- Email: [email protected]
Influence of targeted intervention on ballet dancers’ foot load during gait
S114
Abstracts / Gait & Posture 39S (2014) S1–S141
human motion as a base for support and lever for locomotion [3]. The results of this study showed the positive transfer of load toward the lateral side, however there was no decrease of load on the medial side. Because of the high foot load intensity in ballet dancers, a longer duration of intervention is necessary, with an emphasis on autotherapy for each dancer.
P44 Influence of targeted intervention on ballet dancers’ foot load during gait M. Procházková 1,2,∗ , L. Teplá 1 , Z. Svoboda 1 , M. Janura 1 , E. Juráková 2 1
Department of Natural Sciences in Kinanthropology, Faculty of Physical Culture, Palacky University, Olomouc, Czech Republic 2 Department of Physiotherapy, Faculty of Physical Culture, Palacky University, Olomouc, Czech Republic
Reference
Introduction and aim: In the literature there is evidence that ballet dancers excessively load the medial edge of their foot during the gait in comparison with non-dancers [1]. It can be explained by the dancing positions (e.g. turnout) in which the dancers have a tendency to load the medial edge of foot with greater intensity [2]. The dancers transfer this stereotype into their everyday activities, such as gait. For a successful prevention of possible excessive foot inversion and eversion rehabilitation can be used. The aim of the present study is to determine the influence of rehabilitation intervention on the plantar pressure distribution in professional dancers. Materials and methods: Seventeen professional ballet dancers (six men, 11 women; mean age: 25.2 ± 5.2 years; mean height: 170.7 ± 9.9 cm; mean weight: 60.0 ± 12.3 kg) participated in the present study. Their mean dancing experience was 16.1 ± 4.8 years. The intensity of dancing training was 9 h a day. Foot pressure data was collected using a 2 m pressure plate (RSscan International, Olen, Belgium). Eight gait cycles were used for data analysis. Using the Footscan gait software (version 7.97) the foot was divided into ten parts. Dancers were randomly divided into two groups – experimental (EG) (9) and control group (CG) (8). They underwent two measurements (before and after rehabilitation). The EG has been undergoing six weeks of rehabilitation, the CG has been without intervention. For rehabilitation we were using soft tissues treatment of foot and lower limb and methods based on the scientific principles of developmental kinesiology and the neurophysiological aspects of the maturing locomotor system. Results: The results showed significantly higher values (p < 0.05) of the pressure peak in the 2nd and 3rd metatarsus zone after rehabilitation in EG. On the other hand, in zone of the toes 2–5 the pressure peak reached significantly lower output values (p < 0.05) in CG (Table 1.). Discussion and conclusions: Targeted intervention led to a shift of the distribution of the body weight closer to the foot axis. This allowed the foot to better perform its fundamental role in
[1] Lung CW, Chern JS, Hsieh LH, Yang SW. The differences in gait pattern between dancers and non-dancers. J Mech 2008;24(4):451–7. [2] Kravitz SR, Huber S, Ruziskey JA, Murgia CJ. Biomechanical analysis of maximal pedal stress during ballet stance. J Am Podiatr Med Assoc 1987;77(9):484–9. [3] Morrison KE, Kaminski TW. Foot characteristics in association with inversion ankle injury. J Athl Train 2007;42(1):135–42.
http://dx.doi.org/10.1016/j.gaitpost.2014.04.157 P45 Comparing the Harrington and Davis method of hip joint centre localisation for unimpaired and pathological subjects Kathryn Parker ∗ , Julie Stebbins, Joanne Bates Oxford Gait Laboratory, Nuffield Orthopaedic Centre NHS Trust, Oxford, UK Introduction and aim: Localisation of the hip joint centre (HJC) affects both kinematic and kinetic data in gait analysis. The predictive equation suggested by Davis [1] to calculate HJC co-ordinates has been used extensively but the accuracy of this method has recently been questioned. An alternative HJC algorithm was proposed by Harrington et al. [2]. Previous studies have found the Harrington method to be more comparable to functional methods, and to HJC positions calculated using 3-DUS [3]. However, these studies have primarily been tested on healthy adults. The aim of this study was to assess the difference between the two equations for predicting HJC in pathological subjects, particularly focussing on those with abnormal anthropometry. A secondary aim was to determine the effect of error in HJC calculation on kinematic output. Patients/materials and methods: Data from 20 normal subjects (10 children, aged 8–12 years old, five female adults and five male adults) and 25 patients (including cerebral palsy, orthopaedic and neurological diagnoses) were extracted retrospectively from the database at the gait laboratory. Group one included eight subjects of short stature (SS) (below the 0.4th %ile for their age, identified from growth charts). Group two consisted of eight subjects with high BMI (>30 kg/m2 ), and group three consisted of nine subjects with excessive (≥40◦ ) anteversion. All subjects fulfilled criteria for a
Table 1 Statistical analysis of pressure peak (%). Pressure peak (%) EG
CG
IV Mean ± SD Toe 1 Toe 2-5 Metatarsus 1 Metatarsus 2 Metatarsus 3 Metatarsus 4 Metatarsus 5 Midfoot Heel Medial Heel Lateral
8.4 2.5 11.3 16.2 14.1 11.3 6.0 2.4 14.5 11.3
± ± ± ± ± ± ± ± ± ±
2.6 1.1 2.9 2.4 2.3 3.3 2.2 0.7 2.4 1.6
OV Mean ± SD 8.9 2.5 11.6 17.2 15.4 11.8 6.4 2.4 14.7 12.2
± ± ± ± ± ± ± ± ± ±
2.4 1.0 2.5 2.0 3.2 3.4 1.9 0.8 2.4 2.1
p values
IV Mean ± SD 8.9 3.1 11.7 18.5 13.9 9.7 5.6 2.2 15.1 12.0
± ± ± ± ± ± ± ± ± ±
3.4 1.2 2.2 4.6 4.0 3.1 2.8 0.9 2.3 1.9
OV Mean ± SD 8.5 2.8 11.1 17.9 14.1 9.8 5.5 2.1 14.6 11.7
± ± ± ± ± ± ± ± ± ±
2.1 1.2 1.8 4.4 3.9 3.5 2.5 0.9 1.8 1.7
IV – OV EG
CG
EG × CG Input
Output
0.145 0.811 0.557 0.022 0.035 0.557 0.396 0.744 0.557 0.064
0.379 0.023 0.255 0.569 0.569 0.959 0.717 0.215 0.234 0.642
0.851 0.237 0.463 0.175 0.695 0.075 0.484 0.281 0.695 0.403
0.646 0.670 0.403 0.798 0.484 0.088 0.365 0.237 0.825 0.463
EG, Experimental group; CG, Control group; IV, Input values; OV, Output values; SD, Standard deviation; highlighted values are statistically significant (p < 0.05).
Abstracts / Gait & Posture 39S (2014) S1–S141
human motion as a base for support and lever for locomotion [3]. The results of this study showed the positive transfer of load toward the lateral side, however there was no decrease of load on the medial side. Because of the high foot load intensity in ballet dancers, a longer duration of intervention is necessary, with an emphasis on autotherapy for each dancer.
P44 Influence of targeted intervention on ballet dancers’ foot load during gait M. Procházková 1,2,∗ , L. Teplá 1 , Z. Svoboda 1 , M. Janura 1 , E. Juráková 2 1
Department of Natural Sciences in Kinanthropology, Faculty of Physical Culture, Palacky University, Olomouc, Czech Republic 2 Department of Physiotherapy, Faculty of Physical Culture, Palacky University, Olomouc, Czech Republic
Reference
Introduction and aim: In the literature there is evidence that ballet dancers excessively load the medial edge of their foot during the gait in comparison with non-dancers [1]. It can be explained by the dancing positions (e.g. turnout) in which the dancers have a tendency to load the medial edge of foot with greater intensity [2]. The dancers transfer this stereotype into their everyday activities, such as gait. For a successful prevention of possible excessive foot inversion and eversion rehabilitation can be used. The aim of the present study is to determine the influence of rehabilitation intervention on the plantar pressure distribution in professional dancers. Materials and methods: Seventeen professional ballet dancers (six men, 11 women; mean age: 25.2 ± 5.2 years; mean height: 170.7 ± 9.9 cm; mean weight: 60.0 ± 12.3 kg) participated in the present study. Their mean dancing experience was 16.1 ± 4.8 years. The intensity of dancing training was 9 h a day. Foot pressure data was collected using a 2 m pressure plate (RSscan International, Olen, Belgium). Eight gait cycles were used for data analysis. Using the Footscan gait software (version 7.97) the foot was divided into ten parts. Dancers were randomly divided into two groups – experimental (EG) (9) and control group (CG) (8). They underwent two measurements (before and after rehabilitation). The EG has been undergoing six weeks of rehabilitation, the CG has been without intervention. For rehabilitation we were using soft tissues treatment of foot and lower limb and methods based on the scientific principles of developmental kinesiology and the neurophysiological aspects of the maturing locomotor system. Results: The results showed significantly higher values (p < 0.05) of the pressure peak in the 2nd and 3rd metatarsus zone after rehabilitation in EG. On the other hand, in zone of the toes 2–5 the pressure peak reached significantly lower output values (p < 0.05) in CG (Table 1.). Discussion and conclusions: Targeted intervention led to a shift of the distribution of the body weight closer to the foot axis. This allowed the foot to better perform its fundamental role in
[1] Lung CW, Chern JS, Hsieh LH, Yang SW. The differences in gait pattern between dancers and non-dancers. J Mech 2008;24(4):451–7. [2] Kravitz SR, Huber S, Ruziskey JA, Murgia CJ. Biomechanical analysis of maximal pedal stress during ballet stance. J Am Podiatr Med Assoc 1987;77(9):484–9. [3] Morrison KE, Kaminski TW. Foot characteristics in association with inversion ankle injury. J Athl Train 2007;42(1):135–42.
http://dx.doi.org/10.1016/j.gaitpost.2014.04.157 P45 Comparing the Harrington and Davis method of hip joint centre localisation for unimpaired and pathological subjects Kathryn Parker ∗ , Julie Stebbins, Joanne Bates Oxford Gait Laboratory, Nuffield Orthopaedic Centre NHS Trust, Oxford, UK Introduction and aim: Localisation of the hip joint centre (HJC) affects both kinematic and kinetic data in gait analysis. The predictive equation suggested by Davis [1] to calculate HJC co-ordinates has been used extensively but the accuracy of this method has recently been questioned. An alternative HJC algorithm was proposed by Harrington et al. [2]. Previous studies have found the Harrington method to be more comparable to functional methods, and to HJC positions calculated using 3-DUS [3]. However, these studies have primarily been tested on healthy adults. The aim of this study was to assess the difference between the two equations for predicting HJC in pathological subjects, particularly focussing on those with abnormal anthropometry. A secondary aim was to determine the effect of error in HJC calculation on kinematic output. Patients/materials and methods: Data from 20 normal subjects (10 children, aged 8–12 years old, five female adults and five male adults) and 25 patients (including cerebral palsy, orthopaedic and neurological diagnoses) were extracted retrospectively from the database at the gait laboratory. Group one included eight subjects of short stature (SS) (below the 0.4th %ile for their age, identified from growth charts). Group two consisted of eight subjects with high BMI (>30 kg/m2 ), and group three consisted of nine subjects with excessive (≥40◦ ) anteversion. All subjects fulfilled criteria for a
Table 1 Statistical analysis of pressure peak (%). Pressure peak (%) EG
CG
IV Mean ± SD Toe 1 Toe 2-5 Metatarsus 1 Metatarsus 2 Metatarsus 3 Metatarsus 4 Metatarsus 5 Midfoot Heel Medial Heel Lateral
8.4 2.5 11.3 16.2 14.1 11.3 6.0 2.4 14.5 11.3
± ± ± ± ± ± ± ± ± ±
2.6 1.1 2.9 2.4 2.3 3.3 2.2 0.7 2.4 1.6
OV Mean ± SD 8.9 2.5 11.6 17.2 15.4 11.8 6.4 2.4 14.7 12.2
± ± ± ± ± ± ± ± ± ±
2.4 1.0 2.5 2.0 3.2 3.4 1.9 0.8 2.4 2.1
p values
IV Mean ± SD 8.9 3.1 11.7 18.5 13.9 9.7 5.6 2.2 15.1 12.0
± ± ± ± ± ± ± ± ± ±
3.4 1.2 2.2 4.6 4.0 3.1 2.8 0.9 2.3 1.9
OV Mean ± SD 8.5 2.8 11.1 17.9 14.1 9.8 5.5 2.1 14.6 11.7
± ± ± ± ± ± ± ± ± ±
2.1 1.2 1.8 4.4 3.9 3.5 2.5 0.9 1.8 1.7
IV – OV EG
CG
EG × CG Input
Output
0.145 0.811 0.557 0.022 0.035 0.557 0.396 0.744 0.557 0.064
0.379 0.023 0.255 0.569 0.569 0.959 0.717 0.215 0.234 0.642
0.851 0.237 0.463 0.175 0.695 0.075 0.484 0.281 0.695 0.403
0.646 0.670 0.403 0.798 0.484 0.088 0.365 0.237 0.825 0.463
EG, Experimental group; CG, Control group; IV, Input values; OV, Output values; SD, Standard deviation; highlighted values are statistically significant (p < 0.05).