Table 1.

Comparison of advanced techniques used for gait assessment in people with multiple sclerosis (MS).

Assessment technique	Outcome measures	Advantages	Disadvantages	Accuracy/reliability	Application in MS
Marker-based motion capture	Spatial and temporal variables Kinematics	Comprehensive analysis of widest range of gait variables Power consumption is not an issue Little interferences from external environmental factors	Expensive Must be used in a laboratory environment Markers and restricted space can hinder movement	Reliability between trials (ICC) = 0.95–1.00 (15)	GRFs, temporal-spatial measures and ankle, knee, and hip angles throughout gait differ between mild MS patients and controls (3) Spatiotemporal variables and ankle, knee, and hip angles differ in people with MS compared to controls and differences are more pronounced with increasing disease severity (4, 16) Change in balance measures contributes to deficits in walking performance over time in patients with established MS (17) Slower preferred walking speeds with longer dual support; dual support times were longer and swing times were shorter even at fixed walking speeds (18)
Markerless motion capture	Spatial and temporal variables Kinematics	Objectivity Quantification High sensitivity Comprehensivene Better suited to clinical environments than marker-based systems	Can be expensive Generally cannot be used outside the clinic or laboratory environment Measure a restricted number of steps	ToF: accuracy = 84–94% (19) Kinect: <1% mean error compared to marker-based (20) Reliability (ICC) = 0.91–0.98 (15)	ToF used to provide video-based rehabilitation to increase motivation and treatment efficacy for people with MS. Usability and benefits highly rated. System supports rehabilitation by allowing for real-time correction of abnormal movements (21) Kinect can detect differences in gait speed and gait “left/right deviation” in people with MS compared to controls, and results correlate with EDSS and T25FW scores (22)
Force platforms	GRF pattern Kinematics	Objectivity Quantification Good sensitivity	Restricted to laboratory environments	Reliability (ICC) = 0.22–0.97 (23) CoP error = 1.8 mm Orientation error = 1.0% (24) Treadmill mounted force platforms simple gait variables are high (ICC = 0.86–0.97); for gait variability the reliability is low to moderate (ICC = 0.22–0.44) (23)	Changes in walking and jogging gait variables in people with MS with minimal disability compared to controls, with greater change found during jogging compared to walking (25)
Wii Balance Board	GRF pattern	Objectivity Quantification Portability	Clinical, research and home	Excellent ICCs. Test–retest reliability (0.66–0.94), construct validity (0.77–0.89) (26, 27)	Wii Balance Board can discriminate fallers and non-fallers with MS (28) In a single case study Wii Balance Board Measure could predict relapse onset and assess intervention efficacy (29)
Instrumented walkways (GAITRite)	Spatial and temporal variables	Clinical feasibility Objectivity Quantification Good sensitivity	Restricted to clinic or laboratory environments Restricted to few steps at a time	MDC = 7–20% (in older adults) (30) Reliability (ICC) = 0.69–0.99 (31) 1.5% mean error compared to motion capture (32)	Quantitative spatiotemporal gait variables (33, 34) Sensitive in patients with minimal disability (35) Similar clinical validity as T25FW in people with MS (36) Detects changes in gait in very early-stage MS patients with minimal disability (35, 37) Gait variables correlate with EDSS system domains (38)
Pressure sensors	Spatial and temporal variables	Clinical feasibility Objectivity Quantification Good sensitivity Can be used outside the clinic and laboratory	Sensors can impede movement Battery powered	Reliability (ICC) = 0.90–0.99 (39) Correlation with motion capture > 0.95 Mean error < 5.4% compared to motion capture (40)	Differences in gait variability and sites of foot pressure throughout gait cycle between MS patients and controls (41)
Inertial sensors	Spatial and temporal variables Kinematics	Clinical feasibility Objectivity Quantification Good sensitivity Face validity	Sensors can impede movement Battery powered Susceptible to environmental interference May need technical operators	Mean error < 5% compared to motion capture (42) Detection accuracy > 80% (43) Reliability (ICC) = 0.90–0.99 (44)	Can detect changes balance, gait dysfunction, and arm movement during walking otherwise undetected by timed walking tests in MS patients with minimal disability (45, 46) Capable of separating mild MS (average EDSS = 2.2), moderate MS (average EDSS = 4.3) and controls based on gait velocity, trunk motion, sway range, and sway area (14)

MDC, minimal detectable difference; ICC, intraclass correlation coefficient; CoP, center of pressure; ToF, time of flight; GRF, ground reaction force.