During the FGS walking condition, participants walked at a mean (SD) speed of 0.98 (0.40) m/s during session 1 and at 1.05 (0.40) m/s during session 2 (see Table 1). Participants walked significantly faster during the second visit (P < 0.01); however, STAs did not change significantly between sessions (all P > 0.48). High ICC (2,1) values were observed for each STA ratio (stance time asymmetry: 0.925; swing time asymmetry: 0.964; step length asymmetry: 0.944) (Figure 2). Minimal detectable change values for STA and gait speed during FGS walking are given in Table 1.
It is interesting to note that the MDC for stance time asymmetry and swing time asymmetry appeared to be different. The MDC for stance time asymmetry is smaller than the MDC for swing time asymmetry, which initially might suggest that it is easier to elicit a real change in stance time asymmetry. However, the evidence refutes this assumption as therapeutic approaches often fail to elicit changes in stance time asymmetry.8,17,18 Stance time measures incorporate two double support times, whereas swing time is the single support time of the contralateral limb. The observation of a larger MDC for swing time may be due to the inherent challenge associated with the balance requirement during single limb stance (ie, contralateral swing time).32 Each STA measure, however, provides important information and should therefore be considered in the assessment of gait for an individual following stroke.33 Step length asymmetry, for instance, has been related to the paretic limb's propulsive force generation.34 In addition, stance time and swing time asymmetries, while related to each other, are believed to represent different properties of gait.3
A limitation of this work is that we recruited a fairly small number of participants for this study. Eleven of the 26 participants (42%) may be considered “higher-functioning” with CGS greater than 0.8 m/s.35 This may limit the generalizability of our findings and suggests that these data should be applied primarily for limited-community and unrestricted community ambulators. Interestingly, our cohort had nearly the same average gait speed as that of subjects in a report by Patterson et al,3 albeit with a slightly greater percentage of individuals exhibiting STA in our cohort. Nevertheless, participants with overt STA were not intentionally recruited; instead, participants were enrolled as they presented to our laboratory. Using established thresholds for “normal” symmetry for step length (1.08), swing time (1.06), and stance time (1.05) asymmetry, we obtained slightly greater proportions of individuals with stance time asymmetry (73%) and swing time asymmetry (81%), but not step length asymmetry (50%) than what has been reported previously from a much larger sample.3 A major methodological difference between the current work and the larger sample reported by Patterson and colleagues3 is the use of an assistive device. Because gait speed appears to be more consistent in individuals requiring an assistive device compared with those who do not, including subjects who use assistive devices may have contributed to lower gait speed MDC values in our cohort.23 Recently, it was also reported that the use of an assistive device by individuals not accustomed to using an assistive device can increase gait symmetry.36 If cane use also minimizes STA in individuals who routinely use assistive devices, our data would underestimate the extent of STA. Nevertheless, our subjects (who were allowed to use assistive devices) exhibited greater asymmetry than the cohort described by Patterson et al3 (who were not allowed to use assistive devices), making it unlikely that the use of assistive devices minimized STA in our cohort. We caution, however, that our data may not generalize to cases in which individuals who routinely use an assistive device are tested without their aid. By allowing our participants to continue to use their typical assistive devices, however, we intended to capture the way that participants walk in the manner that most closely represents their real-world performance.
A second limitation of the study was that we did not accommodate participants to the laboratory before testing. There is the potential for participants to perceive walking across the GaitRite as a novel situation. While participants were accustomed to walking across carpeting, an initial baseline session would have alleviated concerns about “learning” to walk across the GaitRite mat. Because no intervention was involved, the use of multiple baseline sessions was deemed unnecessary to determine the repeatability of walking function. Nevertheless, we observed a change in gait speed, but not STA, from the first to the second session, indicating that subjects may have felt more comfortable during the second session. We caution, therefore, that if some subjects intentionally slowed their gait during the first session, this would increase the variability between sessions, producing an inflated MDC value for gait speed. If, however, a systematic learning effect occurred, then the intersession correlation (r value) will remain high, and the MDC value will be accurate. That our MDC values for gait speed are comparable with previously reported values22–24 suggests that if a learning effect occurred between sessions, it was minimal.
Finally, we did not standardize the time between test sessions. This was necessary to accommodate the travel and scheduling limitations of some of our participants. When calculating MDC values, it is important to obtain repeated measurements at a time when the measure of interest is stable.21 While changes may have occurred to the gait pattern between testing sessions, we believe that this is highly unlikely given the length of time since the stroke (all participants were greater than 6 months poststroke). In the chronic stage following stroke, STA values should be more stable without an intervention, making MDC values smaller; however, changes to STA may also be more difficult to elicit in the chronic stage. Despite earlier assertions that 6 months poststroke represents a functional plateau in the recovery process,37 we now know that intensive locomotor training can elicit dramatic changes in gait, even years after the stroke.38 Given that none of our participants were participating in intensive rehabilitation, we believe that the time between testing sessions did not influence our results.
1. Lloyd-Jones D, Adams RJ, Brown TM, et al. Heart disease and stroke statistics—2010 update: a report from the American Heart Association. Circulation. 2010;121:e46–e215.
2. Hill K, Ellis P, Bernhardt J, Maggs P, Hull S. Balance and mobility outcomes for stroke patients: a comprehensive audit. Aust J Physiother. 1997;43:173–180.
3. Patterson KK, Gage WH, Brooks D, Black SE, McIlroy WE. Evaluation of gait symmetry
after stroke: a comparison of current methods and recommendations for standardization. Gait
4. Patterson KK, Parafianowicz I, Danells CJ, et al. Gait
asymmetry in community-ambulating stroke survivors. Arch Phys Med Rehabil. 2008;89:304–310.
5. Mizelle C, Rodgers M, Forrester L. Bilateral foot center of pressure measures predict hemiparetic gait
6. Kim CM, Eng JJ. Symmetry
in vertical ground reaction force is accompanied by symmetry
in temporal but not distance variables of gait
in persons with stroke. Gait
7. Hsu AL, Tang PF, Jan MH. Analysis of impairments influencing gait
velocity and asymmetry of hemiplegic patients after mild to moderate stroke. Arch Phys Med Rehabil. 2003;84:1185–1193.
8. Reisman DS, Wityk R, Silver K, Bastian AJ. Locomotor adaptation on a split-belt treadmill can improve walking symmetry
post-stroke. Brain. 2007;130:1861–1872.
9. Norvell DC, Czerniecki JM, Reiber GE, Maynard C, Pecoraro JA, Weiss NS. The prevalence of knee pain and symptomatic knee osteoarthritis among veteran traumatic amputees and nonamputees. Arch Phys Med Rehabil. 2005;86:487–493.
10. Jorgensen L, Crabtree NJ, Reeve J, Jacobsen BK. Ambulatory level and asymmetrical weight bearing after stroke affects bone loss in the upper and lower part of the femoral neck differently: bone adaptation after decreased mechanical loading. Bone. 2000;27:701–707.
11. Visintin M, Barbeau H, Korner-Bitensky N, Mayo NE. A new approach to retrain gait
in stroke patients through body weight support and treadmill stimulation. Stroke. 1998;29:1122–1128.
12. Hornby TG, Campbell DD, Kahn JH, Demott T, Moore JL, Roth HR. Enhanced gait
-related improvements after therapist- versus robotic-assisted locomotor training in subjects with chronic stroke. A randomized controlled study. Stroke. 2008;39:1786–1792.
13. Ada L, Dean CM, Hall JM, Bampton J, Crompton S. A treadmill and overground walking program improves walking in persons residing in the community after stroke: a placebo-controlled, randomized trial. Arch Phys Med Rehabil. 2003;84:1486–1491.
14. Sullivan KJ, Brown DA, Klassen T, et al. Effects of task-specific locomotor and strength training in adults who were ambulatory after stroke: results of the STEPS randomized clinical trial. Phys Ther. 2007;87:1580–1602; discussion 1587–1603.
15. Sullivan KJ, Knowlton BJ, Dobkin BH. Step training with body weight support: effect of treadmill speed and practice paradigms on poststroke locomotor recovery. Arch Phys Med Rehabil. 2002;83:683–691.
16. Patterson SL, Rodgers MM, Macko RF, Forrester LW. Effect of treadmill exercise training on spatial and temporal gait
parameters in subjects with chronic stroke: a preliminary report. J Rehabil Res Dev. 2008;45:221–228.
17. Silver KH, Macko RF, Forrester LW, Goldberg AP, Smith GV. Effects of aerobic treadmill training on gait
velocity, cadence, and gait symmetry
in chronic hemiparetic stroke: a preliminary report. Neurorehabil Neural Repair. 2000;14:65–71.
18. Kahn JH, Hornby TG. Rapid and long-term adaptations in gait symmetry
following unilateral step training in people with hemiparesis. Phys Ther. 2009;89:474–483.
19. Reisman DS, McLean H, Bastian AJ. Split-belt treadmill training poststroke: a case study. Neurol Phys Ther. 2010;34:202–207.
20. Beckerman H, Roebroeck ME, Lankhorst GJ, Becher JG, Bezemer PD, Verbeek AL. Smallest real difference, a link between reproducibility and responsiveness. Qual Life Res. 2001;10:571–578.
21. Tilson JK, Sullivan KJ, Cen SY, et al. Meaningful gait
speed improvement during the first 60 days poststroke: minimal clinically important difference. Phys Ther. 2010;90:196–208.
22. Evans MD, Goldie PA, Hill KD. Systematic and random error in repeated measurements of temporal and distance parameters of gait
after stroke. Arch Phys Med Rehabil. 1997;78:725–729.
23. Fulk GD, Echternach JL. Test-retest reliability
and minimal detectable change of gait
speed in individuals undergoing rehabilitation after stroke. J Neurol Phys Ther. 2008;32:8–13.
24. Flansbjer UB, Holmback AM, Downham D, Patten C, Lexell J. Reliability
performance tests in men and women with hemiparesis after stroke. J Rehabil Med. 2005;37:75–82.
25. Ng SS, Hui-Chan CW. The Timed Up & Go Test: its reliability
and association with lower-limb impairments and locomotor capacities in people with chronic stroke. Arch Phys Med Rehabil. 2005;86:1641–1647.
26. Stokic DS, Horn TS, Ramshur JM, Chow JW. Agreement between temporospatial gait
parameters of an electronic walkway and a motion capture system in healthy and chronic stroke populations. Am J Phys Med Rehabil. 2009;88:437–444.
27. Zifchock RA, Davis I, Higginson J, Royer T. The symmetry
angle: a novel, robust method of quantifying asymmetry. Gait
28. Plotnik M, Giladi N, Hausdorff JM. A new measure for quantifying the bilateral coordination of human gait
: effects of aging and Parkinson's disease. Exp Brain Res. 2007;181:561–570.
29. Perera S, Mody SH, Woodman RC, Studenski SA. Meaningful change and responsiveness in common physical performance measures in older adults. J Am Geriatr Soc. 2006;54:743–749.
30. Roerdink M, Lamoth CJ, Kwakkel G, van Wieringen PC, Beek PJ. Gait
coordination after stroke: benefits of acoustically paced treadmill walking. Phys Ther. 2007;87:1009–1022.
31. Chen CH, Lin KH, Lu TW, et al. Immediate effect of lateral-wedged insole on stance and ambulation after stroke. Am J Phys Med Rehabil. 2010;89:48–55.
32. Brandstater ME, de Bruin H, Gowland C, Clark BM. Hemiplegic gait
: analysis of temporal variables. Arch Phys Med Rehabil. 1983;64:583–587.
33. Wall JC, Turnbull GI. Gait
asymmetries in residual hemiplegia. Arch Phys Med Rehabil. 1986;67:550–553.
34. Balasubramanian CK, Bowden MG, Neptune RR, Kautz SA. Relationship between step length asymmetry and walking performance in subjects with chronic hemiparesis. Arch Phys Med Rehabil. 2007;88:43–49.
35. Perry J, Garrett M, Gronley JK, Mulroy SJ. Classification of walking handicap in the stroke population. Stroke. 1995;26:982–989.
36. Beauchamp MK, Skrela M, Southmayd D, et al. Immediate effects of cane use on gait symmetry
in individuals with subacute stroke. Physiother Can. 2009;61:154–160.
37. Jorgensen HS, Nakayama H, Raaschou HO, Olsen TS. Recovery of walking function in stroke patients: the Copenhagen Stroke Study. Arch Phys Med Rehabil. 1995;76:27–32.
38. Moore JL, Roth EJ, Killian C, Hornby TG. Locomotor training improves daily stepping activity and gait
efficiency in individuals poststroke who have reached a “plateau” in recovery. Stroke. 2010;41:129–135.
39. Patterson KK. Clinician's commentary. Physiother Can. 2009;61:161–162.