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Reliability and minimal detectible change values for gait kinematics and kinetics in healthy adults
Gait & Posture 35 (2012) 301–307
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Gait & Posture journal homepage: www.elsevier.com/locate/gaitpost
Reliability and minimal detectible change values for gait kinematics and kinetics in healthy adults§ Jason M. Wilken *, Kelly M. Rodriguez, Melissa Brawner, Benjamin J. Darter Center for the Intrepid, Department of Orthopedics and Rehabilitation, Brooke Army Medical Center, Ft. Sam Houston, TX 78234, USA
A R T I C L E I N F O
A B S T R A C T
Article history: Received 13 May 2011 Received in revised form 10 August 2011 Accepted 26 September 2011
Computerized assessment of gait is commonly used in both research and clinical settings to quantify gait mechanics and detect change in performance. Minimal Detectable Change values have only recently been reported, are only available for patient populations, and in many cases exceed 108. Twenty nine healthy individuals underwent two biomechanical gait assessments separated by 5.6 (SD 2.2) days, with two raters for each session. All subjects walked at a self selected pace and three controlled velocities. ICC, SEM and MDC for kinematic and kinetic measures were calculated for interrater-intrasession, intraraterintersession and interrater-intersession. ICC values were in the good to excellent range (r > 0.75) for all kinematic and kinetic variables and all comparisons. MDC values were lower than previously published data for all similar comparisons. The results of the current study suggest that reliability is good to excellent across a range of controlled walking velocities and the introduction of a second rater does not appreciably impact ICC or MDC values. In young healthy adults changes in gait kinematics of greater than approximately 58 can be identified when comparing between sessions. Published by Elsevier B.V.
Keywords: Reliability Minimal Detectable Change Intraclass Correlation Coefficient Gait analysis
1. Introduction Computerized assessment of gait is commonly used in both research and clinical settings to identify deviations, plan treatment and determine the effectiveness of interventions for a wide range of conditions such as cerebral palsy, lower extremity amputation and stroke [1–3]. The ability to effectively meet these objectives is dependent on the collection of data that allows identification of real and meaningful change in performance [4]. The ability to detect true change is limited by errors associated with collection methodology, and the effects of natural variability in performance over time. The COSMIN manual which can be used to guide the assessment of measurement properties for health measurement instruments, identifies the two distinct measurement properties of reliability and measurement error [5]. Reliability is associated with the true differences that can exist between patients or testing sessions, while measurement error accounts for the effect of systematic and random sources of error [5]. Errors can be due to the application of
§ The views expressed herein are those of the authors and do not reflect the official policy or position of Brooke Army Medical Center, the U.S. Army Medical Department, the U.S. Army Office of the Surgeon General, the Department of the Army, Department of Defense or the U.S. Government. * Corresponding author. Tel.: +1 210 916 1478; fax: +1 210 916 9016. E-mail addresses: [email protected], [email protected] (J.M. Wilken).
0966-6362/$ – see front matter . Published by Elsevier B.V. doi:10.1016/j.gaitpost.2011.09.105
markers, identification of anatomical landmarks, natural variation in walking and the ability of the system to accurately track markers [4]. In spite of large variations in collection methodology and study design [4], previous studies generally report acceptable reliability using Intraclass Correlation Coefficient (ICC) and Coefficient of Multiple Correlation (CMC) values [2,6–8]. There are however, limitations in the ability to generalize the findings associated with each of these studies to include use of a single rater, the presence of gait pathology, limited number of walking velocities tested, and use of reliability metrics that have limited use when interpreting change in clinical data. Within session or within rater comparisons over time are commonly used to determine the reliability of gait analysis data. Although useful for determining the specific effect of rater or time on the measurements, these comparisons do not effectively replicate the reality of clinical or research assessments which can require multiple raters over multiple sessions. For example, Beiser et al. assessed reliability using within and between rater comparisons but only within a single day of testing. Mackey et al. reported high CMC values and no difference in reliability for within and between session comparisons, but only used a single rater [9]. To date, no study has assessed reliability with multiple raters over multiple sessions. As a result, the combined effects of rater and session remain poorly understood. Walking velocity is a factor that may influence the reliability of gait data and has not been addressed through scientific study. All walking reliability studies reviewed by McGinley et al. assessed
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participants at a self selected walking velocity. Although self selected walking velocities are convenient for data collection purposes, walking velocity is known to influence kinetic variables [10,11]. Recent advances from large motion capture companies now allow investigators to readily control participant walking velocity through the use of external cueing. It is unclear if removing the potential variation induced by natural fluctuation in self-selected walking velocity would improve reliability. Statistical assessment of gait reliability has commonly been performed using the ICC and CMC. Evaluation using ICC and CMC provides information regarding the relative reliability of measurements, but can be of limited help when determining if an observed change is due to actual change in performance. Minimal Detectable Change (MDC), in contrast, provides meaningful and practical assessment of measurement error by providing a single value for each variable in the units of measure. More specifically, the MDC is described as the amount of change which is sufficiently greater than measurement error for the variable of interest [12]. It allows the investigator or clinician to determine if an observed change between assessments is a true difference due to the effect of a treatment intervention, or simply the result of measurement error. Currently, only two studies provide MDC values for computerized gait analysis data [1,13]. Both of these studies were conducted using patient populations and report MDC values as high as 128 for commonly used kinematic variables of the lower extremity [1,13]. Due to natural fluctuations in symptomatoloty or disease progression it is expected that patient populations will demonstrate greater variation in performance over time, and as a result have greater MDC values. If MDC values of similar magnitude are observed when assessing non-pathologic populations it would suggest limited usefulness for detecting all but the largest kinematic and kinetic changes. To date, MDC values from a healthy population have not been published. The availability of MDC values for healthy and pathologic populations will greatly aid scientists and clinicians as they interpret data. The purpose of the current study is to determine the intrarater and interrater reliability and MDC for commonly used gait variables within a single session and between sessions. A second objective is to examine the effect of walking velocity on reliability and MDC variables. 2. Methods 2.1. Subjects Twenty nine young healthy individuals (14 male, 15 female) with no current pain or history of major lower extremity injury participated in this study. Subjects were on average 24.7 (SD 5.7) years old with a mean body mass and height of 69.0 (SD 12.0) kg and 1.7 (SD 0.1) m, respectively. The average leg length was 88.0 (SD 5.8) cm. All subjects provided written informed consent prior to participation in this institutionally approved study. 2.2. Procedure All subjects underwent two biomechanical gait assessments separated by 5.6 (SD 2.2) days. Testing involved walking on level ground at a self-selected pace, a predefined velocity based on leg length (also referred to as a Froude (FR) velocity) [14] and velocities 20% faster and slower. The controlled velocities allow for dynamically equivalent comparisons across subjects based on each subject’s leg p length (l): v ¼ 0:40 ðg lÞ [15,16]. For the purpose of this paper the respective velocities are referred to as FR2, FR3 and FR4 in increasing order. Leg length was defined as the length in centimeters from the greater trochanter to the floor while the subject was standing. An automated auditory cue (Biofeed Trak, Motion Analysis Corp., Santa Rosa, CA), based on trunk marker velocity, guided subjects to walk at each pre-determined velocity. Full body kinematics were assessed using a 6 degrees of freedom marker set [17–19] and a 26 camera optoelectronic motion capture system (Motion Analysis Corp., Santa Rosa, CA) operating at 120 Hz [19] (see Supplemental material) (Fig. 1). Ground reaction force data were obtained using eight AMTI force plates (AMTI, Inc., Watertown, MA) embedded in the walkway operating at a sampling rate of 1200 Hz. Segment local coordinate system orientation was determined in accordance with ISB standards [20,21]. A digitizing process was used to identify
Fig. 1. Screen capture demonstrating representative marker placement.
joint center locations and define the local coordinate system for the shank and thigh segments [22]. Each segment was tracked as an independent rigid body to avoid the potential propagation of errors [23]. To determine the effect of digitizing on lower extremity kinematics and kinetics two raters identified the medial and lateral malleoli and condyles at the ankle and knee respectively. Each rater had over 10 years experience identifying anatomical landmarks. Five gait cycles for each condition were analyzed using Visual 3D (C-Motion Inc., Rockville, MD). Data were normalized to 100% step cycle and peak values for each kinematic and kinetic variable of interest were extracted using MATLAB (The Mathworks, Natick, MA) software and exported for statistical analysis. 2.3. Statistical analysis To assess reliability, the following three comparisons were performed: interrater-intrasession, intrarater-intersession and interrater-intersession. SPSS v. 16 (SPSS Inc., Chicago, IL) was used to calculate mean, standard deviation and ICC (2, k). Standard error of the measurement (SEM) and MDC were calculated for each variable using Microsoft Excel 2007(Microsoft Corp., Redmond, WA). SEM was calculated using the equation SD SQRT (1-ICC), where SD is the pooled variance. MDC was calculated using the equation SEM 1.96 SQRT2 [24]. A two-way (Velocity Session) repeated measures Analysis of Variance (ANOVA) was used to detect between session differences in walking velocity. ICC values 0.75 or higher were considered to be excellent, 0.40–0.74 to be fair to good, and 0.40 or lower to be poor [25]. Published criteria for interpreting MDC values are not currently available and actual MDC values provided in the tables should be referenced when interpreting results. However, to highlight kinematic measures with greater measurement error, MDC values greater than the often used clinical threshold of five degrees [26,27] were identified.
3. Results ICC, SEM, and MDC values for the rater and session assessments of kinematic reliability are presented in Table 1. All three ratersession comparisons were performed for all velocities. Similar results were found across all velocities with mean absolute differences of less than 0.05 for ICC and 0.78 for MDC values between velocity conditions. Therefore, only data from a single controlled velocity (FR3) are presented. Data for intrasession comparisons are not provided for pelvic and trunk kinematics as these segments are based solely on marker data and not affected by the digitizing process. Overall, excellent ICC values (ICC range, 0.76–1.00) were obtained for 100% of interrater-intrasession, 82%
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Table 1 ICC, SEM and MDC values for peak kinematic variables. Table includes (1) interrater-intrasession, (2) intrarater-intersession and (3) interrater-intersession comparisons. * Denotes variables not affected by digitizing process. ICC values less than 0.75 and MDC values greater than 58 are presented in bold. FR3
ICC(95%CI)
Peaks description
1
Ankle angle (8) Initial plantarflexion Dorsiflexion Plantarflexion Sagittal range of motion Knee angle (8) Flexion at initial contact Stance flexion Mid/terminal stance extension Peak flexion during swing Sagittal range of motion Hip angle (8) Flexion during stance Extension during stance Flexion during swing Sagittal range of motion Adduction during stance Abduction during swing Frontal range of motion Pelvic angle (8) Anterior tilt Posterior tilt Sagittal range of motion Contralateral drop Contralateral elevation Frontal range of motion Hip forward Hip back Transverse range of motion Trunk-lab angle (8) Anterior trunk lean Posterior trunk lean Sagittal range of motion Ipsilateral lean Frontal range of motion Ipsilateral shoulder forward Transverse range of motion Average
SEM 2
3
MDC
1
2
3
1
2
3
0.91 0.89 0.98 0.98
(0.79–0.95) (0.75–0.94) (0.95–0.99) (0.95–0.99)
0.81 0.82 0.94 0.91
(0.59–0.91) (0.60–0.91) (0.86–0.97) (0.79–0.95)
0.88 0.80 0.94 0.90
(0.73–0.94) (0.56–0.91) (0.85–0.97) (0.77–0.95)
0.85 1.04 0.83 0.68
1.05 1.32 1.24 1.24
0.89 1.22 1.43 1.37
2.35 2.88 2.30 1.87
2.91 3.66 3.44 3.45
2.46 3.37 3.97 3.79
0.78 0.78 0.81 0.84 0.98
(0.56–0.89) (0.56–0.89) (0.62–0.90) (0.68–0.92) (0.95–0.99)
0.85 0.74 0.70 0.57 0.77
(0.67–0.93) (0.41–0.87) (0.34–0.86) (0.05–0.80) (0.49–0.89)
0.78 0.80 0.75 0.62 0.81
(0.50–0.89) (0.56–0.91) (0.45–0.88) (0.17–0.82) (0.58–0.91)
1.73 1.66 1.70 1.71 0.57
1.48 1.74 1.90 2.65 1.83
1.83 1.50 1.84 2.31 1.76
4.81 4.61 4.70 4.75 1.58
4.12 4.83 5.28 7.33 5.08
5.08 4.16 5.09 6.39 4.89
0.99 0.99 0.99 1.00 0.99 0.99 1.00
(0.97–0.99) (0.98–0.99) (0.97–0.99) (1.00–1.00) (0.98–0.99) (0.98–0.99) (0.99–1.00)
0.89 0.88 0.85 0.93 0.82 0.66 0.89
(0.76–0.95) (0.72–0.94) (0.66–0.93) (0.85–0.97) (0.60–0.91) (0.24–0.84) (0.75–0.94)
0.91 0.89 0.84 0.90 0.84 0.76 0.91
(0.80–0.95) (0.74–0.94) (0.64–0.92) (0.76–0.95) (0.64–0.92) (0.46–0.88) (0.81–0.96)
0.49 0.49 0.50 0.00 0.31 0.32 0.00
1.73 1.86 2.09 0.99 1.59 1.69 0.94
1.59 1.88 2.06 1.14 1.49 1.51 0.77
1.36 1.35 1.40 0.00 0.87 0.88 0.00
4.80 5.16 5.80 2.74 4.41 4.69 2.61
4.41 5.22 5.72 3.17 4.14 4.17 2.14
* * * * * * * * *
0.82 0.79 0.93 0.45 0.45 0.85 0.90 0.80 0.96
(0.60–0.91) (0.54–0.90) (0.84–0.96) (S0.20–0.75) (S0.21–0.74) (0.67–0.93) (0.77–0.95) (0.55–0.90) (0.91–0.98)
0.89 0.87 0.94 0.47 0.54 0.86 0.89 0.86 0.96
(0.75–0.94) (0.71–0.94) (0.86–0.97) (S0.16–0.75) (0.00–0.79) (0.70–0.93) (0.74–0.94) (0.68–0.93) (0.91–0.98)
* * * * * * * * *
1.97 1.96 0.23 1.35 1.57 0.91 1.08 1.30 0.80
1.60 1.62 0.21 1.31 1.45 0.85 1.05 1.02 0.70
* * * * * * * * *
5.45 5.43 0.64 3.75 4.35 2.52 2.99 3.61 2.21
4.43 4.48 0.59 3.63 4.02 2.37 2.92 2.82 1.94
* * * * * * *
0.95 0.96 0.84 0.84 0.95 0.81 0.90
(0.89–0.97) (0.90–0.98) (0.64–0.92) (0.64–0.92) (0.88–0.97) (0.58–0.91) (0.77–0.95)
0.96 0.96 0.86 0.85 0.95 0.77 0.91
(0.91–0.98) (0.91–0.98) (0.69–0.93) (0.67–0.93) (0.89–0.97) (0.50–0.89) (0.79–0.95)
* * * * * * *
0.96 1.01 0.32 0.83 0.41 1.11 0.58
0.92 0.95 0.29 0.80 0.41 1.12 0.56
* * * * * * *
2.67 2.79 0.88 2.29 1.13 3.08 1.62
2.56 2.64 0.80 2.22 1.14 3.10 1.54
0.93
0.82
0.81
1.30
1.23
2.23
3.62
3.42
of intrarater-intersession and 91% of interrater-intersession data. MDC values less than 58 were found in 100% of interraterintrasession, 77% of intrarater-intersession, and 86% of interraterintersession. The lowest ICC values were observed in peak knee flexion during swing, and contralateral pelvic elevation and drop (ICC range, 0.45–0.75) for intrarater-intersession and interraterintersession conditions. Table 2 displays the effect of rater and session on lower extremity kinetics at FR3. All ICC values for interrater-intrasession reliability were excellent. For intrarater-intersession and interrater-intersession, 70% and 74% of the ICC values were in the excellent range, respectively. Hip moment in terminal stance and peak hip power absorption and generation during stance have the lowest ICC values in all three comparison groups (ICC range, 0.48– 0.62). The effect of velocity on kinematic variables for interraterintersession comparisons are shown in Table 3. The mean velocity (m/s) for each condition for all subjects for the first session is as follows: 1.31 (SD 0.17) for SSWV, 0.97 (SD 0.05) for FR2, 1.18 (SD 0.06) for FR3, and 1.39 (SD 0.06) for FR4. There was no significant difference in walking velocity between the two sessions (p = 0.55). Good to excellent ICC values were observed for all kinematic variables. When averaging across dependent variables the mean ICC value for all controlled velocities were identical. Self-selected walking velocity and FR3 had the highest percentage of ICC values in the excellent range at 89%, with FR2 and FR4 at 82% and 80%, respectively. For MDC, FR4 and SSWV had the lowest percentage of
0.84
kinematic values less than 58, at 84%. FR3 had 86% with FR2 having the highest percentage at 91%. Table 4 shows the effect of walking velocity on kinetic variables for interrater-intersession comparisons. The ankle dorsiflexion moment demonstrates the greatest difference between velocities, ranging from an ICC of 0.50 for FR3 to 0.80 for SSWV. For kinetic data, 96% of ICC values were in the excellent range for the SSWV condition, while FR3 had the lowest percentage at 74%. MDC values for kinematic and kinetic measures did not demonstrate consistent trends indicating MDC values were greater or smaller for a particular velocity. The greatest relative difference in MDC values are observed in terminal stance ankle power generation, with SSWV two times greater than FR2.
4. Discussion Patients and research subjects are commonly tested on multiple occasions over a period of days or weeks to track changes in gait associated with a treatment. The use of multiple raters and/or testing over time can introduce measurement error that can affect data quality and influence data interpretation. The ability to distinguish between measurement error and true change over time is essential to the successful application of gait analysis for clinical and research purposes. The results of the current study suggest that, independent of pathology, reliability is excellent for most measures across a wide range of walking velocities, and the
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Table 2 ICC, SEM and MDC values for peak kinetic variables. Table includes (1) interrater-intrasession, (2) intrarater-intersession, and (3) interrater-intersession comparisons. ICC values less than 0.75 are presented in bold. Peaks description
ICC(95%CI)
SEM
MDC
1
2
3
1
2
3
1
2
3
0.79 (0.54–0.90) 0.92 (0.81–0.96)
0.67 (0.28–0.85) 0.84 (0.65–0.92)
0.50 (0.10–0.77) 0.82 (0.60–0.91)
0.02 0.04
0.03 0.05
0.04 0.05
0.07 0.10
0.07 0.13
0.11 0.15
Ankle moment (Nm/kg) Dorsiflexion Plantarflexion Knee moment (Nm/kg) Initial contact flexion Stance extension Mid/terminal stance flexion Loading response varus First peak valgus Second peak valgus Stance internal rotation Stance external rotation Hip moment (Nm/kg) Initial contact extension Terminal stance flexion Swing extension Loading response abduction Terminal stance abduction Loading response external rotation Terminal stance internal rotation Ankle sagittal plane powers (W/kg) Initial contact absorption Stance absorption Terminal stance generation Knee sagittal plane powers (W/kg) Initial contact generation Loading response absorption Terminal stance generation Terminal stance absorption Hip sagittal plane powers (W/kg) Stance generation Stance absorption Swing generation
0.59 0.89 0.90 0.92 0.76 0.90 0.96 0.95
(0.09–0.81) (0.75–0.94) (0.78–0.95) (0.81–0.96) (0.47–0.89) (0.78–0.95) (0.91–0.98) (0.88–0.97)
0.88 0.66 0.76 0.82 0.88 0.78 0.79 0.88
(0.74–0.94) (0.26–0.84) (0.46–0.89) (0.61–0.92) (0.73–0.94) (0.51–0.90) (0.53–0.90) (0.72–0.94)
0.90 0.87 0.85 0.91 0.86 0.90 0.87 0.87
(0.78–0.95) (0.71–0.94) (0.66–0.93) (0.80–0.96) (0.70–0.93) (0.78–0.95) (0.71–0.94) (0.72–0.94)
0.10 0.05 0.05 0.02 0.06 0.04 0.01 0.01
0.04 0.08 0.07 0.02 0.03 0.05 0.01 0.01
0.04 0.05 0.06 0.02 0.04 0.04 0.01 0.01
0.27 0.13 0.13 0.04 0.17 0.10 0.02 0.02
0.10 0.21 0.20 0.06 0.10 0.15 0.04 0.03
0.10 0.14 0.15 0.05 0.10 0.11 0.03 0.03
1.00 1.00 0.95 1.00 1.00 1.00 1.00
(0.99–1.00) (0.99–1.00) (0.89–0.97) (1.00–1.00) (0.99–1.00) (0.99–1.00) (0.99–1.00)
0.89 0.48 0.77 0.88 0.85 0.65 0.73
(0.74–0.94) (S0.13–0.76) (0.48–0.89) (0.73–0.94) (0.67–0.93) (0.23–0.84) (0.40–0.87)
0.91 0.52 0.80 0.88 0.83 0.75 0.73
(0.79–0.95) (0.05–0.78) (0.55–0.90) (0.73–0.94) (0.61–0.92) (0.45–0.88) (0.40–0.87)
0.01 0.00 0.02 0.00 0.00 0.00 0.00
0.06 0.11 0.03 0.05 0.05 0.04 0.02
0.05 0.11 0.03 0.05 0.05 0.03 0.02
0.01 0.00 0.05 0.00 0.00 0.00 0.00
0.15 0.31 0.08 0.15 0.14 0.10 0.05
0.14 0.30 0.09 0.15 0.14 0.08 0.05
1.00 (0.99–1.00) 1.00 (0.99–1.00) 1.00 (0.99–0.99)
Average
0.93
0.83 (0.62–0.92) 0.98 (0.95–0.99) 0.95 (0.90–0.97)
0.77 (0.48–0.89) 0.84 (0.64–0.92) 0.75 (0.45–0.88)
0.56 (0.03–0.80) 0.83 (0.61–0.92) 0.61 (0.14–0.82)
0.04 0.04 0.07
0.05 0.11 0.17
0.07 0.11 0.20
0.11 0.11 0.20
0.13 0.30 0.48
0.20 0.30 0.56
0.99 0.93 0.86 0.97
0.81 0.75 0.68 0.90
0.86 0.87 0.79 0.89
(0.69–0.93) (0.71–0.94) (0.54–0.90) (0.75–0.94)
0.03 0.06 0.09 0.04
0.15 0.10 0.15 0.08
0.13 0.08 0.13 0.08
0.09 0.16 0.25 0.11
0.41 0.28 0.42 0.22
0.36 0.23 0.35 0.23
0.62 (0.16–0.82) 0.69 (0.30–0.85) 0.92 (0.82–0.96)
0.58 (0.07–0.80) 0.67 (0.27–0.84) 0.91 (0.79–0.95)
0.01 0.00 0.01
0.13 0.09 0.05
0.12 0.09 0.05
0.02 0.00 0.03
0.37 0.25 0.14
0.34 0.25 0.15
0.77
0.79
0.03
0.07
0.06
0.08
0.19
0.18
(0.97–0.99) (0.85–0.96) (0.69–0.93) (0.93–0.98)
(0.57–0.91) (0.44–0.88) (0.29–0.85) (0.78–0.95)
introduction of a second rater does not appreciably impact ICC or MDC values. In this study the addition of a second rater did not appreciably affect the reliability of kinematic or kinetic data. The results are in contrast to those of Maynard et al. which demonstrate large but inconsistent differences in ICC values between intrarater and interrater comparisons [8]. ICC values for interrater-intrasession comparisons were the highest of all comparisons. This is to be expected as anatomical landmark identification is the only factor influencing calculated values. The results do, however, demonstrate the importance of landmark identification. Although ICC values are high for all variables, interrater MDC values vary widely between variables. Knee kinematic variables show the greatest effect of digitizing with MDC values greater than 4.68 for peak variables. Range of motion variables yielded substantially lower MDC values for all joints and segments suggesting offsets in local coordinate system orientation contributed to interrater differences. Interrater differences in knee landmark identification also likely contributed to lower ICC values and higher MDC values which were observed for knee joint moments as compared to moments at the ankle and hip. Reliability was generally excellent for both intrarater and interrater comparisons between sessions. Intersession results from the current study are similar to those of previous studies which indicate good to excellent ICC’s for intrarater-intersession comparisons [1,7,13]. Although higher ICC and lower MDC values were observed for interrater comparisons as compared to intrarater comparisons for several variables, they are inconsistent and not likely sufficiently different to be relevant. The results suggest reliable data can be produced between raters and between
assessments in a healthy adult population and that when collecting data across multiple sessions, maintaining the same rater does not significantly improve reliability within our laboratory. However, some caution should be taken when applying this finding because all raters in the current study were clinicians, each with over 10 years experience identifying anatomical landmarks. The experience level of the raters, although not assessed as part of this study, is suspected to influence the ability to use multiple raters across multiple sessions. It is possible that not all similarly experienced individuals would be able to reproduce the results obtained here. Additionally, landmark identification and marker placement may be less reliable when assessing patient populations with altered bony anatomy or segment geometry. To date, no studies have examined the effects of multiple controlled walking velocities on the reliability of kinematic and kinetic gait variables. ICC and MDC values were generally consistent across all walking velocity conditions. MDC values for both kinematic and kinetic variables were on average lower for the FR3 condition as compared to the FR2 and FR4 conditions. These differences are, however, small and not likely of clinical or scientific relevance. This suggests that a specific controlled velocity does not meaningfully influence the reliability of the variables obtained. Similar consistent results were also observed when comparing reliability at SSWV to the controlled velocities. Although SSWV between sessions may have the potential to impact the reliability of kinematic and kinetic variables, our young healthy subjects were consistent between sessions. Therefore it is not surprising that the resulting ICC and MDC values were similar to those obtained at controlled velocities. The potential exists for much larger variability in SSWV in a patient population; therefore,
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Table 3 ICC, SEM, and MDC for peak kinematic variables across all velocities for the interrater-intersession comparison. ICC values less than 0.75 and MDC values greater than 58 are presented in bold. Peaks description
Ankle angle (8) Initial plantarflexion Dorsiflexion Plantarflexion Sagittal range of motion Knee angle (8) Flexion at initial contact Stance flexion Mid/terminal stance extension Peak flexion during swing Sagittal range of motion Hip angle (8) Flexion during stance Extension during stance Flexion during swing Sagittal range of motion Adduction during stance Abduction during swing Frontal range of motion Pelvic angle (8) Anterior tilt Posterior tilt Sagittal range of motion Contralateral drop Contralateral elevation Frontal range of motion Hip forward Hip back Transverse range of motion Trunk-lab angle (8) Anterior trunk lean Posterior trunk lean Sagittal range of motion Ipsilateral lean Frontal range of motion Ipsilateral shoulder forward Transverse range of motion Average
ICC
SEM
MDC
SSWV
FR2
FR3
FR4
SSWV
FR2
FR3
FR4
SSWV
FR2
FR3
FR4
0.85 0.81 0.91 0.89
0.87 0.61 0.91 0.87
0.88 0.80 0.94 0.90
0.82 0.76 0.91 0.89
1.08 1.12 1.56 1.33
0.94 1.27 1.64 1.65
0.89 1.22 1.43 1.37
1.12 1.36 1.65 1.26
2.99 3.11 4.33 3.70
2.60 3.51 4.55 4.57
2.46 3.37 3.97 3.79
3.10 3.78 4.56 3.49
0.73 0.77 0.82 0.75 0.90
0.71 0.82 0.81 0.77 0.87
0.78 0.80 0.75 0.62 0.81
0.71 0.73 0.74 0.73 0.93
2.03 1.93 1.57 1.93 1.32
2.12 1.50 1.58 1.78 1.48
1.83 1.50 1.84 2.31 1.76
2.24 2.03 2.00 2.06 1.04
5.62 5.34 4.36 5.36 3.67
5.86 4.15 4.39 4.94 4.10
5.08 4.16 5.09 6.39 4.89
6.22 5.64 5.55 5.72 2.88
0.84 0.92 0.78 0.91 0.84 0.78 0.93
0.90 0.90 0.85 0.92 0.86 0.72 0.93
0.91 0.89 0.84 0.90 0.84 0.76 0.91
0.91 0.89 0.83 0.89 0.83 0.72 0.96
2.03 1.69 2.30 1.16 1.54 1.45 0.81
1.72 1.71 1.93 0.99 1.39 1.61 0.72
1.59 1.88 2.06 1.14 1.49 1.51 0.77
1.75 1.86 2.20 1.15 1.59 1.70 0.57
5.62 4.69 6.39 3.21 4.26 4.02 2.23
4.76 4.73 5.36 2.74 3.84 4.45 2.00
4.41 5.22 5.72 3.17 4.14 4.17 2.14
4.85 5.16 6.10 3.19 4.40 4.72 1.57
0.86 0.84 0.92 0.45 0.69 0.90 0.90 0.84 0.95
0.87 0.85 0.85 0.52 0.53 0.89 0.88 0.88 0.94
0.89 0.87 0.94 0.47 0.54 0.86 0.89 0.86 0.96
0.88 0.87 0.96 0.45 0.60 0.87 0.87 0.92 0.94
1.74 1.76 0.34 1.34 1.26 0.81 1.05 1.03 0.93
1.67 1.71 0.31 1.27 1.45 0.74 1.02 0.81 0.80
1.60 1.62 0.21 1.31 1.45 0.85 1.05 1.02 0.70
1.65 1.62 0.25 1.29 1.45 0.89 1.23 0.81 1.05
4.81 4.87 0.94 3.72 3.49 2.25 2.90 2.86 2.59
4.64 4.74 0.85 3.53 4.01 2.04 2.82 2.25 2.22
4.43 4.48 0.59 3.63 4.02 2.37 2.92 2.82 1.94
4.58 4.48 0.68 3.59 4.01 2.46 3.42 2.24 2.91
0.96 0.97 0.91 0.90 0.95 0.77 0.90
0.95 0.96 0.89 0.83 0.92 0.83 0.91
0.96 0.96 0.86 0.85 0.95 0.77 0.91
0.96 0.97 0.83 0.88 0.94 0.78 0.87
0.94 0.88 0.26 0.66 0.41 1.24 0.62
0.97 0.98 0.29 0.88 0.50 1.01 0.73
0.92 0.95 0.29 0.80 0.41 1.12 0.56
0.91 0.87 0.41 0.70 0.45 1.17 0.74
2.61 2.43 0.72 1.83 1.14 3.45 1.71
2.70 2.72 0.80 2.44 1.38 2.79 2.03
2.56 2.64 0.80 2.22 1.14 3.10 1.54
2.54 2.42 1.13 1.94 1.26 3.24 2.05
0.85
0.84
0.84
0.84
1.25
1.22
1.23
1.28
3.48
3.39
3.42
3.56
further study into the use of controlled velocities in patients is warranted. Currently, only Klejman et al. and Lobet et al. provide both ICC and MDC values for commonly used gait variables [1,13]. Both studies assessed between session reliability using the same rater, and present substantially lower ICC values and greater MDC values than any of the session and rater comparisons examined in the current study. Several factors may have contributed to the higher ICC and lower MDC values obtained in the current study. Potential factors include the type of subjects tested, time between sessions and digitizing process. Klejman et al. tested 28 children with various severities of cerebral palsy over a one to two week period. It would be expected that the MDC values in the current study would be lower than Klejman because adults have been shown to have less variability than children [28] and children with cerebral palsy have greater variability in lower extremity kinematics than healthy children [29]. Lobet et al. assessed measurement error in an adult population with a joint degeneration disease with an average of 13 weeks between testing. This likely contributed to higher MDC than the current study. Lobet also suggested that significant between session changes in motion of several joints indicated an actual change had occurred in the subject’s gait pattern [13]. Consistent with both Klejman et al. and Lobet et al. ICC values for range of motion were higher, and MDC values were lower than those for peak kinematic measures [1,13]. This result suggests the need to further develop methods for the reliable
identification of anatomical landmarks and local coordinate system orientation in order to improve data quality. The MDC values presented in this study suggest caution should be used when interpreting small within subject or between group differences in kinematic or kinetic variables. Fortunately, for many studies currently published, pre/post changes in gait parameters attributed to treatment interventions are commonly above the MDC values obtained in this study in healthy individuals [30–32]. Because MDC values likely vary considerably between laboratories and patient populations, it is important to identify both lab and population specific MDC values to ensure appropriate data interpretation. The population assessed in this study is both a strength and a limitation. The subjects represent a subset of the general adult population that is healthy and active. Using a healthy population provides the best opportunity to identify measurement errors associated with the specific testing methodology, while minimizing the influence of natural variability in subject performance. However, as a result these data should only serve as a point of reference when interpreting data from patient populations which are expected to have higher MDC values as has been seen previously [1,13]. Additionally, ICC values of 1.0 were obtained for several hip kinematic and kinetic variables for the interrater-intrasession comparisons. Although the calculated SEM and MDC values were zero, the results should not be taken to indicate the absence of error.
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Table 4 ICC, SEM, and MDC for peak kinetic variables across all velocities for the interrater-intersession comparison. ICC values less than 0.75 are presented in bold. Peaks description
Ankle moment (Nm/kg) Dorsiflexion Plantarflexion Knee moment (Nm/kg) Initial contact flexion Stance extension Mid/terminal stance flexion Loading response varus First peak valgus Second peak valgus Stance internal rotation Stance external rotation Hip moment (Nm/kg) Initial contact extension Terminal stance flexion Swing extension Loading response abduction Terminal stance abduction Loading response external rotation Terminal stance internal rotation Ankle sagittal plane powers (W/kg) Initial contact absorption Stance absorption Terminal stance generation Knee sagittal plane powers (W/kg) Initial contact generation Loading response absorption Terminal stance generation Terminal stance absorption Hip sagittal plane powers (W/kg) Stance generation Stance absorption Swing generation Average
ICC
SEM
MDC
SSWV
FR2
FR3
FR4
SSWV
FR2
FR3
FR4
SSWV
FR2
FR3
FR4
0.80 0.90
0.67 0.79
0.50 0.82
0.69 0.82
0.02 0.05
0.03 0.05
0.04 0.05
0.03 0.06
0.07 0.13
0.07 0.13
0.11 0.15
0.08 0.16
0.91 0.81 0.89 0.89 0.86 0.88 0.87 0.90
0.94 0.82 0.89 0.92 0.91 0.86 0.77 0.85
0.90 0.87 0.85 0.91 0.86 0.90 0.87 0.87
0.91 0.86 0.89 0.87 0.87 0.83 0.88 0.77
0.04 0.08 0.05 0.03 0.05 0.05 0.02 0.01
0.02 0.04 0.04 0.02 0.04 0.04 0.02 0.01
0.04 0.05 0.06 0.02 0.04 0.04 0.01 0.01
0.03 0.06 0.05 0.03 0.04 0.06 0.02 0.02
0.11 0.21 0.13 0.07 0.13 0.14 0.05 0.04
0.07 0.12 0.11 0.04 0.10 0.12 0.04 0.03
0.10 0.14 0.15 0.05 0.10 0.11 0.03 0.03
0.10 0.17 0.13 0.07 0.12 0.17 0.04 0.04
0.90 0.80 0.91 0.89 0.80 0.70 0.88
0.96 0.80 0.91 0.91 0.80 0.80 0.73
0.91 0.52 0.80 0.88 0.83 0.75 0.73
0.89 0.79 0.80 0.93 0.82 0.83 0.79
0.07 0.09 0.03 0.06 0.06 0.04 0.01
0.03 0.06 0.02 0.04 0.05 0.02 0.02
0.05 0.11 0.03 0.05 0.05 0.03 0.02
0.05 0.09 0.04 0.04 0.06 0.03 0.01
0.20 0.25 0.08 0.16 0.16 0.11 0.03
0.08 0.17 0.05 0.12 0.15 0.07 0.05
0.14 0.30 0.09 0.15 0.14 0.08 0.05
0.15 0.26 0.10 0.12 0.16 0.08 0.04
0.79 0.91 0.75
0.69 0.71 0.67
0.56 0.83 0.61
0.78 0.84 0.74
0.07 0.09 0.29
0.05 0.10 0.14
0.07 0.11 0.20
0.08 0.12 0.22
0.20 0.26 0.80
0.13 0.27 0.38
0.20 0.30 0.56
0.21 0.33 0.60
0.90 0.86 0.87 0.88
0.86 0.84 0.82 0.91
0.86 0.87 0.79 0.89
0.89 0.84 0.88 0.92
0.16 0.14 0.12 0.09
0.08 0.06 0.08 0.05
0.13 0.08 0.13 0.08
0.14 0.13 0.11 0.08
0.44 0.40 0.32 0.26
0.21 0.15 0.23 0.14
0.36 0.23 0.35 0.23
0.40 0.37 0.31 0.23
0.76 0.84 0.90
0.69 0.83 0.96
0.58 0.67 0.91
0.74 0.73 0.89
0.14 0.10 0.08
0.07 0.04 0.03
0.12 0.09 0.05
0.13 0.12 0.07
0.39 0.28 0.21
0.18 0.12 0.07
0.34 0.25 0.15
0.36 0.33 0.18
0.85
0.83
0.79
0.83
0.07
0.05
0.06
0.07
0.21
0.13
0.18
0.20
5. Conclusions In this study, the reliability and measurement error of several common gait measures was assessed by comparing between raters and over time in a healthy adult population. ICC values were in the good to excellent range, with no effect of rater or session. MDC values were lower than previously reported [1,13] with small differences between raters and sessions. Velocity had no effect on reliability for any gait variables and MDC values were consistent across velocities. Overall, this study demonstrates reliable assessment of gait performance can be achieved when using multiple raters and multiple sessions. This study also provides MDC values for individuals free from pathology, for comparison with future studies in patients. Acknowledgement Support provided by the Military Amputee Research Program (to JMW). Conflict of interest The authors have no conflict of interest to report. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.gaitpost.2011.09.105. References [1] Klejman S, Andrysek J, Dupuis A, Wright V. Test-retest reliability of discrete gait parameters in children with cerebral palsy. Arch Phys Med Rehabil 2010;91:781–7.
[2] Yavuzer G, Oken O, Elhan A, Stam HJ. Repeatability of lower limb threedimensional kinematics in patients with stroke. Gait Posture 2008;27(January (1)):31–5. [3] Frigo C, Tesio L. Speed-dependent variations of lower-limb joint angles during walking: a graphic computerized method showing individual patterns. normal and prosthetized subjects. Am J Phys Med 1986;65(2):51–62. [4] McGinley JL, Baker R, Wolfe R, Morris ME. The reliability of three-dimensional kinemaitic gait measurements: a systematic review. Gait Posture 2009;29: 360–9. [5] Mokkink LB, Terwee CB, Knol DL, Stratford PW, Alonso J, Patrick DL, et al. Protocol of the COSMIN study: COnsensus-based Standards for the selection of health Measurement INstruments. BMC Med Res Methodol 2006;6 (1):2. [6] Besier TF, Sturnieks DL, Alderson JA, Lloyd DG. Repeatability of gait data using a functional hip joint centre and a mean helical knee axis. J Biomech 2003;36 (August (8)):1159–68. [7] Ferber R, McClay Davis I, Williams 3rd DS, Laughton C. A comparison of withinand between-day reliability of discrete 3D lower extremity variables in runners. J Orthop Res 2002;20(November (6)):1139–45. [8] Maynard V, Bakheit AM, Oldham J, Freeman J. Intra-rater and inter-rater reliability of gait measurements with CODA mpx30 motion analysis system. Gait Posture 2003;17(February (1)):59–67. [9] Mackey AH, Walt SE, Lobb GA, Stott NS. Reliability of upper and lower limb three-dimensional kinematics in children with hemiplegia. Gait Posture 2005;22(August (1)):1–9. [10] Kyrolainen H, Belli A, Komi PV. Biomechanical factors affecting running economy. Med Sci Sports Exerc 2001;33(August (8)):1330–7. [11] Silverman AK, Fey NP, Portillo A, Walden JG, Bosker G, Neptune RR. Compensatory mechanisms in below-knee amputee gait in response to increasing steady-state walking speeds. Gait Posture 2008;28(November (4)):602–9. [12] de Vet HC, Terwee CB, Ostelo RW, Beckerman H, Knol DL, Bouter LM. Minimal changes in health status questionnaires: distinction between minimally detectable change and minimally important change. Health Qual Life Out 2006;4(54):1–5. [13] Lobet S, Detrembleur C, Francq B, Hermans C. Natural progression of bloodinduced joint damage in patients with haemophilia: clinical relevance and reproducibility of three-dimensional gait analysis. Haemophilia 2010;16(5): 813–21. [14] Vaughan CL, O’Malley MJ. Froude and the contribution of naval architecture to our understanding of bipedal locomotion. Gait Posture 2005;21(April (3)): 350–62.
J.M. Wilken et al. / Gait & Posture 35 (2012) 301–307 [15] England SA, Granata KP. The influence of gait speed on local dynamic stability of walking. Gait Posture 2007;25(February (2)):172–8. [16] Hof AL, Van Bockel RM, Schoppen T, Postema K. Control of lateral balance in walking. Experimental findings in normal subjects and above-knee amputees. Gait Posture 2007;25(February (2)):250–8. [17] Collins TD, Ghoussayni SN, Ewins DJ, Kent JA. A six degrees-of-freedom marker set for gait analysis: Repeatability and comparison with a modified Helen Hayes set. Gait Posture 2009;30(2):173–80. [18] Manal K, McClay Davis I, Galinat B, Stanhope S. The accuracy of estimating proximal tibial translation during natural cadence walking: bone vs. skin mounted targets. Clin Biomech 2003;18(February (2)):126–31. [19] Manal K, McClay I, Stanhope S, Richards J, Galinat B. Comparison of surface mounted markers and attachment methods in estimating tibial rotations during walking: an in vivo study. Gait Posture 2000;11(1):38–45. [20] Hausswirth C, Bigard AX, Le Chevalier JM. The Cosmed K4 telemetry system as an accurate device for oxygen uptake measurements during exercise. Int J Sports Med 1997;18(August (6)):449–53. [21] Wu G, Cavanagh PR. ISB recommendations for standardization in the reporting of kinematic data. J Biomech 1995;28(October (10)):1257–61. [22] Della Croce U, Leardini A, Chiari L, Cappozzo A. Human movement analysis using stereophotogrammetry. Part 4: assessment of anatomical landmark misplacement and its effects on joint kinematics. Gait Posture 2005;21(February (2)): 226–37. [23] Schwartz MH, Trost JP, Wervey RA. Measurement and management of errors in quantitative gait data. Gait Posture 2004;20(October (2)):196–203.
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Contents lists available at SciVerse ScienceDirect
Gait & Posture journal homepage: www.elsevier.com/locate/gaitpost
Reliability and minimal detectible change values for gait kinematics and kinetics in healthy adults§ Jason M. Wilken *, Kelly M. Rodriguez, Melissa Brawner, Benjamin J. Darter Center for the Intrepid, Department of Orthopedics and Rehabilitation, Brooke Army Medical Center, Ft. Sam Houston, TX 78234, USA
A R T I C L E I N F O
A B S T R A C T
Article history: Received 13 May 2011 Received in revised form 10 August 2011 Accepted 26 September 2011
Computerized assessment of gait is commonly used in both research and clinical settings to quantify gait mechanics and detect change in performance. Minimal Detectable Change values have only recently been reported, are only available for patient populations, and in many cases exceed 108. Twenty nine healthy individuals underwent two biomechanical gait assessments separated by 5.6 (SD 2.2) days, with two raters for each session. All subjects walked at a self selected pace and three controlled velocities. ICC, SEM and MDC for kinematic and kinetic measures were calculated for interrater-intrasession, intraraterintersession and interrater-intersession. ICC values were in the good to excellent range (r > 0.75) for all kinematic and kinetic variables and all comparisons. MDC values were lower than previously published data for all similar comparisons. The results of the current study suggest that reliability is good to excellent across a range of controlled walking velocities and the introduction of a second rater does not appreciably impact ICC or MDC values. In young healthy adults changes in gait kinematics of greater than approximately 58 can be identified when comparing between sessions. Published by Elsevier B.V.
Keywords: Reliability Minimal Detectable Change Intraclass Correlation Coefficient Gait analysis
1. Introduction Computerized assessment of gait is commonly used in both research and clinical settings to identify deviations, plan treatment and determine the effectiveness of interventions for a wide range of conditions such as cerebral palsy, lower extremity amputation and stroke [1–3]. The ability to effectively meet these objectives is dependent on the collection of data that allows identification of real and meaningful change in performance [4]. The ability to detect true change is limited by errors associated with collection methodology, and the effects of natural variability in performance over time. The COSMIN manual which can be used to guide the assessment of measurement properties for health measurement instruments, identifies the two distinct measurement properties of reliability and measurement error [5]. Reliability is associated with the true differences that can exist between patients or testing sessions, while measurement error accounts for the effect of systematic and random sources of error [5]. Errors can be due to the application of
§ The views expressed herein are those of the authors and do not reflect the official policy or position of Brooke Army Medical Center, the U.S. Army Medical Department, the U.S. Army Office of the Surgeon General, the Department of the Army, Department of Defense or the U.S. Government. * Corresponding author. Tel.: +1 210 916 1478; fax: +1 210 916 9016. E-mail addresses: [email protected], [email protected] (J.M. Wilken).
0966-6362/$ – see front matter . Published by Elsevier B.V. doi:10.1016/j.gaitpost.2011.09.105
markers, identification of anatomical landmarks, natural variation in walking and the ability of the system to accurately track markers [4]. In spite of large variations in collection methodology and study design [4], previous studies generally report acceptable reliability using Intraclass Correlation Coefficient (ICC) and Coefficient of Multiple Correlation (CMC) values [2,6–8]. There are however, limitations in the ability to generalize the findings associated with each of these studies to include use of a single rater, the presence of gait pathology, limited number of walking velocities tested, and use of reliability metrics that have limited use when interpreting change in clinical data. Within session or within rater comparisons over time are commonly used to determine the reliability of gait analysis data. Although useful for determining the specific effect of rater or time on the measurements, these comparisons do not effectively replicate the reality of clinical or research assessments which can require multiple raters over multiple sessions. For example, Beiser et al. assessed reliability using within and between rater comparisons but only within a single day of testing. Mackey et al. reported high CMC values and no difference in reliability for within and between session comparisons, but only used a single rater [9]. To date, no study has assessed reliability with multiple raters over multiple sessions. As a result, the combined effects of rater and session remain poorly understood. Walking velocity is a factor that may influence the reliability of gait data and has not been addressed through scientific study. All walking reliability studies reviewed by McGinley et al. assessed
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participants at a self selected walking velocity. Although self selected walking velocities are convenient for data collection purposes, walking velocity is known to influence kinetic variables [10,11]. Recent advances from large motion capture companies now allow investigators to readily control participant walking velocity through the use of external cueing. It is unclear if removing the potential variation induced by natural fluctuation in self-selected walking velocity would improve reliability. Statistical assessment of gait reliability has commonly been performed using the ICC and CMC. Evaluation using ICC and CMC provides information regarding the relative reliability of measurements, but can be of limited help when determining if an observed change is due to actual change in performance. Minimal Detectable Change (MDC), in contrast, provides meaningful and practical assessment of measurement error by providing a single value for each variable in the units of measure. More specifically, the MDC is described as the amount of change which is sufficiently greater than measurement error for the variable of interest [12]. It allows the investigator or clinician to determine if an observed change between assessments is a true difference due to the effect of a treatment intervention, or simply the result of measurement error. Currently, only two studies provide MDC values for computerized gait analysis data [1,13]. Both of these studies were conducted using patient populations and report MDC values as high as 128 for commonly used kinematic variables of the lower extremity [1,13]. Due to natural fluctuations in symptomatoloty or disease progression it is expected that patient populations will demonstrate greater variation in performance over time, and as a result have greater MDC values. If MDC values of similar magnitude are observed when assessing non-pathologic populations it would suggest limited usefulness for detecting all but the largest kinematic and kinetic changes. To date, MDC values from a healthy population have not been published. The availability of MDC values for healthy and pathologic populations will greatly aid scientists and clinicians as they interpret data. The purpose of the current study is to determine the intrarater and interrater reliability and MDC for commonly used gait variables within a single session and between sessions. A second objective is to examine the effect of walking velocity on reliability and MDC variables. 2. Methods 2.1. Subjects Twenty nine young healthy individuals (14 male, 15 female) with no current pain or history of major lower extremity injury participated in this study. Subjects were on average 24.7 (SD 5.7) years old with a mean body mass and height of 69.0 (SD 12.0) kg and 1.7 (SD 0.1) m, respectively. The average leg length was 88.0 (SD 5.8) cm. All subjects provided written informed consent prior to participation in this institutionally approved study. 2.2. Procedure All subjects underwent two biomechanical gait assessments separated by 5.6 (SD 2.2) days. Testing involved walking on level ground at a self-selected pace, a predefined velocity based on leg length (also referred to as a Froude (FR) velocity) [14] and velocities 20% faster and slower. The controlled velocities allow for dynamically equivalent comparisons across subjects based on each subject’s leg p length (l): v ¼ 0:40 ðg lÞ [15,16]. For the purpose of this paper the respective velocities are referred to as FR2, FR3 and FR4 in increasing order. Leg length was defined as the length in centimeters from the greater trochanter to the floor while the subject was standing. An automated auditory cue (Biofeed Trak, Motion Analysis Corp., Santa Rosa, CA), based on trunk marker velocity, guided subjects to walk at each pre-determined velocity. Full body kinematics were assessed using a 6 degrees of freedom marker set [17–19] and a 26 camera optoelectronic motion capture system (Motion Analysis Corp., Santa Rosa, CA) operating at 120 Hz [19] (see Supplemental material) (Fig. 1). Ground reaction force data were obtained using eight AMTI force plates (AMTI, Inc., Watertown, MA) embedded in the walkway operating at a sampling rate of 1200 Hz. Segment local coordinate system orientation was determined in accordance with ISB standards [20,21]. A digitizing process was used to identify
Fig. 1. Screen capture demonstrating representative marker placement.
joint center locations and define the local coordinate system for the shank and thigh segments [22]. Each segment was tracked as an independent rigid body to avoid the potential propagation of errors [23]. To determine the effect of digitizing on lower extremity kinematics and kinetics two raters identified the medial and lateral malleoli and condyles at the ankle and knee respectively. Each rater had over 10 years experience identifying anatomical landmarks. Five gait cycles for each condition were analyzed using Visual 3D (C-Motion Inc., Rockville, MD). Data were normalized to 100% step cycle and peak values for each kinematic and kinetic variable of interest were extracted using MATLAB (The Mathworks, Natick, MA) software and exported for statistical analysis. 2.3. Statistical analysis To assess reliability, the following three comparisons were performed: interrater-intrasession, intrarater-intersession and interrater-intersession. SPSS v. 16 (SPSS Inc., Chicago, IL) was used to calculate mean, standard deviation and ICC (2, k). Standard error of the measurement (SEM) and MDC were calculated for each variable using Microsoft Excel 2007(Microsoft Corp., Redmond, WA). SEM was calculated using the equation SD SQRT (1-ICC), where SD is the pooled variance. MDC was calculated using the equation SEM 1.96 SQRT2 [24]. A two-way (Velocity Session) repeated measures Analysis of Variance (ANOVA) was used to detect between session differences in walking velocity. ICC values 0.75 or higher were considered to be excellent, 0.40–0.74 to be fair to good, and 0.40 or lower to be poor [25]. Published criteria for interpreting MDC values are not currently available and actual MDC values provided in the tables should be referenced when interpreting results. However, to highlight kinematic measures with greater measurement error, MDC values greater than the often used clinical threshold of five degrees [26,27] were identified.
3. Results ICC, SEM, and MDC values for the rater and session assessments of kinematic reliability are presented in Table 1. All three ratersession comparisons were performed for all velocities. Similar results were found across all velocities with mean absolute differences of less than 0.05 for ICC and 0.78 for MDC values between velocity conditions. Therefore, only data from a single controlled velocity (FR3) are presented. Data for intrasession comparisons are not provided for pelvic and trunk kinematics as these segments are based solely on marker data and not affected by the digitizing process. Overall, excellent ICC values (ICC range, 0.76–1.00) were obtained for 100% of interrater-intrasession, 82%
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Table 1 ICC, SEM and MDC values for peak kinematic variables. Table includes (1) interrater-intrasession, (2) intrarater-intersession and (3) interrater-intersession comparisons. * Denotes variables not affected by digitizing process. ICC values less than 0.75 and MDC values greater than 58 are presented in bold. FR3
ICC(95%CI)
Peaks description
1
Ankle angle (8) Initial plantarflexion Dorsiflexion Plantarflexion Sagittal range of motion Knee angle (8) Flexion at initial contact Stance flexion Mid/terminal stance extension Peak flexion during swing Sagittal range of motion Hip angle (8) Flexion during stance Extension during stance Flexion during swing Sagittal range of motion Adduction during stance Abduction during swing Frontal range of motion Pelvic angle (8) Anterior tilt Posterior tilt Sagittal range of motion Contralateral drop Contralateral elevation Frontal range of motion Hip forward Hip back Transverse range of motion Trunk-lab angle (8) Anterior trunk lean Posterior trunk lean Sagittal range of motion Ipsilateral lean Frontal range of motion Ipsilateral shoulder forward Transverse range of motion Average
SEM 2
3
MDC
1
2
3
1
2
3
0.91 0.89 0.98 0.98
(0.79–0.95) (0.75–0.94) (0.95–0.99) (0.95–0.99)
0.81 0.82 0.94 0.91
(0.59–0.91) (0.60–0.91) (0.86–0.97) (0.79–0.95)
0.88 0.80 0.94 0.90
(0.73–0.94) (0.56–0.91) (0.85–0.97) (0.77–0.95)
0.85 1.04 0.83 0.68
1.05 1.32 1.24 1.24
0.89 1.22 1.43 1.37
2.35 2.88 2.30 1.87
2.91 3.66 3.44 3.45
2.46 3.37 3.97 3.79
0.78 0.78 0.81 0.84 0.98
(0.56–0.89) (0.56–0.89) (0.62–0.90) (0.68–0.92) (0.95–0.99)
0.85 0.74 0.70 0.57 0.77
(0.67–0.93) (0.41–0.87) (0.34–0.86) (0.05–0.80) (0.49–0.89)
0.78 0.80 0.75 0.62 0.81
(0.50–0.89) (0.56–0.91) (0.45–0.88) (0.17–0.82) (0.58–0.91)
1.73 1.66 1.70 1.71 0.57
1.48 1.74 1.90 2.65 1.83
1.83 1.50 1.84 2.31 1.76
4.81 4.61 4.70 4.75 1.58
4.12 4.83 5.28 7.33 5.08
5.08 4.16 5.09 6.39 4.89
0.99 0.99 0.99 1.00 0.99 0.99 1.00
(0.97–0.99) (0.98–0.99) (0.97–0.99) (1.00–1.00) (0.98–0.99) (0.98–0.99) (0.99–1.00)
0.89 0.88 0.85 0.93 0.82 0.66 0.89
(0.76–0.95) (0.72–0.94) (0.66–0.93) (0.85–0.97) (0.60–0.91) (0.24–0.84) (0.75–0.94)
0.91 0.89 0.84 0.90 0.84 0.76 0.91
(0.80–0.95) (0.74–0.94) (0.64–0.92) (0.76–0.95) (0.64–0.92) (0.46–0.88) (0.81–0.96)
0.49 0.49 0.50 0.00 0.31 0.32 0.00
1.73 1.86 2.09 0.99 1.59 1.69 0.94
1.59 1.88 2.06 1.14 1.49 1.51 0.77
1.36 1.35 1.40 0.00 0.87 0.88 0.00
4.80 5.16 5.80 2.74 4.41 4.69 2.61
4.41 5.22 5.72 3.17 4.14 4.17 2.14
* * * * * * * * *
0.82 0.79 0.93 0.45 0.45 0.85 0.90 0.80 0.96
(0.60–0.91) (0.54–0.90) (0.84–0.96) (S0.20–0.75) (S0.21–0.74) (0.67–0.93) (0.77–0.95) (0.55–0.90) (0.91–0.98)
0.89 0.87 0.94 0.47 0.54 0.86 0.89 0.86 0.96
(0.75–0.94) (0.71–0.94) (0.86–0.97) (S0.16–0.75) (0.00–0.79) (0.70–0.93) (0.74–0.94) (0.68–0.93) (0.91–0.98)
* * * * * * * * *
1.97 1.96 0.23 1.35 1.57 0.91 1.08 1.30 0.80
1.60 1.62 0.21 1.31 1.45 0.85 1.05 1.02 0.70
* * * * * * * * *
5.45 5.43 0.64 3.75 4.35 2.52 2.99 3.61 2.21
4.43 4.48 0.59 3.63 4.02 2.37 2.92 2.82 1.94
* * * * * * *
0.95 0.96 0.84 0.84 0.95 0.81 0.90
(0.89–0.97) (0.90–0.98) (0.64–0.92) (0.64–0.92) (0.88–0.97) (0.58–0.91) (0.77–0.95)
0.96 0.96 0.86 0.85 0.95 0.77 0.91
(0.91–0.98) (0.91–0.98) (0.69–0.93) (0.67–0.93) (0.89–0.97) (0.50–0.89) (0.79–0.95)
* * * * * * *
0.96 1.01 0.32 0.83 0.41 1.11 0.58
0.92 0.95 0.29 0.80 0.41 1.12 0.56
* * * * * * *
2.67 2.79 0.88 2.29 1.13 3.08 1.62
2.56 2.64 0.80 2.22 1.14 3.10 1.54
0.93
0.82
0.81
1.30
1.23
2.23
3.62
3.42
of intrarater-intersession and 91% of interrater-intersession data. MDC values less than 58 were found in 100% of interraterintrasession, 77% of intrarater-intersession, and 86% of interraterintersession. The lowest ICC values were observed in peak knee flexion during swing, and contralateral pelvic elevation and drop (ICC range, 0.45–0.75) for intrarater-intersession and interraterintersession conditions. Table 2 displays the effect of rater and session on lower extremity kinetics at FR3. All ICC values for interrater-intrasession reliability were excellent. For intrarater-intersession and interrater-intersession, 70% and 74% of the ICC values were in the excellent range, respectively. Hip moment in terminal stance and peak hip power absorption and generation during stance have the lowest ICC values in all three comparison groups (ICC range, 0.48– 0.62). The effect of velocity on kinematic variables for interraterintersession comparisons are shown in Table 3. The mean velocity (m/s) for each condition for all subjects for the first session is as follows: 1.31 (SD 0.17) for SSWV, 0.97 (SD 0.05) for FR2, 1.18 (SD 0.06) for FR3, and 1.39 (SD 0.06) for FR4. There was no significant difference in walking velocity between the two sessions (p = 0.55). Good to excellent ICC values were observed for all kinematic variables. When averaging across dependent variables the mean ICC value for all controlled velocities were identical. Self-selected walking velocity and FR3 had the highest percentage of ICC values in the excellent range at 89%, with FR2 and FR4 at 82% and 80%, respectively. For MDC, FR4 and SSWV had the lowest percentage of
0.84
kinematic values less than 58, at 84%. FR3 had 86% with FR2 having the highest percentage at 91%. Table 4 shows the effect of walking velocity on kinetic variables for interrater-intersession comparisons. The ankle dorsiflexion moment demonstrates the greatest difference between velocities, ranging from an ICC of 0.50 for FR3 to 0.80 for SSWV. For kinetic data, 96% of ICC values were in the excellent range for the SSWV condition, while FR3 had the lowest percentage at 74%. MDC values for kinematic and kinetic measures did not demonstrate consistent trends indicating MDC values were greater or smaller for a particular velocity. The greatest relative difference in MDC values are observed in terminal stance ankle power generation, with SSWV two times greater than FR2.
4. Discussion Patients and research subjects are commonly tested on multiple occasions over a period of days or weeks to track changes in gait associated with a treatment. The use of multiple raters and/or testing over time can introduce measurement error that can affect data quality and influence data interpretation. The ability to distinguish between measurement error and true change over time is essential to the successful application of gait analysis for clinical and research purposes. The results of the current study suggest that, independent of pathology, reliability is excellent for most measures across a wide range of walking velocities, and the
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Table 2 ICC, SEM and MDC values for peak kinetic variables. Table includes (1) interrater-intrasession, (2) intrarater-intersession, and (3) interrater-intersession comparisons. ICC values less than 0.75 are presented in bold. Peaks description
ICC(95%CI)
SEM
MDC
1
2
3
1
2
3
1
2
3
0.79 (0.54–0.90) 0.92 (0.81–0.96)
0.67 (0.28–0.85) 0.84 (0.65–0.92)
0.50 (0.10–0.77) 0.82 (0.60–0.91)
0.02 0.04
0.03 0.05
0.04 0.05
0.07 0.10
0.07 0.13
0.11 0.15
Ankle moment (Nm/kg) Dorsiflexion Plantarflexion Knee moment (Nm/kg) Initial contact flexion Stance extension Mid/terminal stance flexion Loading response varus First peak valgus Second peak valgus Stance internal rotation Stance external rotation Hip moment (Nm/kg) Initial contact extension Terminal stance flexion Swing extension Loading response abduction Terminal stance abduction Loading response external rotation Terminal stance internal rotation Ankle sagittal plane powers (W/kg) Initial contact absorption Stance absorption Terminal stance generation Knee sagittal plane powers (W/kg) Initial contact generation Loading response absorption Terminal stance generation Terminal stance absorption Hip sagittal plane powers (W/kg) Stance generation Stance absorption Swing generation
0.59 0.89 0.90 0.92 0.76 0.90 0.96 0.95
(0.09–0.81) (0.75–0.94) (0.78–0.95) (0.81–0.96) (0.47–0.89) (0.78–0.95) (0.91–0.98) (0.88–0.97)
0.88 0.66 0.76 0.82 0.88 0.78 0.79 0.88
(0.74–0.94) (0.26–0.84) (0.46–0.89) (0.61–0.92) (0.73–0.94) (0.51–0.90) (0.53–0.90) (0.72–0.94)
0.90 0.87 0.85 0.91 0.86 0.90 0.87 0.87
(0.78–0.95) (0.71–0.94) (0.66–0.93) (0.80–0.96) (0.70–0.93) (0.78–0.95) (0.71–0.94) (0.72–0.94)
0.10 0.05 0.05 0.02 0.06 0.04 0.01 0.01
0.04 0.08 0.07 0.02 0.03 0.05 0.01 0.01
0.04 0.05 0.06 0.02 0.04 0.04 0.01 0.01
0.27 0.13 0.13 0.04 0.17 0.10 0.02 0.02
0.10 0.21 0.20 0.06 0.10 0.15 0.04 0.03
0.10 0.14 0.15 0.05 0.10 0.11 0.03 0.03
1.00 1.00 0.95 1.00 1.00 1.00 1.00
(0.99–1.00) (0.99–1.00) (0.89–0.97) (1.00–1.00) (0.99–1.00) (0.99–1.00) (0.99–1.00)
0.89 0.48 0.77 0.88 0.85 0.65 0.73
(0.74–0.94) (S0.13–0.76) (0.48–0.89) (0.73–0.94) (0.67–0.93) (0.23–0.84) (0.40–0.87)
0.91 0.52 0.80 0.88 0.83 0.75 0.73
(0.79–0.95) (0.05–0.78) (0.55–0.90) (0.73–0.94) (0.61–0.92) (0.45–0.88) (0.40–0.87)
0.01 0.00 0.02 0.00 0.00 0.00 0.00
0.06 0.11 0.03 0.05 0.05 0.04 0.02
0.05 0.11 0.03 0.05 0.05 0.03 0.02
0.01 0.00 0.05 0.00 0.00 0.00 0.00
0.15 0.31 0.08 0.15 0.14 0.10 0.05
0.14 0.30 0.09 0.15 0.14 0.08 0.05
1.00 (0.99–1.00) 1.00 (0.99–1.00) 1.00 (0.99–0.99)
Average
0.93
0.83 (0.62–0.92) 0.98 (0.95–0.99) 0.95 (0.90–0.97)
0.77 (0.48–0.89) 0.84 (0.64–0.92) 0.75 (0.45–0.88)
0.56 (0.03–0.80) 0.83 (0.61–0.92) 0.61 (0.14–0.82)
0.04 0.04 0.07
0.05 0.11 0.17
0.07 0.11 0.20
0.11 0.11 0.20
0.13 0.30 0.48
0.20 0.30 0.56
0.99 0.93 0.86 0.97
0.81 0.75 0.68 0.90
0.86 0.87 0.79 0.89
(0.69–0.93) (0.71–0.94) (0.54–0.90) (0.75–0.94)
0.03 0.06 0.09 0.04
0.15 0.10 0.15 0.08
0.13 0.08 0.13 0.08
0.09 0.16 0.25 0.11
0.41 0.28 0.42 0.22
0.36 0.23 0.35 0.23
0.62 (0.16–0.82) 0.69 (0.30–0.85) 0.92 (0.82–0.96)
0.58 (0.07–0.80) 0.67 (0.27–0.84) 0.91 (0.79–0.95)
0.01 0.00 0.01
0.13 0.09 0.05
0.12 0.09 0.05
0.02 0.00 0.03
0.37 0.25 0.14
0.34 0.25 0.15
0.77
0.79
0.03
0.07
0.06
0.08
0.19
0.18
(0.97–0.99) (0.85–0.96) (0.69–0.93) (0.93–0.98)
(0.57–0.91) (0.44–0.88) (0.29–0.85) (0.78–0.95)
introduction of a second rater does not appreciably impact ICC or MDC values. In this study the addition of a second rater did not appreciably affect the reliability of kinematic or kinetic data. The results are in contrast to those of Maynard et al. which demonstrate large but inconsistent differences in ICC values between intrarater and interrater comparisons [8]. ICC values for interrater-intrasession comparisons were the highest of all comparisons. This is to be expected as anatomical landmark identification is the only factor influencing calculated values. The results do, however, demonstrate the importance of landmark identification. Although ICC values are high for all variables, interrater MDC values vary widely between variables. Knee kinematic variables show the greatest effect of digitizing with MDC values greater than 4.68 for peak variables. Range of motion variables yielded substantially lower MDC values for all joints and segments suggesting offsets in local coordinate system orientation contributed to interrater differences. Interrater differences in knee landmark identification also likely contributed to lower ICC values and higher MDC values which were observed for knee joint moments as compared to moments at the ankle and hip. Reliability was generally excellent for both intrarater and interrater comparisons between sessions. Intersession results from the current study are similar to those of previous studies which indicate good to excellent ICC’s for intrarater-intersession comparisons [1,7,13]. Although higher ICC and lower MDC values were observed for interrater comparisons as compared to intrarater comparisons for several variables, they are inconsistent and not likely sufficiently different to be relevant. The results suggest reliable data can be produced between raters and between
assessments in a healthy adult population and that when collecting data across multiple sessions, maintaining the same rater does not significantly improve reliability within our laboratory. However, some caution should be taken when applying this finding because all raters in the current study were clinicians, each with over 10 years experience identifying anatomical landmarks. The experience level of the raters, although not assessed as part of this study, is suspected to influence the ability to use multiple raters across multiple sessions. It is possible that not all similarly experienced individuals would be able to reproduce the results obtained here. Additionally, landmark identification and marker placement may be less reliable when assessing patient populations with altered bony anatomy or segment geometry. To date, no studies have examined the effects of multiple controlled walking velocities on the reliability of kinematic and kinetic gait variables. ICC and MDC values were generally consistent across all walking velocity conditions. MDC values for both kinematic and kinetic variables were on average lower for the FR3 condition as compared to the FR2 and FR4 conditions. These differences are, however, small and not likely of clinical or scientific relevance. This suggests that a specific controlled velocity does not meaningfully influence the reliability of the variables obtained. Similar consistent results were also observed when comparing reliability at SSWV to the controlled velocities. Although SSWV between sessions may have the potential to impact the reliability of kinematic and kinetic variables, our young healthy subjects were consistent between sessions. Therefore it is not surprising that the resulting ICC and MDC values were similar to those obtained at controlled velocities. The potential exists for much larger variability in SSWV in a patient population; therefore,
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Table 3 ICC, SEM, and MDC for peak kinematic variables across all velocities for the interrater-intersession comparison. ICC values less than 0.75 and MDC values greater than 58 are presented in bold. Peaks description
Ankle angle (8) Initial plantarflexion Dorsiflexion Plantarflexion Sagittal range of motion Knee angle (8) Flexion at initial contact Stance flexion Mid/terminal stance extension Peak flexion during swing Sagittal range of motion Hip angle (8) Flexion during stance Extension during stance Flexion during swing Sagittal range of motion Adduction during stance Abduction during swing Frontal range of motion Pelvic angle (8) Anterior tilt Posterior tilt Sagittal range of motion Contralateral drop Contralateral elevation Frontal range of motion Hip forward Hip back Transverse range of motion Trunk-lab angle (8) Anterior trunk lean Posterior trunk lean Sagittal range of motion Ipsilateral lean Frontal range of motion Ipsilateral shoulder forward Transverse range of motion Average
ICC
SEM
MDC
SSWV
FR2
FR3
FR4
SSWV
FR2
FR3
FR4
SSWV
FR2
FR3
FR4
0.85 0.81 0.91 0.89
0.87 0.61 0.91 0.87
0.88 0.80 0.94 0.90
0.82 0.76 0.91 0.89
1.08 1.12 1.56 1.33
0.94 1.27 1.64 1.65
0.89 1.22 1.43 1.37
1.12 1.36 1.65 1.26
2.99 3.11 4.33 3.70
2.60 3.51 4.55 4.57
2.46 3.37 3.97 3.79
3.10 3.78 4.56 3.49
0.73 0.77 0.82 0.75 0.90
0.71 0.82 0.81 0.77 0.87
0.78 0.80 0.75 0.62 0.81
0.71 0.73 0.74 0.73 0.93
2.03 1.93 1.57 1.93 1.32
2.12 1.50 1.58 1.78 1.48
1.83 1.50 1.84 2.31 1.76
2.24 2.03 2.00 2.06 1.04
5.62 5.34 4.36 5.36 3.67
5.86 4.15 4.39 4.94 4.10
5.08 4.16 5.09 6.39 4.89
6.22 5.64 5.55 5.72 2.88
0.84 0.92 0.78 0.91 0.84 0.78 0.93
0.90 0.90 0.85 0.92 0.86 0.72 0.93
0.91 0.89 0.84 0.90 0.84 0.76 0.91
0.91 0.89 0.83 0.89 0.83 0.72 0.96
2.03 1.69 2.30 1.16 1.54 1.45 0.81
1.72 1.71 1.93 0.99 1.39 1.61 0.72
1.59 1.88 2.06 1.14 1.49 1.51 0.77
1.75 1.86 2.20 1.15 1.59 1.70 0.57
5.62 4.69 6.39 3.21 4.26 4.02 2.23
4.76 4.73 5.36 2.74 3.84 4.45 2.00
4.41 5.22 5.72 3.17 4.14 4.17 2.14
4.85 5.16 6.10 3.19 4.40 4.72 1.57
0.86 0.84 0.92 0.45 0.69 0.90 0.90 0.84 0.95
0.87 0.85 0.85 0.52 0.53 0.89 0.88 0.88 0.94
0.89 0.87 0.94 0.47 0.54 0.86 0.89 0.86 0.96
0.88 0.87 0.96 0.45 0.60 0.87 0.87 0.92 0.94
1.74 1.76 0.34 1.34 1.26 0.81 1.05 1.03 0.93
1.67 1.71 0.31 1.27 1.45 0.74 1.02 0.81 0.80
1.60 1.62 0.21 1.31 1.45 0.85 1.05 1.02 0.70
1.65 1.62 0.25 1.29 1.45 0.89 1.23 0.81 1.05
4.81 4.87 0.94 3.72 3.49 2.25 2.90 2.86 2.59
4.64 4.74 0.85 3.53 4.01 2.04 2.82 2.25 2.22
4.43 4.48 0.59 3.63 4.02 2.37 2.92 2.82 1.94
4.58 4.48 0.68 3.59 4.01 2.46 3.42 2.24 2.91
0.96 0.97 0.91 0.90 0.95 0.77 0.90
0.95 0.96 0.89 0.83 0.92 0.83 0.91
0.96 0.96 0.86 0.85 0.95 0.77 0.91
0.96 0.97 0.83 0.88 0.94 0.78 0.87
0.94 0.88 0.26 0.66 0.41 1.24 0.62
0.97 0.98 0.29 0.88 0.50 1.01 0.73
0.92 0.95 0.29 0.80 0.41 1.12 0.56
0.91 0.87 0.41 0.70 0.45 1.17 0.74
2.61 2.43 0.72 1.83 1.14 3.45 1.71
2.70 2.72 0.80 2.44 1.38 2.79 2.03
2.56 2.64 0.80 2.22 1.14 3.10 1.54
2.54 2.42 1.13 1.94 1.26 3.24 2.05
0.85
0.84
0.84
0.84
1.25
1.22
1.23
1.28
3.48
3.39
3.42
3.56
further study into the use of controlled velocities in patients is warranted. Currently, only Klejman et al. and Lobet et al. provide both ICC and MDC values for commonly used gait variables [1,13]. Both studies assessed between session reliability using the same rater, and present substantially lower ICC values and greater MDC values than any of the session and rater comparisons examined in the current study. Several factors may have contributed to the higher ICC and lower MDC values obtained in the current study. Potential factors include the type of subjects tested, time between sessions and digitizing process. Klejman et al. tested 28 children with various severities of cerebral palsy over a one to two week period. It would be expected that the MDC values in the current study would be lower than Klejman because adults have been shown to have less variability than children [28] and children with cerebral palsy have greater variability in lower extremity kinematics than healthy children [29]. Lobet et al. assessed measurement error in an adult population with a joint degeneration disease with an average of 13 weeks between testing. This likely contributed to higher MDC than the current study. Lobet also suggested that significant between session changes in motion of several joints indicated an actual change had occurred in the subject’s gait pattern [13]. Consistent with both Klejman et al. and Lobet et al. ICC values for range of motion were higher, and MDC values were lower than those for peak kinematic measures [1,13]. This result suggests the need to further develop methods for the reliable
identification of anatomical landmarks and local coordinate system orientation in order to improve data quality. The MDC values presented in this study suggest caution should be used when interpreting small within subject or between group differences in kinematic or kinetic variables. Fortunately, for many studies currently published, pre/post changes in gait parameters attributed to treatment interventions are commonly above the MDC values obtained in this study in healthy individuals [30–32]. Because MDC values likely vary considerably between laboratories and patient populations, it is important to identify both lab and population specific MDC values to ensure appropriate data interpretation. The population assessed in this study is both a strength and a limitation. The subjects represent a subset of the general adult population that is healthy and active. Using a healthy population provides the best opportunity to identify measurement errors associated with the specific testing methodology, while minimizing the influence of natural variability in subject performance. However, as a result these data should only serve as a point of reference when interpreting data from patient populations which are expected to have higher MDC values as has been seen previously [1,13]. Additionally, ICC values of 1.0 were obtained for several hip kinematic and kinetic variables for the interrater-intrasession comparisons. Although the calculated SEM and MDC values were zero, the results should not be taken to indicate the absence of error.
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Table 4 ICC, SEM, and MDC for peak kinetic variables across all velocities for the interrater-intersession comparison. ICC values less than 0.75 are presented in bold. Peaks description
Ankle moment (Nm/kg) Dorsiflexion Plantarflexion Knee moment (Nm/kg) Initial contact flexion Stance extension Mid/terminal stance flexion Loading response varus First peak valgus Second peak valgus Stance internal rotation Stance external rotation Hip moment (Nm/kg) Initial contact extension Terminal stance flexion Swing extension Loading response abduction Terminal stance abduction Loading response external rotation Terminal stance internal rotation Ankle sagittal plane powers (W/kg) Initial contact absorption Stance absorption Terminal stance generation Knee sagittal plane powers (W/kg) Initial contact generation Loading response absorption Terminal stance generation Terminal stance absorption Hip sagittal plane powers (W/kg) Stance generation Stance absorption Swing generation Average
ICC
SEM
MDC
SSWV
FR2
FR3
FR4
SSWV
FR2
FR3
FR4
SSWV
FR2
FR3
FR4
0.80 0.90
0.67 0.79
0.50 0.82
0.69 0.82
0.02 0.05
0.03 0.05
0.04 0.05
0.03 0.06
0.07 0.13
0.07 0.13
0.11 0.15
0.08 0.16
0.91 0.81 0.89 0.89 0.86 0.88 0.87 0.90
0.94 0.82 0.89 0.92 0.91 0.86 0.77 0.85
0.90 0.87 0.85 0.91 0.86 0.90 0.87 0.87
0.91 0.86 0.89 0.87 0.87 0.83 0.88 0.77
0.04 0.08 0.05 0.03 0.05 0.05 0.02 0.01
0.02 0.04 0.04 0.02 0.04 0.04 0.02 0.01
0.04 0.05 0.06 0.02 0.04 0.04 0.01 0.01
0.03 0.06 0.05 0.03 0.04 0.06 0.02 0.02
0.11 0.21 0.13 0.07 0.13 0.14 0.05 0.04
0.07 0.12 0.11 0.04 0.10 0.12 0.04 0.03
0.10 0.14 0.15 0.05 0.10 0.11 0.03 0.03
0.10 0.17 0.13 0.07 0.12 0.17 0.04 0.04
0.90 0.80 0.91 0.89 0.80 0.70 0.88
0.96 0.80 0.91 0.91 0.80 0.80 0.73
0.91 0.52 0.80 0.88 0.83 0.75 0.73
0.89 0.79 0.80 0.93 0.82 0.83 0.79
0.07 0.09 0.03 0.06 0.06 0.04 0.01
0.03 0.06 0.02 0.04 0.05 0.02 0.02
0.05 0.11 0.03 0.05 0.05 0.03 0.02
0.05 0.09 0.04 0.04 0.06 0.03 0.01
0.20 0.25 0.08 0.16 0.16 0.11 0.03
0.08 0.17 0.05 0.12 0.15 0.07 0.05
0.14 0.30 0.09 0.15 0.14 0.08 0.05
0.15 0.26 0.10 0.12 0.16 0.08 0.04
0.79 0.91 0.75
0.69 0.71 0.67
0.56 0.83 0.61
0.78 0.84 0.74
0.07 0.09 0.29
0.05 0.10 0.14
0.07 0.11 0.20
0.08 0.12 0.22
0.20 0.26 0.80
0.13 0.27 0.38
0.20 0.30 0.56
0.21 0.33 0.60
0.90 0.86 0.87 0.88
0.86 0.84 0.82 0.91
0.86 0.87 0.79 0.89
0.89 0.84 0.88 0.92
0.16 0.14 0.12 0.09
0.08 0.06 0.08 0.05
0.13 0.08 0.13 0.08
0.14 0.13 0.11 0.08
0.44 0.40 0.32 0.26
0.21 0.15 0.23 0.14
0.36 0.23 0.35 0.23
0.40 0.37 0.31 0.23
0.76 0.84 0.90
0.69 0.83 0.96
0.58 0.67 0.91
0.74 0.73 0.89
0.14 0.10 0.08
0.07 0.04 0.03
0.12 0.09 0.05
0.13 0.12 0.07
0.39 0.28 0.21
0.18 0.12 0.07
0.34 0.25 0.15
0.36 0.33 0.18
0.85
0.83
0.79
0.83
0.07
0.05
0.06
0.07
0.21
0.13
0.18
0.20
5. Conclusions In this study, the reliability and measurement error of several common gait measures was assessed by comparing between raters and over time in a healthy adult population. ICC values were in the good to excellent range, with no effect of rater or session. MDC values were lower than previously reported [1,13] with small differences between raters and sessions. Velocity had no effect on reliability for any gait variables and MDC values were consistent across velocities. Overall, this study demonstrates reliable assessment of gait performance can be achieved when using multiple raters and multiple sessions. This study also provides MDC values for individuals free from pathology, for comparison with future studies in patients. Acknowledgement Support provided by the Military Amputee Research Program (to JMW). Conflict of interest The authors have no conflict of interest to report. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.gaitpost.2011.09.105. References [1] Klejman S, Andrysek J, Dupuis A, Wright V. Test-retest reliability of discrete gait parameters in children with cerebral palsy. Arch Phys Med Rehabil 2010;91:781–7.
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