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Gait characteristics of children with cerebral palsy as they walk with body weight unloading on a treadmill and over the ground
Research in Developmental Disabilities 35 (2014) 3624–3631
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Research in Developmental Disabilities
Gait characteristics of children with cerebral palsy as they walk with body weight unloading on a treadmill and over the ground Melissa L. Celestino, Gabriela L. Gama, Ana M.F. Barela * Graduate Program in Human Movement Sciences, Institute of Physical Activity and Sport Sciences, Cruzeiro do Sul University, Brazil
A R T I C L E I N F O
A B S T R A C T
Article history: Received 3 June 2014 Received in revised form 31 August 2014 Accepted 2 September 2014 Available online
Body weight support (BWS) has become a typical strategy for gait training, in special with children with cerebral palsy (CP). Although several findings have been reported in the literature, it remains uncertain how different types of surfaces and gradual amount of BWS can facilitate the mobility of children with CP. The aim of this study was to investigate gait kinematic parameters of children with CP by manipulating BWS and two different types of ground surfaces. Ten children (7.7 2.1 years old) diagnosed with spastic CP and GMFCS classification between levels II and IV were asked to walk on a treadmill and over the ground. In both conditions, BWS was manipulated to minimize gravitational effects and spatial– temporal gait parameters and lower limb joints were analyzed. The results revealed that the type of ground surface causes greater impact on the gait pattern of children with CP as compared to body weight unloading. This finding may provide new insights into the behavioral heterogeneity of children with CP, and offers critical information to be considered on interventional programs specifically designed to improve mobility on this population. ß 2014 Elsevier Ltd. All rights reserved.
Keywords: Body weight support system Spatial–temporal parameters Joint angles
1. Introduction While gait is an activity that most of us take for granted, it is a motor skill that requires an optimal pattern of motor coordination and involves complex control mechanisms (Inman, Ralston, & Todd, 1994; Winter, 1991). The optimal performance level might be specified by the interaction of three different categories of constraints (Newell, 1986): organism, including structural features (e.g., body mass and height) and functional features (e.g., synaptic connections); environment (e.g., gravity, ambient temperature, natural light, cultural backgrounds); and task, including goals of the task and rules and implements specifying response dynamics. Constraints are considered as boundaries that limit an individual’s motion at the same time that lead to alternative patterns of movement coordination and control; even if a movement is performed under the same set of environmental and task constraints. CP has been described as a group of disorders of the development of movement and posture that are permanent and cause activity limitation, and are attributed to non-progressive disturbances that occurred in the developing fetal or infant brain (Rosenbaum, Paneth, Leviton, Goldstein, & Bax, 2007). The effect of CP on functional abilities varies greatly. Some people are
* Corresponding author at: Rua Galva˜o Bueno, 868, 138 andar, Bloco B, 01506-000 Sa˜o Paulo, SP, Brazil. Tel.: +55 11 3385 3103. E-mail addresses: [email protected], [email protected] (Ana M.F. Barela). http://dx.doi.org/10.1016/j.ridd.2014.09.002 0891-4222/ß 2014 Elsevier Ltd. All rights reserved.
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able to walk while others are not. Some people show normal to near typical intellectual function, but others may have intellectual disabilities. Its motor severity is generally classified according to the Gross Motor Function Classification System (GMFCS) (Palisano et al., 1997; Palisano, Rosenbaum, Bartlett, & Livingston, 2008). Among several movement deficiencies, the gait impairment is one of the major concerns for parents and caregivers. According to Chang, Rhodes, Flynn, and Carollo (2010), the gait impairment is due to spasticity (or abnormal muscle tone), reduced motor control ability and impaired balance. As these children grow with no simultaneous lengthening of skeletal muscles, muscular tightness and muscle contractures, they eventually develop bony torsion. Consequently, children with CP on ambulatory condition usually present a decline in gait function over time (Bell, Ounpuu, DeLuca, & Romness, 2002; Johnson, Damiano, & Abel, 1997; Norlin & Odenrick, 1986). To overcome the inability to typically develop gait movement patterns, different categories of treatment have been proposed and investigated, including therapeutic interventions and neuromuscular invasive techniques. For instance, the use of body weight support (BWS) is a typical therapeutic intervention technique that provides taskspecific gait training. The rationale for using the BWS system is that the reduction of gravitational forces would reduce the load that should be overcome by the individual; facilitating the walking constraints. Consequently, this strategy might promote a gait pattern close to typical (Finch, Barbeau, & Arsenault, 1991). In general, the BWS systems consist of a mounting frame and a harness to support a percentage of the individual’s weight as s/he walks on a motorized treadmill (MatternBaxter, 2009; Mutlu, Krosschell, & Spira, 2009). The use of a treadmill is usually adopted to stimulates rhythmical and repetitive steps (Visintin, Barbeau, Korner-Bitensky, & Mayo, 1998). In addition, the treadmill belt triggers interlimb symmetry causing positive effects on the temporal parameters of walking (Harris-Love, Macko, Whitall, & Forrester, 2004), as well as diminishing the need for propulsive force generation at the end of the stance period (Norman, Pepin, Ladouceur, & Barbeau, 1995). More recently, the BWS systems have been employed during over ground walking in individuals with stroke (Lamontagne & Fung, 2004; Miller, Quinn, & Seddon, 2002; Prado-Medeiros et al., 2011; Sousa, Barela, Prado-Medeiros, Salvini, & Barela, 2009; Sousa, Barela, Prado-Medeiros, Salvini, & Barela, 2011) and children with CP (Matsuno, Camargo, Palma, Alveno, & Barela, 2010). However, to the best of our knowledge, it remains unclear whether the type of surface and/or the amount of body weight unloaded could influence the way that children with CP walk. This study was designed to investigate gait kinematic parameters of children with CP by manipulating BWS and two different types of ground surfaces (treadmill and over ground). 2. Methods 2.1. Participants Ten children (7.7 2.1 years old) diagnosed with spastic CP and GMFCS classification between levels II and IV were selected to participate in this study (Table 1). The inclusion criteria also account for the individual’s ability to walk approximately 7 m with or without assistance, and to understand the experimental instructions and procedures. Fourteen children were initially recruited and assessed. However, data from four participants were excluded due to experimental difficulties encountered either during data acquisition (n = 2) or data processing (n = 2). Prior to participation, each child’s parent or legal guardian provided informed consent. All experimental procedures were approved by the Institutional Review Board at the University of Cruzeiro do Sul, Sao Paulo, Brazil (Protocol 020/2010). 2.2. Procedures The children were asked to walk at a comfortable speed along a walkway (7 m) and on a treadmill under three different conditions: walking wearing a harness and bearing full body weight (‘‘0% BWS’’ condition); walking wearing a harness and 15% of full body weight unloaded (‘‘15% BWS’’ condition); and walking wearing a harness and 30% of full body weight Table 1 General information about the children considered in the final sample. ID
Sex
Age (years)
Mass (kg)
Height (cm)
Diagnosis
GMFCS
1 2 3 4 5 6 7 8 9 10 Mean SD
F M M F F F M M F F – –
9.3 8.3 9.5 3.2 7.8 7.5 8.9 8.6 4.9 9 7.7 2.1
19.7 23.8 25.3 13.1 34.5 30.0 30.7 23.2 15.5 19.1 23.5 6.9
123 132 130 93 138 108 122 136 110 104 119.6 15.1
Diplegia Diplegia Diplegia Diplegia Hemiplegia Diplegia Diplegia Diplegia Diplegia Hemiplegia – –
III II II III III IV III III IV II – –
Abbreviation: ID, child’s identification; GMFCS, Gross Motor Function Classification System (Palisano et al., 1997).
[(Fig._1)TD$IG]
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Fig. 1. Representation of the customized body weight support system, illustrating the suspended rail, moving cart and the two electrical servo motors, load cell, drivers and computer that control the displacement, velocity and acceleration of the moving cart, and the harness. Note: more details are described in the text.
unloaded (‘‘30% BWS’’ condition). Fig. 1 exemplifies the customized BWS system (Finix Tecnologia). The system consists of a suspended rail (7 m) mounted on the ceiling (3 m height) and sustained by two steel beams. A moving cart is attached to the bottom of the rail allowing for backward and forward movements and controlled by a belt system linked to a servo motor. A customized program (LabView 2011, National Instruments Inc.) was developed to control displacement, velocity and acceleration of the moving cart. In addition, the moving cart was controlled by a second servo motor that controlled the mechanical body weight supported provided by the harness. An instrumented load cell registered the body weight and allowed for weight unload manipulation. To accurately unload the individual’s body weight according to the desired experimental conditions, participants were asked to stay still until the belt’s length was properly adjusted. A computerized gait analysis system (VICON Bonita 10) with seven infrared cameras was used to measure kinematic data. Based on the Vicon Plug-In Gait model (Vicon, 2010), reflective markers were placed on the sacrum, and bilaterally on the anterior superior iliac crest, the midpoint of the lateral femur, the lateral knee joint axis, the midpoint of the lateral tibia, the lateral malleolus, the calcaneus and the second metatarsal head. This reference point system has been broadly adoptee by previous studies (e.g., Benedetti, Manca, Ferraresi, Boschi, & Leardini, 2011; Bohm & Doderlein, 2012). A calibration trial was conducted prior to testing. Each participant stood upright to record the neutral position (baseline) of all joints and segments. All participants were asked to walk barefoot at a self-determined speed, which was kept the same for all experimental conditions. Before data acquisition, all children practiced for a few trials until they felt comfortable with the mechanical device and the lab environment. Three trials, minimum, were recorded for each experimental condition. The experimental conditions were properly randomized within and across individuals. 2.3. Data processing One intermediate stride per trial by each child, for a total of three selected trials for each condition, was analyzed. The trial selection was determined by the best visualization of the markers as the children walked with no interruption. Through visual inspection, a stride (walking cycle) was defined by two consecutive initial contacts of the same limb with the ground along the progression line. In addition, walking events during a stride were identified for subsequent calculation of the temporal organization of walking, such as initial and terminal double stance, single limb support and swing period (Perry, 1992). This procedure was carried out for both right and left sides of the body. Joint and segmental angles were processed with Vicon Nexus software (version 1.8.5). Subsequent analyses were performed using Matlab software (MathWorks, Inc.). For joint and segmental angles, strides were normalized in time from 0% to 100% with a 1% step. These cycles were referred to the children’s neutral angles measured during the calibration trial in each condition and were then averaged to obtain the mean cycle for each participant. The same procedure was repeated to obtain the mean cycle among participants. The outcome measures analyzed in this study were: stride length (distance between two successive initial contacts of the same foot to the surface, determined by the position of the calcaneus), speed (calculated as the ratio between stride length and duration), durations of total double stance and single limb support, maximum angles of pelvis (posterior tilt), hip (extension), knee (extension) and ankle (plantar flexion) and minimum angles of pelvis (anterior tilt), hip (flexion), knee (flexion) and ankle (dorsiflexion) at the sagittal plane during each stride. Data from right and left sides were averaged together before making comparisons among different experimental conditions. 2.4. Statistical analysis For all variables, data from three trials under each condition were averaged for each child. Multivariate analyses of variance (MANOVAs) for repeated measures were employed, using surface (treadmill and over ground) and body weight unloading (0%, 15% and 30%) as factors. The dependent variables were stride length and stride speed for the first MANOVA;
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Table 2 Mean (SD) values of the spatial–temporal parameters of walking during the stride cycle according to surface and body weight support (BWS). Outcome measures/surface
BWS 0%
p value 15%
Stride length (m) Over ground Treadmill
0.56 (0,17) 0.60 (0.23)
0.60 (0.18) 0.57 (0.21)
Stride speed (m/s) Over ground Treadmill
0.44 (0.19) 0.47 (0.17)
0.45 (0.19) 0.45 (0.17)
30%
Surface
BWS
Surface*BWS
0.61 (0.17) 0.56 (0.22)
0.743
0.905
0.028
0.46 (0.18) 0.42 (0.18)
0.877
0.585
0.001
Total double stance (%) Over ground Treadmill
34 (7.4) 42 (5.4)
37 (5.5) 40 (5.4)
31 (7.6) 39 (6.7)
0.002
0.075
0.480
Single limb support (%) Over ground Treadmill
32 (6.7) 23 (2.5)
27 (4.4) 25 (2.4)
31 (6.6) 24 (4.2)
0.005
0.378
0.065
total double stance and single limb support for the second MANOVA; maximum angles of pelvis, hip, knee and ankle for the third MANOVA; and minimum angles of pelvis, hip, knee and ankle for the fourth MANOVA. When necessary, univariate analyses, comparisons with Bonferroni adjustments and Tukey post hoc tests were employed as necessary. Alpha level of 0.05 was adopted. All analyses were performed using the Statistical Package for Social Sciences software. 3. Results Each child walked at the same mean speed in all conditions. The speed ranged from 0.29 to 0.83 (0.43, SD 0.19) m/s. Table 2 depicts mean (SD) values of walking cycle’s spatial–temporal parameters. MANOVA for stride length and speed revealed interaction between the surface and BWS (Wilks’ Lambda = 0.42, F4,34 = 4.65, p < 0.005). The univariate analysis revealed interaction between the surface and BWS for stride length (F2,18 = 4.37) and stride speed (F2,18 = 10.14). Tukey post hoc test revealed that only stride speed was lower when children walked with 30% BWS compared to 0% BWS on a treadmill. MANOVA for durations of total double stance and single limb support revealed a surface effect only (Wilks’ Lambda = 0.30, F2,8 = 9.40, p = 0.008). The univariate analysis revealed that children presented shorter double stance (F1,9 = 17.69) and longer single limb support (F1,9 = 13.99) when they walked over ground compared to on a treadmill (Table 2). Fig. 2 illustrates the mean (SD) values gait cycles of pelvis, hip, knee and ankle angles in the sagittal plane of all children as they walked on both surfaces with 0%, 15% and 30% BWS. Qualitatively, the pelvis and all joints seemed to have roughly similar patterns in all conditions. Anterior and posterior pelvic tilt, hip and knee flexion and extension, and ankle dorsiflexion and plantar flexion were present in all conditions. Table 3 depicts mean (SD) values of minimum and maximum angles for pelvis, hip, knee and ankle joints during the gait cycle in all conditions. For minimum angles, MANOVA revealed an effect only for the surface (Wilks’ Lambda = 0.06, F4,6 = 22.68, p = 001). Univariate analyses revealed that children presented less pelvic posterior tilt (F1,9 = 7.67), hip extension (F1,9 = 7.92), knee extension (F1,9 = 14.52) and ankle plantar flexion (F1,9 = 13.57) when walking over ground compared to on a treadmill (Table 3). For maximum angles, MANOVA revealed an effect for surface (Wilks’ Lambda = 0.13, F4,6 = 9.73, p = 0.009), and a tendency for BWS (Wilks’ Lambda = 0.39, F8,30 = 2.24, p = 0.52). Univariate analyses for surface revealed that children presented less pelvic anterior tilt (F1,9 = 7.92) and hip flexion (F1,9 = 16.18) when walking over ground compared to on a treadmill. Univariate analyses for BWS revealed differences for pelvic anterior tilt (F2,18 = 5.23), hip flexion (F2,18 = 5.47) and ankle dorsiflexion (F2,18 = 9.23). Comparisons with Bonferroni adjustment revealed that children presented higher excursion for pelvis, hip and ankle with 0% BWS compared to 30% BWS, and higher excursion for ankle with 15% BWS compared to 30% BWS (Table 3). 4. Discussion The aim of this study was to investigate gait kinematic parameters of children with CP by manipulating BWS and two different types of ground surfaces. Overall, the results revealed that ground surfaces caused greater impact on gait patterns of children with CP as compared to body weight unloading. Interestingly, even the children who could not walk independently were able to walk with a BWS system on both surfaces. Specifically, it was found that ground surface affected individual’s total double stance, single limb support, minimum angles of pelvis, hip, knee and ankle and maximum angles of pelvis and hip, suggesting that walking over the ground promoted a gait pattern more similar to their typically developing peers. The body weight unloading affected the maximum angles of the pelvis, hip and ankle on both surfaces and stride speed on treadmill, suggesting that children with CP had difficulties overcoming the gravitational forces.
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Fig. 2. Mean (SD) stride cycles of pelvis (A, E, I), hip (B, F, J), knee (C, G, K) and ankle (D, H, L) in the sagittal plane for the children with cerebral palsy as they walked with 0% BWS (left panel), 15% BWS (middle panel) and 30% BWS (right panel) on a treadmill (gray area) and over ground (line).
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Table 3 Mean (SD) values of pelvis and joint angles (degrees) during the stride cycle according to surface and body weight support (BWS). Outcome measures/surface
BWS 0%
Pelvic posterior tilt Over ground Treadmill Hip extension Over ground Treadmill
p value 15%
10 (7) 13 (8)
9 (8) 11 (7)
30%
Surface
BWS
Surface*BWS
9 (9) 10 (10)
0.022
0.087
0.527
2 (10) 7 (12)
2 (10) 5 (10)
3 (11) 6 (11)
0.020
0.105
0.353
Knee extension Over ground Treadmill
14 (13) 19 (15)
15 (14) 18 (13)
15 (13) 18 (13)
0.004
0.658
0.478
Ankle plantar flexion Over ground Treadmill
21 (25) 13 (17)
21 (18) 17 (18)
22 (22) 21 (22)
0.005
0.953
0.297
Pelvic anterior tilt Over ground Treadmill
19 (6) 22 (10)
18 (7) 20 (7)
18 (8) 19 (8)
0.020
0.016
0.248
Hip flexion Over ground Treadmill
42 (11) 49 (14)
42 (13) 44 (12)
42 (14) 43 (13)
0.003
0.014
0.199
Knee flexion Over ground Treadmill
59 (24) 62 (30)
61 (26) 57 (19)
61 (25) 58 (25)
0.383
0.884
0.498
Ankle dorsiflexion Over ground Treadmill
19 (11) 23 (12)
19 (16) 17 (12)
14 (9) 19 (15)
0.182
0.002
0.290
Different from previous findings (Matsuno et al., 2010), similar stride length was observed in all experimental conditions. This might be attributed to the mean walking speed that is known as a critical parameter that affect the gait pattern (Winter, 1991). On the other hand, the children in this study presented greater instability while walking on a treadmill as compared to walking over the ground. This finding was supported by higher double stance duration and lower single limb support duration, respectively. For instance, it was observed that by increasing the base of support (both feet on the ground), balance and stability also increased. The children with CP took longer strides (keeping both feet in contact with the treadmill) as strategy to ensure greater walking stability. Furthermore, the tested children were more capable of sustaining their limbs while walking over the ground as compared to walking on a treadmill, independent of body weight unloading. The duration of single limb support indicates the capacity for sustaining the limb (Perry, 1992). Greater pelvic posterior tilt, hip and knee extension and ankle plantar flexion were observed when children walked on a treadmill as compared to walking over the ground. Similarly, greater pelvic anterior tilt and hip flexion while walking on a treadmill as compared to over the ground. However, these findings should be carefully interpreted since these differences did not indicate different ranges of motion of pelvis and lower limb joints. The children tested in this experiment kept their thigh closer to the shank (knee flexion), and the shank closer to their foot (ankle dorsiflexion) while walking on a treadmill as compared to over the ground, which suggests a more crouched gait. Interestingly, while walking over the ground the children were able to keep these segments straighter as compared to walking on a treadmill. With the except of knee joint values that revealed greater inter-individual variability, all remaining values observed when the children with CP walked with BWS over the ground were pretty similar to their typically developing peers (Ounpuu, Gage, & Davis, 1991). In terms of BWS values, the children presented maximum angles similar to typically developing (Ounpuu et al., 1991) while walking with 30% BWS as compared to walking with 0% BWS. The use of treadmill for gait intervention is very common. Among several well-known advantages are the restricted space necessary and the better control of the number of steps during a gait training session. Controversy, the use of the treadmill imposes a different context altering propulsion and balance patterns (Norman et al., 1995). For example, to walk over the ground people must apply sufficient forces toward the floor to propel limbs forward. On a treadmill, the propulsion generated by the limbs is not necessarily proportional to velocity (Goldberg, Kautz, & Neptune, 2008), as the belt allows for the limbs to passively move with minimized levels of muscle activation (Harris-Love et al., 2004). In terms of balance control, it seems that children with CP adopt a different strategy, as they would adopt while walking over the ground. This was confirmed on this study as the children extended duration of double stance and single limb support. The results of this study clearly indicate the use of BWS system over the ground (instead of treadmill) would promote greater kinematic benefits for children with CP. One additional advantage is that these children would not have to transfer or adapt their gait parameters from the treadmill to over ground, if the intervention program directly focuses on learning how
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to walk over the ground. This is particularly important because children with CP struggle with such type adaptation (Barela et al., 2011). Importantly, the amount of BWS has to be set accordingly, so these children can sustain their body weight during the single limb support of each lower limb without excessively flexing their hip and knee. To present, only a few studies have assessed individuals with gait impairment as they walked with BWS (Lamontagne & Fung, 2004; Matsuno et al., 2010; Sousa et al., 2009). To the best of our knowledge only Matsuno et al. (2010) had used similar experimental conditions; walking with BWS on a treadmill and over the ground. On this study we further Matsuno’s results as our innovative findings showed the consequences of manipulating practical conditions that therapists could eventually use during training sessions with BWS. Additionally, this is the first study that assessed children with CP walking with a customized BWS system on a treadmill and over ground with different body weight unloading. Walking is a rather complex motor task and many other parameters beyond the spatial–temporal analysis and lower body joint angles must be considered. In addition, we recognize that a large number of participants would strengthen our findings. However, the challenges imposed by the inclusion criteria, as well as the difficulties faced on recording kinematic data on this population limited our sample size. Nevertheless, our results provide new insights to therapists and intervention programs targeting walking rehabilitation for this population. 5. Conclusion We concluded that changing the ground surface in which children with CP walk positively impact their gait performance; more than body weight unloading. Therefore, therapists adopting BWS strategies for gait training of children with CP, should be aware that although body unloading might facilitate gait execution the ground surface might promote greater impact on gait rehabilitation of children with CP. Conflict of interest The authors declare no competing interests. Acknowledgments This study was supported by the Sa˜o Paulo Research Foundation – FAPESP (Grant #2010/15218-3) – and by a fellowship by Coordenac¸a˜o de Aperfeic¸oamento de Pessoal de Nı´vel Superior – CAPES – for M.L. Celestino and by FAPEPS for G.L. Gama (#2013/01050-1). The study was conducted in the Laboratory of Movement Analysis, Institute of Physical Activity and Sport Sciences, Cruzeiro do Sul University. We would like to thank the children and their parents for participating in our study and P.B. Freitas for programming the routine in LabView. References Barela, J. A., Focks, G. M., Hilgeholt, T., Barela, A. M., Carvalho Rde, P., & Savelsbergh, G. J. (2011). 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Research in Developmental Disabilities
Gait characteristics of children with cerebral palsy as they walk with body weight unloading on a treadmill and over the ground Melissa L. Celestino, Gabriela L. Gama, Ana M.F. Barela * Graduate Program in Human Movement Sciences, Institute of Physical Activity and Sport Sciences, Cruzeiro do Sul University, Brazil
A R T I C L E I N F O
A B S T R A C T
Article history: Received 3 June 2014 Received in revised form 31 August 2014 Accepted 2 September 2014 Available online
Body weight support (BWS) has become a typical strategy for gait training, in special with children with cerebral palsy (CP). Although several findings have been reported in the literature, it remains uncertain how different types of surfaces and gradual amount of BWS can facilitate the mobility of children with CP. The aim of this study was to investigate gait kinematic parameters of children with CP by manipulating BWS and two different types of ground surfaces. Ten children (7.7 2.1 years old) diagnosed with spastic CP and GMFCS classification between levels II and IV were asked to walk on a treadmill and over the ground. In both conditions, BWS was manipulated to minimize gravitational effects and spatial– temporal gait parameters and lower limb joints were analyzed. The results revealed that the type of ground surface causes greater impact on the gait pattern of children with CP as compared to body weight unloading. This finding may provide new insights into the behavioral heterogeneity of children with CP, and offers critical information to be considered on interventional programs specifically designed to improve mobility on this population. ß 2014 Elsevier Ltd. All rights reserved.
Keywords: Body weight support system Spatial–temporal parameters Joint angles
1. Introduction While gait is an activity that most of us take for granted, it is a motor skill that requires an optimal pattern of motor coordination and involves complex control mechanisms (Inman, Ralston, & Todd, 1994; Winter, 1991). The optimal performance level might be specified by the interaction of three different categories of constraints (Newell, 1986): organism, including structural features (e.g., body mass and height) and functional features (e.g., synaptic connections); environment (e.g., gravity, ambient temperature, natural light, cultural backgrounds); and task, including goals of the task and rules and implements specifying response dynamics. Constraints are considered as boundaries that limit an individual’s motion at the same time that lead to alternative patterns of movement coordination and control; even if a movement is performed under the same set of environmental and task constraints. CP has been described as a group of disorders of the development of movement and posture that are permanent and cause activity limitation, and are attributed to non-progressive disturbances that occurred in the developing fetal or infant brain (Rosenbaum, Paneth, Leviton, Goldstein, & Bax, 2007). The effect of CP on functional abilities varies greatly. Some people are
* Corresponding author at: Rua Galva˜o Bueno, 868, 138 andar, Bloco B, 01506-000 Sa˜o Paulo, SP, Brazil. Tel.: +55 11 3385 3103. E-mail addresses: [email protected], [email protected] (Ana M.F. Barela). http://dx.doi.org/10.1016/j.ridd.2014.09.002 0891-4222/ß 2014 Elsevier Ltd. All rights reserved.
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able to walk while others are not. Some people show normal to near typical intellectual function, but others may have intellectual disabilities. Its motor severity is generally classified according to the Gross Motor Function Classification System (GMFCS) (Palisano et al., 1997; Palisano, Rosenbaum, Bartlett, & Livingston, 2008). Among several movement deficiencies, the gait impairment is one of the major concerns for parents and caregivers. According to Chang, Rhodes, Flynn, and Carollo (2010), the gait impairment is due to spasticity (or abnormal muscle tone), reduced motor control ability and impaired balance. As these children grow with no simultaneous lengthening of skeletal muscles, muscular tightness and muscle contractures, they eventually develop bony torsion. Consequently, children with CP on ambulatory condition usually present a decline in gait function over time (Bell, Ounpuu, DeLuca, & Romness, 2002; Johnson, Damiano, & Abel, 1997; Norlin & Odenrick, 1986). To overcome the inability to typically develop gait movement patterns, different categories of treatment have been proposed and investigated, including therapeutic interventions and neuromuscular invasive techniques. For instance, the use of body weight support (BWS) is a typical therapeutic intervention technique that provides taskspecific gait training. The rationale for using the BWS system is that the reduction of gravitational forces would reduce the load that should be overcome by the individual; facilitating the walking constraints. Consequently, this strategy might promote a gait pattern close to typical (Finch, Barbeau, & Arsenault, 1991). In general, the BWS systems consist of a mounting frame and a harness to support a percentage of the individual’s weight as s/he walks on a motorized treadmill (MatternBaxter, 2009; Mutlu, Krosschell, & Spira, 2009). The use of a treadmill is usually adopted to stimulates rhythmical and repetitive steps (Visintin, Barbeau, Korner-Bitensky, & Mayo, 1998). In addition, the treadmill belt triggers interlimb symmetry causing positive effects on the temporal parameters of walking (Harris-Love, Macko, Whitall, & Forrester, 2004), as well as diminishing the need for propulsive force generation at the end of the stance period (Norman, Pepin, Ladouceur, & Barbeau, 1995). More recently, the BWS systems have been employed during over ground walking in individuals with stroke (Lamontagne & Fung, 2004; Miller, Quinn, & Seddon, 2002; Prado-Medeiros et al., 2011; Sousa, Barela, Prado-Medeiros, Salvini, & Barela, 2009; Sousa, Barela, Prado-Medeiros, Salvini, & Barela, 2011) and children with CP (Matsuno, Camargo, Palma, Alveno, & Barela, 2010). However, to the best of our knowledge, it remains unclear whether the type of surface and/or the amount of body weight unloaded could influence the way that children with CP walk. This study was designed to investigate gait kinematic parameters of children with CP by manipulating BWS and two different types of ground surfaces (treadmill and over ground). 2. Methods 2.1. Participants Ten children (7.7 2.1 years old) diagnosed with spastic CP and GMFCS classification between levels II and IV were selected to participate in this study (Table 1). The inclusion criteria also account for the individual’s ability to walk approximately 7 m with or without assistance, and to understand the experimental instructions and procedures. Fourteen children were initially recruited and assessed. However, data from four participants were excluded due to experimental difficulties encountered either during data acquisition (n = 2) or data processing (n = 2). Prior to participation, each child’s parent or legal guardian provided informed consent. All experimental procedures were approved by the Institutional Review Board at the University of Cruzeiro do Sul, Sao Paulo, Brazil (Protocol 020/2010). 2.2. Procedures The children were asked to walk at a comfortable speed along a walkway (7 m) and on a treadmill under three different conditions: walking wearing a harness and bearing full body weight (‘‘0% BWS’’ condition); walking wearing a harness and 15% of full body weight unloaded (‘‘15% BWS’’ condition); and walking wearing a harness and 30% of full body weight Table 1 General information about the children considered in the final sample. ID
Sex
Age (years)
Mass (kg)
Height (cm)
Diagnosis
GMFCS
1 2 3 4 5 6 7 8 9 10 Mean SD
F M M F F F M M F F – –
9.3 8.3 9.5 3.2 7.8 7.5 8.9 8.6 4.9 9 7.7 2.1
19.7 23.8 25.3 13.1 34.5 30.0 30.7 23.2 15.5 19.1 23.5 6.9
123 132 130 93 138 108 122 136 110 104 119.6 15.1
Diplegia Diplegia Diplegia Diplegia Hemiplegia Diplegia Diplegia Diplegia Diplegia Hemiplegia – –
III II II III III IV III III IV II – –
Abbreviation: ID, child’s identification; GMFCS, Gross Motor Function Classification System (Palisano et al., 1997).
[(Fig._1)TD$IG]
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Fig. 1. Representation of the customized body weight support system, illustrating the suspended rail, moving cart and the two electrical servo motors, load cell, drivers and computer that control the displacement, velocity and acceleration of the moving cart, and the harness. Note: more details are described in the text.
unloaded (‘‘30% BWS’’ condition). Fig. 1 exemplifies the customized BWS system (Finix Tecnologia). The system consists of a suspended rail (7 m) mounted on the ceiling (3 m height) and sustained by two steel beams. A moving cart is attached to the bottom of the rail allowing for backward and forward movements and controlled by a belt system linked to a servo motor. A customized program (LabView 2011, National Instruments Inc.) was developed to control displacement, velocity and acceleration of the moving cart. In addition, the moving cart was controlled by a second servo motor that controlled the mechanical body weight supported provided by the harness. An instrumented load cell registered the body weight and allowed for weight unload manipulation. To accurately unload the individual’s body weight according to the desired experimental conditions, participants were asked to stay still until the belt’s length was properly adjusted. A computerized gait analysis system (VICON Bonita 10) with seven infrared cameras was used to measure kinematic data. Based on the Vicon Plug-In Gait model (Vicon, 2010), reflective markers were placed on the sacrum, and bilaterally on the anterior superior iliac crest, the midpoint of the lateral femur, the lateral knee joint axis, the midpoint of the lateral tibia, the lateral malleolus, the calcaneus and the second metatarsal head. This reference point system has been broadly adoptee by previous studies (e.g., Benedetti, Manca, Ferraresi, Boschi, & Leardini, 2011; Bohm & Doderlein, 2012). A calibration trial was conducted prior to testing. Each participant stood upright to record the neutral position (baseline) of all joints and segments. All participants were asked to walk barefoot at a self-determined speed, which was kept the same for all experimental conditions. Before data acquisition, all children practiced for a few trials until they felt comfortable with the mechanical device and the lab environment. Three trials, minimum, were recorded for each experimental condition. The experimental conditions were properly randomized within and across individuals. 2.3. Data processing One intermediate stride per trial by each child, for a total of three selected trials for each condition, was analyzed. The trial selection was determined by the best visualization of the markers as the children walked with no interruption. Through visual inspection, a stride (walking cycle) was defined by two consecutive initial contacts of the same limb with the ground along the progression line. In addition, walking events during a stride were identified for subsequent calculation of the temporal organization of walking, such as initial and terminal double stance, single limb support and swing period (Perry, 1992). This procedure was carried out for both right and left sides of the body. Joint and segmental angles were processed with Vicon Nexus software (version 1.8.5). Subsequent analyses were performed using Matlab software (MathWorks, Inc.). For joint and segmental angles, strides were normalized in time from 0% to 100% with a 1% step. These cycles were referred to the children’s neutral angles measured during the calibration trial in each condition and were then averaged to obtain the mean cycle for each participant. The same procedure was repeated to obtain the mean cycle among participants. The outcome measures analyzed in this study were: stride length (distance between two successive initial contacts of the same foot to the surface, determined by the position of the calcaneus), speed (calculated as the ratio between stride length and duration), durations of total double stance and single limb support, maximum angles of pelvis (posterior tilt), hip (extension), knee (extension) and ankle (plantar flexion) and minimum angles of pelvis (anterior tilt), hip (flexion), knee (flexion) and ankle (dorsiflexion) at the sagittal plane during each stride. Data from right and left sides were averaged together before making comparisons among different experimental conditions. 2.4. Statistical analysis For all variables, data from three trials under each condition were averaged for each child. Multivariate analyses of variance (MANOVAs) for repeated measures were employed, using surface (treadmill and over ground) and body weight unloading (0%, 15% and 30%) as factors. The dependent variables were stride length and stride speed for the first MANOVA;
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Table 2 Mean (SD) values of the spatial–temporal parameters of walking during the stride cycle according to surface and body weight support (BWS). Outcome measures/surface
BWS 0%
p value 15%
Stride length (m) Over ground Treadmill
0.56 (0,17) 0.60 (0.23)
0.60 (0.18) 0.57 (0.21)
Stride speed (m/s) Over ground Treadmill
0.44 (0.19) 0.47 (0.17)
0.45 (0.19) 0.45 (0.17)
30%
Surface
BWS
Surface*BWS
0.61 (0.17) 0.56 (0.22)
0.743
0.905
0.028
0.46 (0.18) 0.42 (0.18)
0.877
0.585
0.001
Total double stance (%) Over ground Treadmill
34 (7.4) 42 (5.4)
37 (5.5) 40 (5.4)
31 (7.6) 39 (6.7)
0.002
0.075
0.480
Single limb support (%) Over ground Treadmill
32 (6.7) 23 (2.5)
27 (4.4) 25 (2.4)
31 (6.6) 24 (4.2)
0.005
0.378
0.065
total double stance and single limb support for the second MANOVA; maximum angles of pelvis, hip, knee and ankle for the third MANOVA; and minimum angles of pelvis, hip, knee and ankle for the fourth MANOVA. When necessary, univariate analyses, comparisons with Bonferroni adjustments and Tukey post hoc tests were employed as necessary. Alpha level of 0.05 was adopted. All analyses were performed using the Statistical Package for Social Sciences software. 3. Results Each child walked at the same mean speed in all conditions. The speed ranged from 0.29 to 0.83 (0.43, SD 0.19) m/s. Table 2 depicts mean (SD) values of walking cycle’s spatial–temporal parameters. MANOVA for stride length and speed revealed interaction between the surface and BWS (Wilks’ Lambda = 0.42, F4,34 = 4.65, p < 0.005). The univariate analysis revealed interaction between the surface and BWS for stride length (F2,18 = 4.37) and stride speed (F2,18 = 10.14). Tukey post hoc test revealed that only stride speed was lower when children walked with 30% BWS compared to 0% BWS on a treadmill. MANOVA for durations of total double stance and single limb support revealed a surface effect only (Wilks’ Lambda = 0.30, F2,8 = 9.40, p = 0.008). The univariate analysis revealed that children presented shorter double stance (F1,9 = 17.69) and longer single limb support (F1,9 = 13.99) when they walked over ground compared to on a treadmill (Table 2). Fig. 2 illustrates the mean (SD) values gait cycles of pelvis, hip, knee and ankle angles in the sagittal plane of all children as they walked on both surfaces with 0%, 15% and 30% BWS. Qualitatively, the pelvis and all joints seemed to have roughly similar patterns in all conditions. Anterior and posterior pelvic tilt, hip and knee flexion and extension, and ankle dorsiflexion and plantar flexion were present in all conditions. Table 3 depicts mean (SD) values of minimum and maximum angles for pelvis, hip, knee and ankle joints during the gait cycle in all conditions. For minimum angles, MANOVA revealed an effect only for the surface (Wilks’ Lambda = 0.06, F4,6 = 22.68, p = 001). Univariate analyses revealed that children presented less pelvic posterior tilt (F1,9 = 7.67), hip extension (F1,9 = 7.92), knee extension (F1,9 = 14.52) and ankle plantar flexion (F1,9 = 13.57) when walking over ground compared to on a treadmill (Table 3). For maximum angles, MANOVA revealed an effect for surface (Wilks’ Lambda = 0.13, F4,6 = 9.73, p = 0.009), and a tendency for BWS (Wilks’ Lambda = 0.39, F8,30 = 2.24, p = 0.52). Univariate analyses for surface revealed that children presented less pelvic anterior tilt (F1,9 = 7.92) and hip flexion (F1,9 = 16.18) when walking over ground compared to on a treadmill. Univariate analyses for BWS revealed differences for pelvic anterior tilt (F2,18 = 5.23), hip flexion (F2,18 = 5.47) and ankle dorsiflexion (F2,18 = 9.23). Comparisons with Bonferroni adjustment revealed that children presented higher excursion for pelvis, hip and ankle with 0% BWS compared to 30% BWS, and higher excursion for ankle with 15% BWS compared to 30% BWS (Table 3). 4. Discussion The aim of this study was to investigate gait kinematic parameters of children with CP by manipulating BWS and two different types of ground surfaces. Overall, the results revealed that ground surfaces caused greater impact on gait patterns of children with CP as compared to body weight unloading. Interestingly, even the children who could not walk independently were able to walk with a BWS system on both surfaces. Specifically, it was found that ground surface affected individual’s total double stance, single limb support, minimum angles of pelvis, hip, knee and ankle and maximum angles of pelvis and hip, suggesting that walking over the ground promoted a gait pattern more similar to their typically developing peers. The body weight unloading affected the maximum angles of the pelvis, hip and ankle on both surfaces and stride speed on treadmill, suggesting that children with CP had difficulties overcoming the gravitational forces.
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Fig. 2. Mean (SD) stride cycles of pelvis (A, E, I), hip (B, F, J), knee (C, G, K) and ankle (D, H, L) in the sagittal plane for the children with cerebral palsy as they walked with 0% BWS (left panel), 15% BWS (middle panel) and 30% BWS (right panel) on a treadmill (gray area) and over ground (line).
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Table 3 Mean (SD) values of pelvis and joint angles (degrees) during the stride cycle according to surface and body weight support (BWS). Outcome measures/surface
BWS 0%
Pelvic posterior tilt Over ground Treadmill Hip extension Over ground Treadmill
p value 15%
10 (7) 13 (8)
9 (8) 11 (7)
30%
Surface
BWS
Surface*BWS
9 (9) 10 (10)
0.022
0.087
0.527
2 (10) 7 (12)
2 (10) 5 (10)
3 (11) 6 (11)
0.020
0.105
0.353
Knee extension Over ground Treadmill
14 (13) 19 (15)
15 (14) 18 (13)
15 (13) 18 (13)
0.004
0.658
0.478
Ankle plantar flexion Over ground Treadmill
21 (25) 13 (17)
21 (18) 17 (18)
22 (22) 21 (22)
0.005
0.953
0.297
Pelvic anterior tilt Over ground Treadmill
19 (6) 22 (10)
18 (7) 20 (7)
18 (8) 19 (8)
0.020
0.016
0.248
Hip flexion Over ground Treadmill
42 (11) 49 (14)
42 (13) 44 (12)
42 (14) 43 (13)
0.003
0.014
0.199
Knee flexion Over ground Treadmill
59 (24) 62 (30)
61 (26) 57 (19)
61 (25) 58 (25)
0.383
0.884
0.498
Ankle dorsiflexion Over ground Treadmill
19 (11) 23 (12)
19 (16) 17 (12)
14 (9) 19 (15)
0.182
0.002
0.290
Different from previous findings (Matsuno et al., 2010), similar stride length was observed in all experimental conditions. This might be attributed to the mean walking speed that is known as a critical parameter that affect the gait pattern (Winter, 1991). On the other hand, the children in this study presented greater instability while walking on a treadmill as compared to walking over the ground. This finding was supported by higher double stance duration and lower single limb support duration, respectively. For instance, it was observed that by increasing the base of support (both feet on the ground), balance and stability also increased. The children with CP took longer strides (keeping both feet in contact with the treadmill) as strategy to ensure greater walking stability. Furthermore, the tested children were more capable of sustaining their limbs while walking over the ground as compared to walking on a treadmill, independent of body weight unloading. The duration of single limb support indicates the capacity for sustaining the limb (Perry, 1992). Greater pelvic posterior tilt, hip and knee extension and ankle plantar flexion were observed when children walked on a treadmill as compared to walking over the ground. Similarly, greater pelvic anterior tilt and hip flexion while walking on a treadmill as compared to over the ground. However, these findings should be carefully interpreted since these differences did not indicate different ranges of motion of pelvis and lower limb joints. The children tested in this experiment kept their thigh closer to the shank (knee flexion), and the shank closer to their foot (ankle dorsiflexion) while walking on a treadmill as compared to over the ground, which suggests a more crouched gait. Interestingly, while walking over the ground the children were able to keep these segments straighter as compared to walking on a treadmill. With the except of knee joint values that revealed greater inter-individual variability, all remaining values observed when the children with CP walked with BWS over the ground were pretty similar to their typically developing peers (Ounpuu, Gage, & Davis, 1991). In terms of BWS values, the children presented maximum angles similar to typically developing (Ounpuu et al., 1991) while walking with 30% BWS as compared to walking with 0% BWS. The use of treadmill for gait intervention is very common. Among several well-known advantages are the restricted space necessary and the better control of the number of steps during a gait training session. Controversy, the use of the treadmill imposes a different context altering propulsion and balance patterns (Norman et al., 1995). For example, to walk over the ground people must apply sufficient forces toward the floor to propel limbs forward. On a treadmill, the propulsion generated by the limbs is not necessarily proportional to velocity (Goldberg, Kautz, & Neptune, 2008), as the belt allows for the limbs to passively move with minimized levels of muscle activation (Harris-Love et al., 2004). In terms of balance control, it seems that children with CP adopt a different strategy, as they would adopt while walking over the ground. This was confirmed on this study as the children extended duration of double stance and single limb support. The results of this study clearly indicate the use of BWS system over the ground (instead of treadmill) would promote greater kinematic benefits for children with CP. One additional advantage is that these children would not have to transfer or adapt their gait parameters from the treadmill to over ground, if the intervention program directly focuses on learning how
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to walk over the ground. This is particularly important because children with CP struggle with such type adaptation (Barela et al., 2011). Importantly, the amount of BWS has to be set accordingly, so these children can sustain their body weight during the single limb support of each lower limb without excessively flexing their hip and knee. To present, only a few studies have assessed individuals with gait impairment as they walked with BWS (Lamontagne & Fung, 2004; Matsuno et al., 2010; Sousa et al., 2009). To the best of our knowledge only Matsuno et al. (2010) had used similar experimental conditions; walking with BWS on a treadmill and over the ground. On this study we further Matsuno’s results as our innovative findings showed the consequences of manipulating practical conditions that therapists could eventually use during training sessions with BWS. Additionally, this is the first study that assessed children with CP walking with a customized BWS system on a treadmill and over ground with different body weight unloading. Walking is a rather complex motor task and many other parameters beyond the spatial–temporal analysis and lower body joint angles must be considered. In addition, we recognize that a large number of participants would strengthen our findings. However, the challenges imposed by the inclusion criteria, as well as the difficulties faced on recording kinematic data on this population limited our sample size. Nevertheless, our results provide new insights to therapists and intervention programs targeting walking rehabilitation for this population. 5. Conclusion We concluded that changing the ground surface in which children with CP walk positively impact their gait performance; more than body weight unloading. Therefore, therapists adopting BWS strategies for gait training of children with CP, should be aware that although body unloading might facilitate gait execution the ground surface might promote greater impact on gait rehabilitation of children with CP. Conflict of interest The authors declare no competing interests. Acknowledgments This study was supported by the Sa˜o Paulo Research Foundation – FAPESP (Grant #2010/15218-3) – and by a fellowship by Coordenac¸a˜o de Aperfeic¸oamento de Pessoal de Nı´vel Superior – CAPES – for M.L. Celestino and by FAPEPS for G.L. Gama (#2013/01050-1). The study was conducted in the Laboratory of Movement Analysis, Institute of Physical Activity and Sport Sciences, Cruzeiro do Sul University. We would like to thank the children and their parents for participating in our study and P.B. Freitas for programming the routine in LabView. References Barela, J. A., Focks, G. M., Hilgeholt, T., Barela, A. M., Carvalho Rde, P., & Savelsbergh, G. J. (2011). 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