Clinical Utility of Proposed Gait Stability Measures: Selection, Application and Evaluation of the Extrapolated Centre of Mass

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Abstract

Gait stability is the ability to maintain a state of equilibrium during locomotion. In humans, this includes the need to maintain a stable walking pattern while regularly positioning the body in a state of imbalance. Thus, it is not surprising that gait is accompanied by an increased risk of falling, particularly among the elderly and individuals with physical impairments, such as stroke, spinal cord injury, amputation, or hemophilic arthropathy. In addition, the precarious nature of gait makes it difficult to establish an exact definition of stability, leading to the development of a variety of different measures, each based on its own set of unique principles and assumptions. As a result, these measures have varying characteristics and experimental requirements, often limiting their feasibility for clinical implementation. In light of these considerations, the objectives of this thesis research were to: (1) conduct a literature review to identify the characteristics of proposed gait stability measures and select those that are clinically feasible based on pre-defined criteria; (2) demonstrate the practical feasibility of obtaining the selected measures and assess their robustness for a non-disabled sample; (3) evaluate the between-session reliability of the measures, as a key requirement for clinical implementation; and (4) demonstrate the clinical utility of the measures using three clinical case studies. Proposed gait stability measures were identified, reviewed, and scrutinized based on their expected burden on the patient, in terms of the required walking distance; the time required for assessment, including setup and trial time; the versatility of being applied to multiple walking conditions; and the mechanistic link between gait and the theoretical basis for stability. In total, three gait stability measures were identified as being clinically-feasible: the extrapolated centre of mass (XCoM), the gait sensitivity norm, and the stabilizing and destabilizing forces. For the purpose of this study, only the XCoM was used for further investigation as per the preceding objectives. To quantify stability, the XCoM, a quantity that accounts for both the position and velocity of the center of mass, must remain within the limits of the base of support. The degree of stability at a given instant in time is then given by the margin of stability (MoS): the minimum distance between the XCoM and the base of support. Fifteen non-disabled participants were asked to walk in the Computer-Assisted Rehabilitation Environment at self-selected speed on a level, treadmill-driven surface. All participants returned for a repeat session several weeks following initial testing. Three case study participants with hemophilic arthropathy, unilateral transtibial amputation, and mild traumatic brain injury were also included, each completing one session. Careful attention was given to choose data collection and analysis techniques that would overcome common barriers to clinical implementation and support its feasibility in that respect. Acquired kinematic and kinetic data were used to compute the XCoM and corresponding MoS. To quantify stability in the mediolateral and anteroposterior directions, mean MoS values were taken at heel strike (MoS-HS) and mid-stance (MoS-MS). In addition, the minimum MoS value between heel strike and contralateral toe off (MoS-HScTO) was used to quantify stability in the ML direction. The protocol was designed to minimize the burden on the patient, as well as the time required for setup and overall trial length. Gait stability results suggest that MoS-HS is best suited to quantifying stability in both the mediolateral and anteroposterior directions. Not only does MoS-HS demonstrate reasonable within- and across-participant variability, it also showed good repeatability between sessions. Although the identified repeatability is not sufficient to support clinical implementation at this point, it is sufficient for continued use of the MoS in research. Furthermore, MoS-HS provided promising results towards highlighting differences between right and left body sides in the case study participants. Despite recommendation of the MoS-HS, further investigation is warranted before dismissing any of the MoS measures in either the mediolateral or anteroposterior direction. This work represents a significant step towards demonstrating that the MoS is a robust measure that can be reliably used in fundamental research to quantify human gait stability. Further work is necessary to achieve the repeatability necessary for clinical purposes and investigate the ability of the MoS measures to detect difference in a larger sample of impaired participants.

Cited Works (18)

Year	Entry
2013	Robinovitch SN, Feldman F, Yang Y, Schonnop R, Leung PM, Sarraf T, Sims-Gould J, Loughin M. Video capture of the circumstances of falls in elderly people residing in long-term care: an observational study. Lancet. January 5, 2013;381(9860):47-54.
1979	Shrout PE, Fleiss JL. Intraclass correlations: uses in assessing rater reliability. Psychol Bull. 1979;86(2):420-428.
1995	Cappozzo A, Catani F, Della Croce U, Leardini A. Position and orientation in space of bones during movement: anatomical frame definition and determination. Clin Biomech (Bristol, Avon). June 1995;10(4):171-178.
1986	Horak FB, Nashner LM. Central programming of postural movements: adaptation to altered support-surface configurations. J Neurophysiol. June 1986;55(6):1369-1381.
2005	Hof AL, Gazendam MGJ, Sinke WE. The condition for dynamic stability. J Biomech. January 2005;38(1):1-8.
1999	Center JR, Nguyen TV, Schneider D, Sambrook PN, Eisman JA. Mortality after all major types of osteoporotic fracture in men and women: an observational study. Lancet. March 13, 1999;353(9156):878-882.
1990	Winter DA, Patla AE, Frank JS, Walt SE. Biomechanical walking pattern changes in the fit and healthy elderly. Phys Therap. June 1990;70(6):340-347.
2005	Cappozzo A, Della Croce U, Leardini A, Chiari L. Human movement analysis using stereophotogrammetry, I: theoretical background. Gait Post. February 2005;21(2):186-196.
2016	Koo TK, Li MY. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med. June 2016;15(2):155-163.
2005	Leardini A, Chiari L, Della Croce U, Cappozzo A. Human movement analysis using stereophotogrammetry, III: soft tissue artifact assessment and compensation. Gait Post. February 2005;21(2):212-225.
2005	Chiari L, Della Croce U, Leardini A, Cappozzo A. Human movement analysis using stereophotogrammetry, II: instrumental errors. Gait Post. February 2005;21(2):197-211.
1997	Maki BE. Gait changes in older adults: predictors of falls or indicators of fear? J Am Geriatr Soc. March 1997;45(3):313-320.
2005	Della Croce U, Leardini A, Chiari L, Cappozzo A. Human movement analysis using stereophotogrammetry, IV: assessment of anatomical landmark misplacement and its effects on joint kinematics. Gait Post. February 2005;21(2):226-237.
1996	Prieto TE, Myklebust JB, Hoffmann RG, Lovett EG, Myklebust BM. Measures of postural steadiness: differences between healthy young and elderly adults. IEEE Trans Biomed Eng. September 1996;43(9):956-966.
2002	Donelan JM, Kram R, Kuo AD. Simultaneous positive and negative external mechanical work in human walking. J Biomech. January 2002;35(1):117-124.
2009	Winter DA. Biomechanics and Motor Control of Human Movement. 4th ed. Hoboken, NJ: Inc, John Wiley & Sons; 2009.
2008	Zeni JA Jr, Richards JG, Higginson JS. Two simple methods for determining gait events during treadmill and overground walking using kinematic data. Gait Post. May 2008;27(4):710-714.
2001	Dingwell JB, Cusumano JP, Cavanagh PR, Sternad D. Local dynamic stability versus kinematic variability of continuous overground and treadmill walking. J Biomech Eng. February 2001;123(1):27-32.