazzoleni S, Smania N, et al. Systematic review of outcome measures of walking training using electromechanical and robotic devices in patients with stroke. J Rehabil Med 2013; 45(10): 987-96.
[ 16 ] van Hedel HJA, Wirz M and Dietz V. Assessing walking ability in subjects with spinal cord injury: validity and reliability of 3 walking tests. Arch Phys Med Rehabil 2005; 86(2): 190-196.
[ 17 ] Ditunno P and Dittuno J. Walking index for spinal cord injury (WISCI II): scale revision. Spinal Cord 2001; 39(12): 654-656.
[ 18 ] American Thoracic Society. ATS Statement: Guidelines for the Six-Minute Walk Test. Am J Respir Crit Care Med 2002; 166(1): 111-117.
[ 19 ] Collen FM, Wade DT, Robb GF and Bradshaw CM. The Rivermead Mobility Index: A further development of the Rivermead Motor Assessment. Int Disabil Stud 1991; 13(2): 50-54.
[ 20 ] Berg K, Wood-Dauphinee S, Williams JI and Gayton D. Measuring balance in the elderly: preliminary development of an instrument. Physiotherapy Canada 1989; 41(6): 304-311.
[ 21 ] Martínez-Martín P, Carrasco de la Peña JL, Ramo C, Antigüedad AR and Bermejo F. Inter-observer reproducibility of qualitative scales in Parkinson disease (I). Arch Neuro-biol 1987; 50(5): 309-314.
[ 22 ] Fahn S, Elton RL and UPDRS program members. Unified Parkinson’s Disease Rating Scale. In: Fahn S, Marsden CD, Goldstein M, Calne DB, editors. Recent Developments in Parkinson’s Disease, vol. 2. Florham Park, NJ. Macmillan Healthcare Information; 1987.
[ 23 ] Sipe JC, Knobler RL, Braheny SL, Rice GPA, Panitch HS and Oldstone MBA. A neuro-logic rating scale (NRS) for use in multiple sclerosis. Neurology 1984; 34(10): 1368-1372.
[ 24 ] Kressig RW and Beauchet O. Guidelines for clinical applications of spatio-temporal gait analysis in older adults. Aging Clin Exp Res 2006; 18(2): 174-176.
[ 25 ] Lindemann U, Najafi B, Jijlstra W, et al. Distance to achieve steady state walking speed in frail elderly persons. Gait Posture 2008; 27(1): 91-96.
[ 26 ] Bland JM and Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986; 1(8476): 307-310.
[ 27 ] Shrout PE and Fleiss JL. Intraclass correlations: uses in assessing rater reliability. Psychol Bull 1979; 86(2): 420-428.
[ 28 ] McGraw KO and Wong SP. Forming Inferences About Some Intraclass Correlation Co-efficients. Psychol Methods 1996; 1(1): 30-46.
[ 29 ] Schuirmann DJ. A comparison of the two one-sided tests procedure and the power ap-proach for assessing equivalence of average bioavailability. J Pharmacokin Biopharm 1987; 15(6): 657–680.
[ 30 ] Walker E and Nowacki AS. Understanding Equivalence and Noninferiority Testing. J Gen Intern Med 2011; 26(2): 192–196.
[ 31 ] Hoehn MM and Yahr MD. Parkinsonism: onset, progression and mortality. Neurology 1967; 17(5): 427-442.
[ 32 ] Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). J Neurol 1983; 33(11): 1444–1452.
[ 33 ] Holden MK, Gill KM, Magliozzi MR, Nathan J and Piehl-Baker L. Clinical gait assess-ment in the neurologically impaired. Reliability and meaningfulness. Phys Ther 1984; 64(1): 35-40.
[ 34 ] Kirtley C. Clinical gait analysis. Theory and Practice. Edingburgh. Elsevier; 2006.
[ 35 ] Öberg K and Lamoreux LW. Gait assessment of total joint replacement patients by means of step parameters and hip – knee angle diagrams. In: Kenedi RM, Paul JP, Hughes J, editors. Disability. London. Macmillan Press; 1979.
[ 36 ] Brach JS, Perera S, Studenski S and Newman AB. The reliability and validity of measures of gait variability in community-dwelling older adults. Arch Phys Med Rehabil 2008; 89(12): 2293-2296.
[ 37 ] Peters DM, Fritz SL and Krotish DE. Assessing the reliability and validity of a shorter walk test compared with the 10-Meter Walk Test for measurements of gait speed in healthy, older adults. J Geriatr Phys Ther 2013; 36(1): 24-30.
[ 38 ] Cerny K. A clinical method of quantitative gait analysis. Suggestion from the field. Phys Ther 1983; 63(7): 1125-1126.
[ 39 ] Boenig DD. Evaluation of a clinical method of gait analysis. Phys Ther 1977; 57(7): 795-798.
[ 40 ] Schubert P. The application of nonlinear methods to characterize human variability from time series [Schubert P: Die Anwendung nichtlinearer Verfahren zur Charakterisierung der menschlichen Variabilitt aus Zeitreihen]. Dtsch Z Sportmed 2013; 64(5): 132–140.
[ 41 ] Kirchner M, Schubert P, Liebherr M and Haas CT. Detrended fluctuation analysis and adaptive fractal analysis of stride time data in Parkinson's disease: stitching together short gait trials. PLoS One 2014; 9(1):e85787.
[ 42 ] Sutherland DH. The evolution of clinical gait analysis part l: kinesiological EMG. Gait Posture 2001; 14(1): 61-70.
[ 43 ] Sutherland DH. The evolution of clinical gait analysis. Part II kinematics. Gait Posture 2002; 16(2): 159-179.
[ 44 ] Sutherland DH. The evolution of clinical gait analysis part III--kinetics and energy as-sessment. Gait Posture 2005; 21(4): 447-461.
[ 45 ] Samson MM, Crowe A, de Vreede PL, Dessens JA, Duursma SA and Verhaar HJ (2001) Differences in gait parameters at a preferred walking speed in healthy subjects due to age, height and body weight. Aging (Milano) 2001; 13(1): 16-21.
[ 46 ] Bugané F, Benedetti MG, Casadio G, et al. Estimation of spatial-temporal gait parameters in level walking based on a single accelerometer: validation on normal subjects by stand-ard gait analysis. Comput Methods Programs Biomed 2012; 108(1): 129-137.
[ 47 ] Givon U, Zeilig G and Achiron A. Gait analysis in multiple sclerosis: characterization of temporal-spatial parameters using GAITRite functional ambulation system. Gait Posture 2009; 29(1): 138-142.
[ 48 ] Al-Obaidi S, Wall JC, Al-Yaqoub A and Al-Ghanim M. Basic gait parameters: a compar-ison of reference data for normal subjects 20 to 29 years of age from Kuwait and Scandi-navia. J Rehabil Res 2003; 40(4): 361-366.
[ 49 ] Lee MM, Song CH, Lee KJ, Jung SW, Shin DC, Shin SH. Concurrent Validity and Test-retest Reliability of the OPTOGait Photoelectric Cell System for the Assessment of Spa-tio-temporal Parameters of the Gait of Young Adults. J Phys Ther Sci 2014; 26(1): 81–85.
[ 50 ] Hass CJ, Malczak P, Nocera J, et al. Quantitative Normative Gait Data in a Large Cohort of Ambulatory Persons with Parkinson’s Disease. Plos One 2012; 7(8): e42337.
[ 51 ] Morris ME, Iansek R, Matyas TA and Summers JJ. Stride length regulation in Parkinson's disease. Normalization strategies and underlying mechanisms. Brain 1996; 119(Pt 2): 551-568.
[ 52 ] Nelson AJ, Zwick D, Brody S, et al. The validity of the GaitRite and the Functional Am-bulation Performance scoring system in the analysis of Parkinson gait. NeuroRehabilita-tion 2002; 17(3): 255-262.