Journal of Electromyography and Kinesiology 24 (2014) 718–721
Contents lists available at ScienceDirect
Journal of Electromyography and Kinesiology journal homepage: www.elsevier.com/locate/jelekin
The reliability of biomechanical variables collected during single leg squat and landing tasks Faisal Alenezi a,b,⇑, Lee Herrington a, Paul Jones a, Richard Jones a a b
Knee Biomechanics and Injury Research Programme, School of Health Sciences, University of Salford, Manchester, United Kingdom General Directorate of Medical Rehabilitation, Ministry of Health, Riyadh, Saudi Arabia
a r t i c l e
i n f o
Article history: Received 29 April 2014 Received in revised form 26 June 2014 Accepted 8 July 2014
Keywords: Reliability Single leg squat Single leg landing Kinetic Kinematic
a b s t r a c t Introduction: The aim of this study was to determine the within- and between-day reliability of lower limb biomechanical variables collected during single leg squat (SLS) and single leg landing (SLL) tasks. Methods: 15 recreational athletes took part in three testing sessions, two sessions on the same day and another session one week later. Kinematic and kinetic data was gathered using a ten-camera movement analysis system (Qualisys) and a force platform (AMTI) embedded into the floor. Results: The combined averages of within-day ICC values (ICCSLS = 0.87; ICCSLL = 0.90) were higher than between-days (ICCSLS = 0.81; ICCSLL = 0.78). Vertical GRF values (ICCSLS = 0.90; ICCSLL = 0.98) were more reliable than joint angles (ICCSLS = 0.85; ICCSLL = 0.82) and moments (ICCSLS = 0.83; ICCSLL = 0.87). Discussion: This study demonstrates that all joint angles, moments, and vertical ground reaction force (GRF) variables obtained during both tasks showed good to excellent consistency with relatively low standard error of measurement values. These findings would be of relevance to practitioners who are using such measures for screening and prospective studies of rehabilitative techniques. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction The single-leg squat (SLS) and single leg landing (SLL) manoeuvres are frequently used tasks to assess lower alignment (Herrington, 2013; Nakagawa et al., 2014; Willy and Davis, 2011). Both have biomechanical and neuromuscular similarities to a wide range of athletic movements and thus are involved in rehabilitation programmes of different sports designed to prevent injuries and enhance athletic performance (Herrington, 2013; Willy and Davis, 2011; Willson et al., 2006; Myer et al., 2005). Given their widespread use, understanding the kinematic and kinetic variability of single leg squat and landing are essential to be able to discriminate between random error and real differences attributable to poor movement strategies or to interventions to change those movement strategies. Previous studies have undertaken assessments of reliability in SLS (Nakagawa et al., 2014; Whatman et al., 2011) and landings (Malfait et al., 2014; Milner et al., 2011; Ford et al., 2007). These previous studies have only investigated single elements of reliability (i.e. kinematics or kinetic data alone or within or between day reliability). In reviewing the literature, no study ⇑ Corresponding author at: P030 Brian Blatchford Building, University of Salford, Salford M6 6PU, United Kingdom. E-mail address: [email protected] (F. Alenezi). http://dx.doi.org/10.1016/j.jelekin.2014.07.007 1050-6411/Ó 2014 Elsevier Ltd. All rights reserved.
has looked at the within- and between-day reliability and associated measurement error of lower limb joint angles, moments and ground reaction force variables during SLS & SLL together in the same cohort. This information is important to evaluate previous and upcoming research, especially intervention studies, and also for practitioners who use these tasks to evaluate individual performance during training or rehabilitation. Without measurement error values, changes in performance cannot be evaluated properly as it is not known whether these changes may be attributed to the intervention or from measurement errors such as marker position, marker re-application, static alignment and tasks difficulty (Whatman et al., 2011; Malfait et al., 2014; Ford et al., 2007). The purpose of this study was to investigate the within- and between-day absolute and relative reliability of lower limb kinematic and kinetic variables collected during SLS and SLL maneuverers. 2. Materials and methods 2.1. Subjects Fifteen recreational athletes, 7 males (age 25 ± 6.4 years; height 171 ± 6.7 cm; mass 69.7 ± 10.7 kg) and 8 females (age 26 ± 3.5 years; height 163 ± 5.4 cm; mass 63 ± 8.0 kg) participated. Subjects
F. Alenezi et al. / Journal of Electromyography and Kinesiology 24 (2014) 718–721
were required to be free from lower limb injury for at least six months, and have no history of lower limb surgery. A recreational athlete was defined as participating in physical activity for at least 1 hour, three times a week. Ethical approval was given from the University Research and Governance committee and all participants gave informed consent. 2.2. Procedure A ten-camera motion analysis system (Pro-Reflex, Qualisys, Sweden), sampling at 240 Hz, and a force platform embedded into the floor (AMTI, USA), sampling at 1200 Hz, were used to collect kinematic and kinetic variables during the support phase of single leg squat and landing tasks. Each participant underwent two sessions on the same day with an hour break between, and another session one week later. Before testing, subjects were fitted with the standard training shoes (New Balance, UK) to control shoe-surface interface. Reflective markers (14 mm) were attached with self-adhesive tape to the participants’ lower extremities over the following landmarks; anterior superior iliac spines, posterior superior iliac spines, iliac crest, greater trochanters, medial and lateral femoral condyles, medial and lateral malleoli, posterior calcanei, and the head of the first, second and fifth metatarsals. The tracking markers were mounted on technical clusters on the thigh and shank with elastic bands. The foot markers were placed on the shoes, and the same individual placed the markers for all participants. That individual had undertaken over 10 supervised (by an expert in the field) marker application sessions prior to undertaking the project. The calibration anatomical systems technique (CAST) was employed to determine the six-degree of freedom movement of each segment and anatomical significance during the movement trials (Ford et al., 2007). The static trial position was designated as the subjects’ neutral (anatomical zero) alignment, and subsequent kinematic measures were related back to this position. The markers were removed and replaced for the within-session trials and obviously removed and replaced for the between-day trials. To orientate participants with the tasks, each subject was asked to perform 3–5 practice trials of each task before data collection. During SLS, subjects were instructed to stand on the right leg and hold the left leg in approximately of knee flexion without allowing the legs to contact each other, then start squatting down as far as they can (but no lower than a position of the thigh being parallel to the ground) and return to single leg stance without losing their balance. Consistent with the work of Zeller et al. Zeller et al. (2003), the squat depth was not controlled as this better represented a clinical setting in which normal inter-participant variability would exist. During practice trials, there was an acoustic counter for each participant over this 5-s period, in which the first count initiates the squat, the third indicates the deepest point of the squat and the fifth indicates the end (Herrington, 2013). This standardises the test for all participants, thereby reducing the effect of velocity on knee angles and movement pattern. In SLL, subjects landed down from a 30-cm step on their right leg onto a mark 10 cm from the bench. The effect of the arms was minimised by asking the subjects to keep their arms crossed against their chest. Participants were required to complete five successful trials for each task. 2.3. Data processing Visual3D motion (Version 4.21, C-Motion Inc. USA) was used to calculate the joint kinematic and kinetic data. Motion and force plate data were filtered using a Butterworth 4th order bi-directional low-pass filter with cut-off frequencies of 12 Hz and 25 Hz, respectively, with the cut-off frequencies based on a residual
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analysis (Yu et al., 1999). All lower extremity segments were modelled as conical frustra, with inertial parameters estimated from anthropometric data (Dempster, 1959). Kinematic and kinetic data were normalised to of the right leg descend phase during squat and landing. Joint kinematic data was calculated using an X–Y–Z Euler rotation sequence. Joint kinetic data were calculated using three-dimensional inverse dynamics, and the joint moment data were normalised to body mass and presented as external moments referenced to the proximal segment. External moments were described in this study, for example, an external knee valgus load will lead to abduct the knee (valgus position), and an external knee flexion load will tend to flex the knee (Malfait et al., 2014). The following discrete variables were calculated for each trial: peaks of vertical ground reaction force (vGRF), hip flexion and adduction moments, knee flexion and abduction moments, ankle dorsiflexion moment, and peaks of lower limb joint angles at frontal, Sagittal, & transverse planes. 2.4. Statistical analysis In order to assess the relative and absolute reliability, Intraclass correlation coefficients, model, was used in conjunction with Confidence Intervals and Standard error of measurement (SEM), with a significance value of P < 0.05. The ICC classification (less than 0.4 was poor, between 0.4 and 0.75 was fair to good, and greater than 0.75 is excellent) was used to describe the range of values (Fleiss, 1986). SEM was obtained by taking square root of the mean square error from the analysis of variance. 3. Results Tables 1 and 2 contain ICCs with (95% CI), means, and SEM values for lower limb kinematic and kinetic variables collected from SLS and SLL trials. The combined averages of within-day ICC values (ICCSLS = 0.87; ICCSLL = 0.90) were higher as compared to the between-days (ICCSLS = 0.81; ICCSLL = 0.78). Out of seven joint angles analysed in this study, within-day ICC values for all measures were excellent during both tasks (ICC P 0.78) apart from knee internal rotation during SLL which showed moderate reliability (ICC P 0.53). Between-day kinematic measures exhibited fair to excellent consistency with ICCs ranging from 0.48 to 0.96. Within- and between-day SEM values for joint angles ranged between (1.22°–4.16°) during SLS, while during SLL ranged between (1.00°–3.35°). During both tasks, sagittal and frontal planes moments exhibited excellent ICCs during within- and between-day (ICC P 0.75) apart from hip adduction in SLS (Within ICC = 0.63; between ICC = 0.73) and between day knee valgus moment in SLL (ICC = 0.69). Within- and between-day SEM values for joint moments ranged between (0.5–0.13 N m kg) during both tasks. The ICC values of vertical GRF data (ICCSLS P 0.89; ICCSLL P 0.97) were higher than kinetic and kinematic variables. 4. Discussion This study set out to assess the within- and between-day reliability of kinematic and kinetic variables during SLS and SLL tasks in recreational athletes. Previous studies have reported the reliability of only kinematic variables during similar but not identical tasks such squat and stepping (Nakagawa et al., 2014) drop vertical jump (Malfait et al., 2014), small knee bending (Whatman et al., 2011), & landing (Ford et al., 2007). With the single leg squat and landing being used in many screening programmes (Willy and Davis, 2011; Willson et al., 2006; Myer et al., 2005; Zeller et al., 2003; Dwyer et al., 2010), it is important to know how the variability in
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F. Alenezi et al. / Journal of Electromyography and Kinesiology 24 (2014) 718–721
Table 1 Within and between days ICC, Mean, and SEM values for 3D variables during SLS task. Variables
Within-day
Between-days
ICC (95% CI)
Mean
SEM
ICC (95% CI)
Mean
SEM
Joint angles (°) Hip adduction Hip flexion Hip int. rotation Knee valgus Knee flexion Knee int. rotation Dorsiflexion
0.93 0.95 0.85 0.92 0.97 0.78 0.97
(0.80 to 0.97) (0.84 to 0.98) (0.56 to 0.95) (0.76 to 0.97) (0.92 to 0.99) ( 0.33 to 0.93) (0.91 to 0.99)
15.81 68.88 6.69 6.66 92.56 7.25 43.12
1.72 4.16 1.5 1.35 2.44 1.22 1.24
0.94 0.88 0.61 0.48 0.88 0.75 0.96
(0.81 to 0.97) (0.63 to 0.96) ( 0.15 to 0.87) ( 0.55 to 0.83) (0.64 to 0.96) (0.25 to 0.92) (0.88 to 0.99)
15.55 69.43 6.53 6.34 93.06 7.05 43.46
1.50 3.77 1.56 1.07 2.16 1.49 1.22
Moments (N m/kg) Hip adduction Hip flexion Knee valgus Knee flexion Dorsiflexion VGRF (*bw)
0.63 0.93 0.80 0.94 0.86 0.92
( 0.08 to 0.88) (0.79 to 0.98) (0.39 to 0.93) (0.83 to 0.98) (0.59 to 0.95) (0.75 to 0.97)
1.17 0.84 0.43 1.98 1.10 1.13
0.09 0.13 0.06 0.06 0.05 0.01
0.73 0.87 0.77 0.95 0.82 0.89
(0.19 (0.63 (0.31 (0.85 (0.45 (0.69
1.12 0.85 0.41 1.96 1.08 1.12
0.06 0.11 0.06 0.06 0.05 0.01
to to to to to to
0.91) 0.96) 0.92) 0.98) 0.45) 0.97)
Table 2 Within and between days ICC, Mean, and SEM values for 3D variables during SLL task. Variables
Joint angles (°) Hip adduction Hip flexion Hip int. rotation Knee valgus Knee flexion Knee int. rotation Dorsiflexion Moments (N m/kg) Hip adduction Hip flexion Knee valgus Knee flexion Dorsiflexion Vertical GRF (*bw)
Within-day
Between-days
ICC (95% CI)
Mean
SEM
ICC (95% CI)
Mean
SEM
0.92 0.98 0.88 0.94 0.98 0.53 0.98
(0.76 to 0.97) (0.94 to 0.99) (0.64 to 0.56) (0.83 to 0.98) (0.93 to 0.99) ( 0.40 to 0.84) (0.94 to 0.99)
8.56 49.83 13.84 9.36 70.27 8.81 17.52
1.53 3.26 1.71 1.44 3.35 1.00 2.44
0.87 0.92 0.48 0.52 0.96 0.53 0.96
(0.61 to 0.96) (0.76 to 0.97) ( 0.55 to 0.825) ( 0.41 to 0.84) (0.87 to 0.99) ( 0.38 to 0.84) (0.88 to 0.99)
7.70 50.19 13.59 8.89 70.27 7.52 17.77
1.29 2.97 1.76 1.14 3.27 1.39 2.20
0.96 0.82 0.90 0.96 0.91 0.99
(0.89 (0.47 (0.69 (0.88 (0.72 (0.96
1.93 2.39 0.51 3.33 2.42 4.42
0.16 0.21 0.08 0.11 0.26 0.24
0.75 0.77 0.69 0.91 0.75 0.97
(0.25 (0.29 (0.06 (0.74 (0.25 (0.91
2.01 2.51 0.57 3.35 2.44 4.45
0.11 0.29 0.08 0.11 0.28 0.25
to to to to to to
0.988) 0.94) 0.96) 0.99) 0.97) 0.99)
this outcome associated with the subject’s performance and with the methodology employed. In the present investigation, the between-day ICC values for joint angles and moments were lower than within-day values. Other researchers have reported similar finding during single leg squat, stepping, and landing (Nakagawa et al., 2014; Ford et al., 2007). Several factors may have influenced both the within- and between-day reliability, such as skin marker movement, referenced static alignment (the initial starting angles may have introduced a slight offset in the data recorded), and task difficulty (Ford et al., 2007). Kadaba et al. (1989) attributed the variability of between-day measures to marker re-application. In this study, only one investigator attached the markers in all trials. The decreased between-day ICC values indicate that differences in marker replacement influenced the consistency even when controlling for the tester. However, to reduce this variability within this study, the CAST marker based protocol (Cappozzo et al., 1995) was used which has an advantage of offering improved anatomical relevance compared to the modified Helen Hayes marker set (Kadaba et al., 1989) and attempts to reduce skin movement artefact by attaching markers in the centre of the segments rather than close to the joints. In the present study, all subjects wore the same brand and type of running shoe as we believe this improved consistency of data, the marker position and relationship on the shoe remains constant, the degree of motion control applied to the foot remains constant, the friction between shoe and surface remains constant across all subjects.
to to to to to to
0.92) 0.92) 0.89) 0.97) 0.92) 0.99)
Vertical GRF data were less variable than joint angles or moments during both tasks (Tables 1 and 2), which is in line with previous findings (Kadaba et al., 1989; Winter, 1981). This result may be explained by the fact that the GRF values are the sum of all segmental masses, accelerations and gravitational forces. Thus, would be more reliable than joint kinematic or kinetic data (Winter, 1981). Moreover, the GRF values are an instant and are not derived from marker data and would therefore be assumed to be more repeatable. The SEM deliver information about the magnitude of the error associated with tests in order to distinguish real changes that occur as a result of intervention (Fleiss, 1986). Although the highest SEM values, in both tasks, were found with hip flexion angles (SLS = 4.16°; SLL = 3.26°) these represent less than 6.5% of the means (SLS = 68.8°; SLL = 49.8°). This may be explained by the larger range of motion in sagittal plane compared to other planes. The generalisability of these findings is subject to certain limitations. For instance, these results only apply to our laboratory settings and models, though consistent with those previously reported, these along with an individual’s ability to place markers could affect the results found in other laboratories. Moreover, the depth of the squat was not adequately controlled for each subject but this would reflect standard practice. Subjects were instructed to squat down on their right extremity as far as possible and return to a single- legged stand without losing their balance. A further limitation is the uninjured population that we examined but given the tests are used as screening tasks; it would be beneficial to
F. Alenezi et al. / Journal of Electromyography and Kinesiology 24 (2014) 718–721
investigators carrying out this research. The reliability of these functional tests in a population with a lower extremity injury, such as patellofemoral syndrome (PFPS), needs further investigation. Since the PFPS has been linked to excessive hip adduction and internal rotation, and knee external rotation during single leg squat and landing (Willson and Davis, 2008). 5. Conclusion The study undertaken demonstrates that all kinematic and kinetic variables obtained from healthy participants during single leg squat and landing tasks showed good to excellent consistency with relatively low values of standard error of measurement. These findings would be of relevance to practitioners who are using single legged squatting and landing as they establish the tasks reliability and level of measurement error for future screening and prospective studies for injury prevention and rehabilitation techniques.
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Winter DA. Kinematic and kinetic patterns in human gait: variability and compensating effects. Hum Movement Sci 1981:35–76. Yu B, Gabriel D, Noble L, An KN. Estimate of the optimum cutoff frequency for the Butterworth low-pass digital filter. J Appl Biomech 1999;15:318–29. Zeller BL, McCrory JL, Kibler WB, Uhl TL. Differences in kinematics and electromyographic activity between men and women during the singlelegged squat. Am J Sports Med 2003;31(3):449–56.
Faisal S. Alenezi is an MSc graduate and currently doing PhD in Sports Biomechanics at the University of Salford. His contact detail is Room PO30, Brian Blatchford Building, University of Salford, M6 6PU. His e-mail id is ‘‘[email protected]’’.
Conflict of interest None. Acknowledgment
Lee C. Herrington completed PhD and working as a senior lecturer in Sports Rehabilitation. His contact detail is Room C715, Allerton Building, Frederick Road, University of Salford M6 6PU. His e-mail id is ‘‘[email protected]’’.
Authors would like to thank Laura Smith and Steve Horton for their assistance during data collection. References Cappozzo A, Catani F, Della Croce U, Leardini A. Position and orientation in space of bones during movement: anatomical frame definition and determination. Clin Biomech 1995;10(4):171–8. Dempster W. Space requirements of the seated operator. In: WADC Technical Report 0hio: L Wright-Patterson Air Force Base; 1959. p. 55–159. Dwyer MK, Boudreau SN, Mattacola CG, Uhl TL, Lattermann C. Comparison of lower extremity kinematics and hip muscle activation during rehabilitation tasks between sexes. J Athl Training 2010;45(2):181. Fleiss JL. The design and analysis of clinical experiments. New York, NY: Wiley; 1986. Ford KR, Myer GD, Hewett TE. Reliability of landing 3D motion analysis: implications for longitudinal analyses. Med Sci Sports Exerc 2007;39(11):2021–8. Herrington L. Knee valgus angle during single leg squat and landing in patellofemoral pain patients and controls. Knee 2013;21(2):514–7. Kadaba MP, Ramakrishnan HK, Wootten ME, Gainey J, Gorton G, Cochran GVB. Repeatability of kinematic, kinetic, and electromyographic data in normal adult gait. J Orthop Res 1989;7(6):849–60. Malfait B, Sankey S, Azidin RM, Deschamps K, Vanrenterghem J, Robinson MA, et al. How reliable are lower limb kinematics and kinetics during a drop vertical jump. Med Sci Sports Exerc 2014;46(4):678–85. Milner CE, Westlake CG, Tate JJ. Test–retest reliability of knee biomechanics during stop jump landings. J Biomech 2011;44(9):1814–6. Myer GD, Ford KR, Palumbo OP, Hewett TE. Neuromuscular training improves performance and lower-extremity biomechanics in female athletes. J Strength Cond Res 2005;19(1):51–60. Nakagawa TH, Moriya ÉTU, Maciel CD, Serrão FV. Test–retest reliability of threedimensional kinematics using an electromagnetic tracking system during single-leg squat and stepping maneuver. Gait Posture 2014;39(1):141–6. Whatman C, Hing W, Hume P. Kinematics during lower extremity functional screening tests – are they reliable and related to jogging? Phys Ther Sport 2011;12(1):22–9. Willson JD, Davis IS. Lower extremity mechanics of females with and without patellofemoral pain across activities with progressively greater task demands. Clin Biomech 2008;23(2):203–11. Willson JD, Ireland ML, Davis I. Core strength and lower extremity alignment during single leg squats. Med Sci Sports Exerc 2006;38(5):945. Willy RW, Davis IS. The effect of a hip-strengthening program on mechanics during running and during a single-leg squat. J. Orthop Sports Phys Ther 2011;41(9):625.
Paul A. Jones completed PhD and working as a lecturer in Sports Biomechanics and Strength & Conditioning at the University of Salford. His contact detail is Room C702, Allerton Building, Frederick Road, University of Salford M6 6PU. His e-mail id is ‘‘[email protected]’’.
Richard K. Jones completed his PhD and working as a senior lecturer in Clinical Biomechanics at the University of Salford. His contact detail is Room PO18, Brian Blatchford Building, University of Salford, M6 6PU. His e-mail id is ‘‘[email protected]’’.
Contents lists available at ScienceDirect
Journal of Electromyography and Kinesiology journal homepage: www.elsevier.com/locate/jelekin
The reliability of biomechanical variables collected during single leg squat and landing tasks Faisal Alenezi a,b,⇑, Lee Herrington a, Paul Jones a, Richard Jones a a b
Knee Biomechanics and Injury Research Programme, School of Health Sciences, University of Salford, Manchester, United Kingdom General Directorate of Medical Rehabilitation, Ministry of Health, Riyadh, Saudi Arabia
a r t i c l e
i n f o
Article history: Received 29 April 2014 Received in revised form 26 June 2014 Accepted 8 July 2014
Keywords: Reliability Single leg squat Single leg landing Kinetic Kinematic
a b s t r a c t Introduction: The aim of this study was to determine the within- and between-day reliability of lower limb biomechanical variables collected during single leg squat (SLS) and single leg landing (SLL) tasks. Methods: 15 recreational athletes took part in three testing sessions, two sessions on the same day and another session one week later. Kinematic and kinetic data was gathered using a ten-camera movement analysis system (Qualisys) and a force platform (AMTI) embedded into the floor. Results: The combined averages of within-day ICC values (ICCSLS = 0.87; ICCSLL = 0.90) were higher than between-days (ICCSLS = 0.81; ICCSLL = 0.78). Vertical GRF values (ICCSLS = 0.90; ICCSLL = 0.98) were more reliable than joint angles (ICCSLS = 0.85; ICCSLL = 0.82) and moments (ICCSLS = 0.83; ICCSLL = 0.87). Discussion: This study demonstrates that all joint angles, moments, and vertical ground reaction force (GRF) variables obtained during both tasks showed good to excellent consistency with relatively low standard error of measurement values. These findings would be of relevance to practitioners who are using such measures for screening and prospective studies of rehabilitative techniques. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction The single-leg squat (SLS) and single leg landing (SLL) manoeuvres are frequently used tasks to assess lower alignment (Herrington, 2013; Nakagawa et al., 2014; Willy and Davis, 2011). Both have biomechanical and neuromuscular similarities to a wide range of athletic movements and thus are involved in rehabilitation programmes of different sports designed to prevent injuries and enhance athletic performance (Herrington, 2013; Willy and Davis, 2011; Willson et al., 2006; Myer et al., 2005). Given their widespread use, understanding the kinematic and kinetic variability of single leg squat and landing are essential to be able to discriminate between random error and real differences attributable to poor movement strategies or to interventions to change those movement strategies. Previous studies have undertaken assessments of reliability in SLS (Nakagawa et al., 2014; Whatman et al., 2011) and landings (Malfait et al., 2014; Milner et al., 2011; Ford et al., 2007). These previous studies have only investigated single elements of reliability (i.e. kinematics or kinetic data alone or within or between day reliability). In reviewing the literature, no study ⇑ Corresponding author at: P030 Brian Blatchford Building, University of Salford, Salford M6 6PU, United Kingdom. E-mail address: [email protected] (F. Alenezi). http://dx.doi.org/10.1016/j.jelekin.2014.07.007 1050-6411/Ó 2014 Elsevier Ltd. All rights reserved.
has looked at the within- and between-day reliability and associated measurement error of lower limb joint angles, moments and ground reaction force variables during SLS & SLL together in the same cohort. This information is important to evaluate previous and upcoming research, especially intervention studies, and also for practitioners who use these tasks to evaluate individual performance during training or rehabilitation. Without measurement error values, changes in performance cannot be evaluated properly as it is not known whether these changes may be attributed to the intervention or from measurement errors such as marker position, marker re-application, static alignment and tasks difficulty (Whatman et al., 2011; Malfait et al., 2014; Ford et al., 2007). The purpose of this study was to investigate the within- and between-day absolute and relative reliability of lower limb kinematic and kinetic variables collected during SLS and SLL maneuverers. 2. Materials and methods 2.1. Subjects Fifteen recreational athletes, 7 males (age 25 ± 6.4 years; height 171 ± 6.7 cm; mass 69.7 ± 10.7 kg) and 8 females (age 26 ± 3.5 years; height 163 ± 5.4 cm; mass 63 ± 8.0 kg) participated. Subjects
F. Alenezi et al. / Journal of Electromyography and Kinesiology 24 (2014) 718–721
were required to be free from lower limb injury for at least six months, and have no history of lower limb surgery. A recreational athlete was defined as participating in physical activity for at least 1 hour, three times a week. Ethical approval was given from the University Research and Governance committee and all participants gave informed consent. 2.2. Procedure A ten-camera motion analysis system (Pro-Reflex, Qualisys, Sweden), sampling at 240 Hz, and a force platform embedded into the floor (AMTI, USA), sampling at 1200 Hz, were used to collect kinematic and kinetic variables during the support phase of single leg squat and landing tasks. Each participant underwent two sessions on the same day with an hour break between, and another session one week later. Before testing, subjects were fitted with the standard training shoes (New Balance, UK) to control shoe-surface interface. Reflective markers (14 mm) were attached with self-adhesive tape to the participants’ lower extremities over the following landmarks; anterior superior iliac spines, posterior superior iliac spines, iliac crest, greater trochanters, medial and lateral femoral condyles, medial and lateral malleoli, posterior calcanei, and the head of the first, second and fifth metatarsals. The tracking markers were mounted on technical clusters on the thigh and shank with elastic bands. The foot markers were placed on the shoes, and the same individual placed the markers for all participants. That individual had undertaken over 10 supervised (by an expert in the field) marker application sessions prior to undertaking the project. The calibration anatomical systems technique (CAST) was employed to determine the six-degree of freedom movement of each segment and anatomical significance during the movement trials (Ford et al., 2007). The static trial position was designated as the subjects’ neutral (anatomical zero) alignment, and subsequent kinematic measures were related back to this position. The markers were removed and replaced for the within-session trials and obviously removed and replaced for the between-day trials. To orientate participants with the tasks, each subject was asked to perform 3–5 practice trials of each task before data collection. During SLS, subjects were instructed to stand on the right leg and hold the left leg in approximately of knee flexion without allowing the legs to contact each other, then start squatting down as far as they can (but no lower than a position of the thigh being parallel to the ground) and return to single leg stance without losing their balance. Consistent with the work of Zeller et al. Zeller et al. (2003), the squat depth was not controlled as this better represented a clinical setting in which normal inter-participant variability would exist. During practice trials, there was an acoustic counter for each participant over this 5-s period, in which the first count initiates the squat, the third indicates the deepest point of the squat and the fifth indicates the end (Herrington, 2013). This standardises the test for all participants, thereby reducing the effect of velocity on knee angles and movement pattern. In SLL, subjects landed down from a 30-cm step on their right leg onto a mark 10 cm from the bench. The effect of the arms was minimised by asking the subjects to keep their arms crossed against their chest. Participants were required to complete five successful trials for each task. 2.3. Data processing Visual3D motion (Version 4.21, C-Motion Inc. USA) was used to calculate the joint kinematic and kinetic data. Motion and force plate data were filtered using a Butterworth 4th order bi-directional low-pass filter with cut-off frequencies of 12 Hz and 25 Hz, respectively, with the cut-off frequencies based on a residual
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analysis (Yu et al., 1999). All lower extremity segments were modelled as conical frustra, with inertial parameters estimated from anthropometric data (Dempster, 1959). Kinematic and kinetic data were normalised to of the right leg descend phase during squat and landing. Joint kinematic data was calculated using an X–Y–Z Euler rotation sequence. Joint kinetic data were calculated using three-dimensional inverse dynamics, and the joint moment data were normalised to body mass and presented as external moments referenced to the proximal segment. External moments were described in this study, for example, an external knee valgus load will lead to abduct the knee (valgus position), and an external knee flexion load will tend to flex the knee (Malfait et al., 2014). The following discrete variables were calculated for each trial: peaks of vertical ground reaction force (vGRF), hip flexion and adduction moments, knee flexion and abduction moments, ankle dorsiflexion moment, and peaks of lower limb joint angles at frontal, Sagittal, & transverse planes. 2.4. Statistical analysis In order to assess the relative and absolute reliability, Intraclass correlation coefficients, model, was used in conjunction with Confidence Intervals and Standard error of measurement (SEM), with a significance value of P < 0.05. The ICC classification (less than 0.4 was poor, between 0.4 and 0.75 was fair to good, and greater than 0.75 is excellent) was used to describe the range of values (Fleiss, 1986). SEM was obtained by taking square root of the mean square error from the analysis of variance. 3. Results Tables 1 and 2 contain ICCs with (95% CI), means, and SEM values for lower limb kinematic and kinetic variables collected from SLS and SLL trials. The combined averages of within-day ICC values (ICCSLS = 0.87; ICCSLL = 0.90) were higher as compared to the between-days (ICCSLS = 0.81; ICCSLL = 0.78). Out of seven joint angles analysed in this study, within-day ICC values for all measures were excellent during both tasks (ICC P 0.78) apart from knee internal rotation during SLL which showed moderate reliability (ICC P 0.53). Between-day kinematic measures exhibited fair to excellent consistency with ICCs ranging from 0.48 to 0.96. Within- and between-day SEM values for joint angles ranged between (1.22°–4.16°) during SLS, while during SLL ranged between (1.00°–3.35°). During both tasks, sagittal and frontal planes moments exhibited excellent ICCs during within- and between-day (ICC P 0.75) apart from hip adduction in SLS (Within ICC = 0.63; between ICC = 0.73) and between day knee valgus moment in SLL (ICC = 0.69). Within- and between-day SEM values for joint moments ranged between (0.5–0.13 N m kg) during both tasks. The ICC values of vertical GRF data (ICCSLS P 0.89; ICCSLL P 0.97) were higher than kinetic and kinematic variables. 4. Discussion This study set out to assess the within- and between-day reliability of kinematic and kinetic variables during SLS and SLL tasks in recreational athletes. Previous studies have reported the reliability of only kinematic variables during similar but not identical tasks such squat and stepping (Nakagawa et al., 2014) drop vertical jump (Malfait et al., 2014), small knee bending (Whatman et al., 2011), & landing (Ford et al., 2007). With the single leg squat and landing being used in many screening programmes (Willy and Davis, 2011; Willson et al., 2006; Myer et al., 2005; Zeller et al., 2003; Dwyer et al., 2010), it is important to know how the variability in
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Table 1 Within and between days ICC, Mean, and SEM values for 3D variables during SLS task. Variables
Within-day
Between-days
ICC (95% CI)
Mean
SEM
ICC (95% CI)
Mean
SEM
Joint angles (°) Hip adduction Hip flexion Hip int. rotation Knee valgus Knee flexion Knee int. rotation Dorsiflexion
0.93 0.95 0.85 0.92 0.97 0.78 0.97
(0.80 to 0.97) (0.84 to 0.98) (0.56 to 0.95) (0.76 to 0.97) (0.92 to 0.99) ( 0.33 to 0.93) (0.91 to 0.99)
15.81 68.88 6.69 6.66 92.56 7.25 43.12
1.72 4.16 1.5 1.35 2.44 1.22 1.24
0.94 0.88 0.61 0.48 0.88 0.75 0.96
(0.81 to 0.97) (0.63 to 0.96) ( 0.15 to 0.87) ( 0.55 to 0.83) (0.64 to 0.96) (0.25 to 0.92) (0.88 to 0.99)
15.55 69.43 6.53 6.34 93.06 7.05 43.46
1.50 3.77 1.56 1.07 2.16 1.49 1.22
Moments (N m/kg) Hip adduction Hip flexion Knee valgus Knee flexion Dorsiflexion VGRF (*bw)
0.63 0.93 0.80 0.94 0.86 0.92
( 0.08 to 0.88) (0.79 to 0.98) (0.39 to 0.93) (0.83 to 0.98) (0.59 to 0.95) (0.75 to 0.97)
1.17 0.84 0.43 1.98 1.10 1.13
0.09 0.13 0.06 0.06 0.05 0.01
0.73 0.87 0.77 0.95 0.82 0.89
(0.19 (0.63 (0.31 (0.85 (0.45 (0.69
1.12 0.85 0.41 1.96 1.08 1.12
0.06 0.11 0.06 0.06 0.05 0.01
to to to to to to
0.91) 0.96) 0.92) 0.98) 0.45) 0.97)
Table 2 Within and between days ICC, Mean, and SEM values for 3D variables during SLL task. Variables
Joint angles (°) Hip adduction Hip flexion Hip int. rotation Knee valgus Knee flexion Knee int. rotation Dorsiflexion Moments (N m/kg) Hip adduction Hip flexion Knee valgus Knee flexion Dorsiflexion Vertical GRF (*bw)
Within-day
Between-days
ICC (95% CI)
Mean
SEM
ICC (95% CI)
Mean
SEM
0.92 0.98 0.88 0.94 0.98 0.53 0.98
(0.76 to 0.97) (0.94 to 0.99) (0.64 to 0.56) (0.83 to 0.98) (0.93 to 0.99) ( 0.40 to 0.84) (0.94 to 0.99)
8.56 49.83 13.84 9.36 70.27 8.81 17.52
1.53 3.26 1.71 1.44 3.35 1.00 2.44
0.87 0.92 0.48 0.52 0.96 0.53 0.96
(0.61 to 0.96) (0.76 to 0.97) ( 0.55 to 0.825) ( 0.41 to 0.84) (0.87 to 0.99) ( 0.38 to 0.84) (0.88 to 0.99)
7.70 50.19 13.59 8.89 70.27 7.52 17.77
1.29 2.97 1.76 1.14 3.27 1.39 2.20
0.96 0.82 0.90 0.96 0.91 0.99
(0.89 (0.47 (0.69 (0.88 (0.72 (0.96
1.93 2.39 0.51 3.33 2.42 4.42
0.16 0.21 0.08 0.11 0.26 0.24
0.75 0.77 0.69 0.91 0.75 0.97
(0.25 (0.29 (0.06 (0.74 (0.25 (0.91
2.01 2.51 0.57 3.35 2.44 4.45
0.11 0.29 0.08 0.11 0.28 0.25
to to to to to to
0.988) 0.94) 0.96) 0.99) 0.97) 0.99)
this outcome associated with the subject’s performance and with the methodology employed. In the present investigation, the between-day ICC values for joint angles and moments were lower than within-day values. Other researchers have reported similar finding during single leg squat, stepping, and landing (Nakagawa et al., 2014; Ford et al., 2007). Several factors may have influenced both the within- and between-day reliability, such as skin marker movement, referenced static alignment (the initial starting angles may have introduced a slight offset in the data recorded), and task difficulty (Ford et al., 2007). Kadaba et al. (1989) attributed the variability of between-day measures to marker re-application. In this study, only one investigator attached the markers in all trials. The decreased between-day ICC values indicate that differences in marker replacement influenced the consistency even when controlling for the tester. However, to reduce this variability within this study, the CAST marker based protocol (Cappozzo et al., 1995) was used which has an advantage of offering improved anatomical relevance compared to the modified Helen Hayes marker set (Kadaba et al., 1989) and attempts to reduce skin movement artefact by attaching markers in the centre of the segments rather than close to the joints. In the present study, all subjects wore the same brand and type of running shoe as we believe this improved consistency of data, the marker position and relationship on the shoe remains constant, the degree of motion control applied to the foot remains constant, the friction between shoe and surface remains constant across all subjects.
to to to to to to
0.92) 0.92) 0.89) 0.97) 0.92) 0.99)
Vertical GRF data were less variable than joint angles or moments during both tasks (Tables 1 and 2), which is in line with previous findings (Kadaba et al., 1989; Winter, 1981). This result may be explained by the fact that the GRF values are the sum of all segmental masses, accelerations and gravitational forces. Thus, would be more reliable than joint kinematic or kinetic data (Winter, 1981). Moreover, the GRF values are an instant and are not derived from marker data and would therefore be assumed to be more repeatable. The SEM deliver information about the magnitude of the error associated with tests in order to distinguish real changes that occur as a result of intervention (Fleiss, 1986). Although the highest SEM values, in both tasks, were found with hip flexion angles (SLS = 4.16°; SLL = 3.26°) these represent less than 6.5% of the means (SLS = 68.8°; SLL = 49.8°). This may be explained by the larger range of motion in sagittal plane compared to other planes. The generalisability of these findings is subject to certain limitations. For instance, these results only apply to our laboratory settings and models, though consistent with those previously reported, these along with an individual’s ability to place markers could affect the results found in other laboratories. Moreover, the depth of the squat was not adequately controlled for each subject but this would reflect standard practice. Subjects were instructed to squat down on their right extremity as far as possible and return to a single- legged stand without losing their balance. A further limitation is the uninjured population that we examined but given the tests are used as screening tasks; it would be beneficial to
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investigators carrying out this research. The reliability of these functional tests in a population with a lower extremity injury, such as patellofemoral syndrome (PFPS), needs further investigation. Since the PFPS has been linked to excessive hip adduction and internal rotation, and knee external rotation during single leg squat and landing (Willson and Davis, 2008). 5. Conclusion The study undertaken demonstrates that all kinematic and kinetic variables obtained from healthy participants during single leg squat and landing tasks showed good to excellent consistency with relatively low values of standard error of measurement. These findings would be of relevance to practitioners who are using single legged squatting and landing as they establish the tasks reliability and level of measurement error for future screening and prospective studies for injury prevention and rehabilitation techniques.
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Winter DA. Kinematic and kinetic patterns in human gait: variability and compensating effects. Hum Movement Sci 1981:35–76. Yu B, Gabriel D, Noble L, An KN. Estimate of the optimum cutoff frequency for the Butterworth low-pass digital filter. J Appl Biomech 1999;15:318–29. Zeller BL, McCrory JL, Kibler WB, Uhl TL. Differences in kinematics and electromyographic activity between men and women during the singlelegged squat. Am J Sports Med 2003;31(3):449–56.
Faisal S. Alenezi is an MSc graduate and currently doing PhD in Sports Biomechanics at the University of Salford. His contact detail is Room PO30, Brian Blatchford Building, University of Salford, M6 6PU. His e-mail id is ‘‘[email protected]’’.
Conflict of interest None. Acknowledgment
Lee C. Herrington completed PhD and working as a senior lecturer in Sports Rehabilitation. His contact detail is Room C715, Allerton Building, Frederick Road, University of Salford M6 6PU. His e-mail id is ‘‘[email protected]’’.
Authors would like to thank Laura Smith and Steve Horton for their assistance during data collection. References Cappozzo A, Catani F, Della Croce U, Leardini A. Position and orientation in space of bones during movement: anatomical frame definition and determination. Clin Biomech 1995;10(4):171–8. Dempster W. Space requirements of the seated operator. In: WADC Technical Report 0hio: L Wright-Patterson Air Force Base; 1959. p. 55–159. Dwyer MK, Boudreau SN, Mattacola CG, Uhl TL, Lattermann C. Comparison of lower extremity kinematics and hip muscle activation during rehabilitation tasks between sexes. J Athl Training 2010;45(2):181. Fleiss JL. The design and analysis of clinical experiments. New York, NY: Wiley; 1986. Ford KR, Myer GD, Hewett TE. Reliability of landing 3D motion analysis: implications for longitudinal analyses. Med Sci Sports Exerc 2007;39(11):2021–8. Herrington L. Knee valgus angle during single leg squat and landing in patellofemoral pain patients and controls. Knee 2013;21(2):514–7. Kadaba MP, Ramakrishnan HK, Wootten ME, Gainey J, Gorton G, Cochran GVB. Repeatability of kinematic, kinetic, and electromyographic data in normal adult gait. J Orthop Res 1989;7(6):849–60. Malfait B, Sankey S, Azidin RM, Deschamps K, Vanrenterghem J, Robinson MA, et al. How reliable are lower limb kinematics and kinetics during a drop vertical jump. Med Sci Sports Exerc 2014;46(4):678–85. Milner CE, Westlake CG, Tate JJ. Test–retest reliability of knee biomechanics during stop jump landings. J Biomech 2011;44(9):1814–6. Myer GD, Ford KR, Palumbo OP, Hewett TE. Neuromuscular training improves performance and lower-extremity biomechanics in female athletes. J Strength Cond Res 2005;19(1):51–60. Nakagawa TH, Moriya ÉTU, Maciel CD, Serrão FV. Test–retest reliability of threedimensional kinematics using an electromagnetic tracking system during single-leg squat and stepping maneuver. Gait Posture 2014;39(1):141–6. Whatman C, Hing W, Hume P. Kinematics during lower extremity functional screening tests – are they reliable and related to jogging? Phys Ther Sport 2011;12(1):22–9. Willson JD, Davis IS. Lower extremity mechanics of females with and without patellofemoral pain across activities with progressively greater task demands. Clin Biomech 2008;23(2):203–11. Willson JD, Ireland ML, Davis I. Core strength and lower extremity alignment during single leg squats. Med Sci Sports Exerc 2006;38(5):945. Willy RW, Davis IS. The effect of a hip-strengthening program on mechanics during running and during a single-leg squat. J. Orthop Sports Phys Ther 2011;41(9):625.
Paul A. Jones completed PhD and working as a lecturer in Sports Biomechanics and Strength & Conditioning at the University of Salford. His contact detail is Room C702, Allerton Building, Frederick Road, University of Salford M6 6PU. His e-mail id is ‘‘[email protected]’’.
Richard K. Jones completed his PhD and working as a senior lecturer in Clinical Biomechanics at the University of Salford. His contact detail is Room PO18, Brian Blatchford Building, University of Salford, M6 6PU. His e-mail id is ‘‘[email protected]’’.
