Test-retest reliability and minimal detectable change of ankle kinematics and spatiotemporal parameters in MS population

Andreopoulou, Georgia; Mahad, Don J.; Mercer, Thomas H.; Linden, Marietta van der

doi:10.1016/j.gaitpost.2019.09.015

Cited by 16 publications

(17 citation statements)

References 41 publications

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“…Minimal detectable change (MDC) values for these spatiotemporal gait parameters have been measured for a variety of pathological populations, including chronic stroke patients (Geiger et al, 2019), adults with multiple sclerosis (Andreopoulou et al, 2019), post-incomplete spinal chord injury patients (Nair et al, 2012), chronic low back pain patients (Fernandes et al, 2015), and adults with cerebral palsy (Levin et al, 2019), and range from 0.11 m/s to 0.23 m/s for gait speed, 4 cm to 17 cm for step length, 8 cm to 17 cm for stride length, and 2 cm to 3 cm for stride width. Similarly, time-based gait parameter MDC values have been reported as 0.04 s to 0.05 s for step time, 0.09 s for cycle time, 0.03 s to 0.28 s for swing time, 0.06 s to 0.09 s for stance time, and 0.03 s to 0.69 s for double limb support time (Fernandes et al, 2015;Nair et al, 2012;Wittwer et al, 2013).…”

Section: Discussionmentioning

confidence: 99%

Assessment of spatiotemporal gait parameters using a deep learning algorithm-based markerless motion capture system

Kanko

Laende

Strutzenberger

et al. 2021

Journal of Biomechanics

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Spatiotemporal parameters can characterize the gait patterns of individuals, allowing assessment of their health status and detection of clinically meaningful changes in their gait. Video-based markerless motion capture is a user-friendly, inexpensive, and widely applicable technology that could reduce the barriers to measuring spatiotemporal gait parameters in clinical and more diverse settings. Two studies were performed to determine whether gait parameters measured using markerless motion capture demonstrate concurrent validity with those measured using marker-based motion capture and pressure sensitive gait mats. For the first study, thirty healthy adults performed treadmill gait at self-selected speeds while marker-based motion capture and synchronized video data were recorded simultaneously. For the second study, twenty-five healthy adults performed over-ground gait at self-selected speeds while footfalls were recorded using a gait mat and synchronized video data were recorded simultaneously. Kinematic heelstrike and toe-off gait events were used to identify the same gait cycles between systems. Nine spatiotemporal gait parameters were measured by each system and directly compared between systems.Measurements were compared using Bland-Altman methods, mean differences, Pearson correlation coefficients, and intraclass correlation coefficients. The results indicate that markerless measurements of spatiotemporal gait parameters have good to excellent agreement with marker-based motion capture and gait mat systems, except for stance time and double limb support time relative to both systems and stride width relative to the gait mat. These findings indicate that markerless motion capture can adequately measure spatiotemporal gait parameters during treadmill and overground gait.

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Section: Discussionmentioning

confidence: 99%

Assessment of spatiotemporal gait parameters using a deep learning algorithm-based markerless motion capture system

Kanko

Laende

Strutzenberger

et al. 2021

Journal of Biomechanics

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“…Regarding GSTP in pwMS, absolute and relative reliability of GSTP have been studied [ 71 ] in populations with lower (0–3.5) and higher (4–6) EDSS scores, and this study showed that higher walking disability in pwMS was associated with higher within-subject variability. These results are consistent with our review findings showing that clinical researchers less often chose this kind of assessment in pwMS with lower gait capacities.…”

Section: Discussionmentioning

confidence: 88%

“…Despite this fact, studies on the psychometric properties of these methods is needed. This point was already pointed out by Andreopoulou in 2019 [ 71 ], stating that although 3D gait analysis is considered a “gold” standard, psychometric properties of some of the measures provided by these technological systems have not been examined in pwMS. They studied the relative and absolute reliability of ankle kinematics and GSTP provided by VICON system in a sample of 49 pwMS.…”

Section: Discussionmentioning

confidence: 99%

Outcome measures used in trials on gait rehabilitation in multiple sclerosis: A systematic literature review

et al. 2021

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Background Multiple Sclerosis (MS) is associated with impaired gait and a growing number of clinical trials have investigated efficacy of various interventions. Choice of outcome measures is crucial in determining efficiency of interventions. However, it remains unclear whether there is consensus on which outcome measures to use in gait intervention studies in MS. Objective We aimed to identify the commonly selected outcome measures in randomized controlled trials (RCTs) on gait rehabilitation interventions in people with MS. Additional aims were to identify which of the domains of the International Classification of Functioning, Disability and Health (ICF) are the most studied and to characterize how outcome measures are combined and adapted to MS severity. Methods Pubmed, Cochrane Central, Embase and Scopus databases were searched for RCT studies on gait interventions in people living with MS according to PRISMA guidelines. Results In 46 RCTs, we identified 69 different outcome measures. The most used outcome measures were 6-minute walking test and the Timed Up and Go test, used in 37% of the analyzed studies. They were followed by gait spatiotemporal parameters (35%) most often used to inform on gait speed, cadence, and step length. Fatigue was measured in 39% of studies. Participation was assessed in 50% of studies, albeit with a wide variety of scales. Only 39% of studies included measures covering all ICF levels, and Participation measures were rarely combined with gait spatiotemporal parameters (only two studies). Conclusions Selection of outcome measures remains heterogenous in RCTs on gait rehabilitation interventions in MS. However, there is a growing consensus on the need for quantitative gait spatiotemporal parameter measures combined with clinical assessments of gait, balance, and mobility in RCTs on gait interventions in MS. Future RCTs should incorporate measures of fatigue and measures from Participation domain of ICF to provide comprehensive evaluation of trial efficacy across all levels of functioning.

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“…The minimal detectable change (MDC) was calculated using the relation: SEM × 1.96 × √ 2 [29]. The MDC indicates the minimum amount of change that is not likely to be due to an accidental error in measurement [30]. Pearson and Spearman correlation coefficients were used to examine the relationships between variables.…”

Section: Discussionmentioning

confidence: 99%

Self-Perception of the Knee Is Associated with Joint Motion during the Loading Response in Individuals with Knee Osteoarthritis: A Pilot Cross-Sectional Study

Toda

Maruyama

Fujita

et al. 2021

Sensors

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Small knee flexion motion is a characteristic of gait in individuals with knee osteoarthritis. This study examined the relationship between knee flexion excursion in loading response and knee self-perception in individuals with knee osteoarthritis. Twenty-one individuals with knee osteoarthritis participated in this study. Knee flexion excursions in loading response while walking at a comfortable and a fast-walking speed were measured using an inertial measurement unit-based motion capture system. The degree of knee perceptual impairment was evaluated using the Fremantle Knee Awareness Questionnaire (FreKAQ). The relationships between the FreKAQ score and gait variables and knee function were evaluated by calculating the correlation coefficient. The unique contributions of knee self-perception and muscle strength to knee flexion excursion in loading response were analyzed using hierarchical linear regression. Knee self-perception was significantly correlated with pain during walking, muscle strength and knee flexion excursion at fast speed. In the fast speed condition only, impaired knee self-perception was inversely proportional to knee flexion excursion and accounted for 21.8% of the variance in knee flexion excursion. This result suggests that impaired self-perception of the knee may help to explain the decrease in the knee flexion excursion in the loading response in individuals with knee osteoarthritis.

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Test-retest reliability and minimal detectable change of ankle kinematics and spatiotemporal parameters in MS population

Cited by 16 publications

References 41 publications

Assessment of spatiotemporal gait parameters using a deep learning algorithm-based markerless motion capture system

Assessment of spatiotemporal gait parameters using a deep learning algorithm-based markerless motion capture system

Outcome measures used in trials on gait rehabilitation in multiple sclerosis: A systematic literature review

Self-Perception of the Knee Is Associated with Joint Motion during the Loading Response in Individuals with Knee Osteoarthritis: A Pilot Cross-Sectional Study

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