View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Wolverhampton Intellectual Repository and E-theses 1 AN INVESTIGATION OF GRAND BATTEMENT DEVANT AT BARRE, CENTRE, AND IN MOTION USING KINEMATICS AND ELECTROMYOGRAPHY Donna Krasnow, MSc A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy This research programme was carried out in collaboration with the California State University, Northridge This work or any part thereof has not previously been presented in any form to the University or to any other body whether for the purposes of assessment, publication or for any other purpose (unless otherwise indicated). Save for any express acknowledgments, references and/or bibliographies cited in the work, I confirm that the intellectual content of the work is the result of my own efforts and of no other person. The right of Donna Krasnow to be identified as author of this work is asserted in accordance with ss.77 and 78 of the Copyright, Designs and Patents Act 1988. At this date copyright is owned by the author. Signature……………………………………….. Date……………………………………………… 2 ABSTRACT The purpose of this study was to examine grand battement devant in three conditions: at the barre, in the centre, and traveling. The primary focus was to consider weight transfer in the three conditions, and to examine utilisation of the trunk and lower extremity muscles. An extensive review was done in the dance science literature to determine what previous research had been done related to this subject, and to establish what preliminary work might be needed. As indicated by the literature, in order to achieve this research, it was necessary to develop a dance-specific method for the normalisation of surface electromyography data. In phase one of the research, a dance-specific portable anchored dynamometer was developed and tested. The PAD allowed for the collection of maximum voluntary isometric contractions (MVICs), which could then be used to normalise the sEMG data. In phase two of the research, the grand battement was tested in the three conditions, at the barre, in the centre, and traveling. Forty female dancers volunteered (mean age 30.0 ± 13.0 yrs, mean height 1.63 ± 0.06 m, mean mass 59.0 ± 7.4 kg, and 13.9 ± 13.3 yrs of training in ballet and/or modern dance) and were placed in three groups (Training level): beginner (n = 12), intermediate (n = 14) and advanced (n = 14). Dancers executed five grand battement devant in each of the three conditions (Condition) in randomized order. Data were collected with a 7-camera Vicon motion capture system, two Kistler forceplates, and surface electromyography (EMG), using eight muscles bilaterally. Kinematic data were analysed in three intervals: stance to battement initiation, initiation to battement peak, and peak to end. Four variables were investigated: centre of gravity of the full trunk, centre of gravity of the pelvis, centre of gravity of the upper trunk, and centre of mass. EMG data were analysed in four events: stance, initiation, peak, and end. For weight transfer, the main effect of Condition was significant for all 3 four variables in both the x-axis and the y-axis (p < .001). There were no significant differences for Training and no significant Condition x Training interactions. Muscle use varied according to the combination of event and condition that was executed, and these differences were also influenced by the level of training of the dancer and the side of the body used. It is recommended that dance educators consider the importance of allocating sufficient time to each of the three conditions (barre, centre, and traveling), to ensure development of a variety of motor strategies and muscle activation patterns for dance practice. 4 TABLE OF CONTENTS Abstract 2 Table of Contents 4 List of Figures and Tables 6 Figures 6 Tables 7 Acknowledgements 8 1 Introduction 9 1.1 Background 9 1.2 Purpose 14 2 Review of Literature 15 2.1 Review methodology 15 2.2 Review of articles based on dance movement 16 2.2.1 Alignment 16 2.2.2 Plié 19 2.2.3 Relevé 23 2.2.4 Passé 27 2.2.5 Degagé 28 2.2.6 Développé 31 2.2.7 Rond de jambe 34 2.2.8 Grand battement 35 2.2.9 Forward stepping 38 2.2.10 Turns 40 2.2.11 Elevation work 42 2.2.11.1 1970s: Early work profiling technique 42 2.2.11.2 1980s: Work profiling technique 43 2.2.11.3 1990s: Examining additional elements - Momentum, forces, motor strategies, interventions 45 2.2.11.4 2000s: Recent work – Laterality, gender, body composition 48 2.2.12 Motor strategies 51 2.3 Summary of literature review 55 2.3.1 Overview 55 2.3.2 Measurement tools 56 2.3.3 Themes 58 2.3.4 Research design 61 3 Dynamometer study 64 3.1 Stage 1 – Review of literature 66 3.1.1 Introduction 66 3.1.2 Dynamometers for sEMG normalization 67 3.1.3 Standardized equipment 67 3.1.4 The hand-held dynamometer (HHD) 68 3.1.5 Portable anchored dynamometers (PAD) 70 5 3.2 Stage 2 – Need for a dance-specific PAD 72 3.2.1 Methods 73 3.2.2 Results 86 4 Grand battement study 91 4.1 Introduction 91 4.2 Methods 92 4.2.1 Participants 92 4.2.2 Instrumentation 93 4.2.3 Protocol for data collection of grand battement trials 96 4.2.4 Definitions of variables (body regions) and events 97 4.3 Section 1: Kinematic data 99 4.3.1 Statistical analyses 99 4.3.2 Results 101 4.3.2.1 Stance to Initiation, x-axis 103 4.3.2.2 Initiation to Peak, x-axis 104 4.3.2.3 Peak to End, x-axis 105 4.3.2.4 Stance to Initiation, x-axis 107 4.3.2.5 Initiation to Peak, y-axis 108 4.3.2.6 Peak to End, y-axis 109 4.3.3 Discussion 111 4.3.3.1 Stance to Initiation, x-axis 111 4.3.3.2 Initiation to Peak, x-axis 112 4.3.3.3 Peak to End, x-axis 113 4.3.3.4 Stance to Initiation, x-axis 114 4.3.3.5 Initiation to Peak, y-axis 114 4.3.3.6 Peak to End, y-axis 115 4.4 Section 2: EMG data 117 4.4.1 Statistical analyses 117 4.4.2 Results 118 4.4.2.1 Stance: Muscle x Event x Condition 130 4.4.2.2 Initiation: Muscle x Event x Condition 131 4.4.2.3 Peak: Muscle x Event x Condition 131 4.4.2.4 End: Muscle x Event x Condition 132 4.4.3 Discussion 133 4.4.3.1 Stance: Muscle x Event x Condition 133 4.4.3.2 Initiation: Muscle x Event x Condition 133 4.4.3.3 Peak: Muscle x Event x Condition 134 4.4.3.4 End: Muscle x Event x Condition 134 4.4.3.5 Overview of each muscle for all conditions 135 4.4.3.6 Training levels: Level x Side x Muscle 137 5 Summary 139 5.1 General Conclusions 139 5.2 Limitations of the study 145 3.3 Delimitations of the study 145 5.4 Recommendations for future research 145 References 147 Appendices 156 6 List of Figures and Tables Figures Figure 1 Components of the PAD: testing the abdominals 76 Figure 2 Components of the PAD: testing the gastrocnemius 77 Figure 3 Components of the PAD: testing the abductor hallucis 77 Figure 4 Components of the PAD: testing the erector spinae 78 Figure 5 Components of the PAD: testing the gluteus maximus 78 Figure 6 Components of the PAD: testing the quadriceps 79 Figure 7 Components of the PAD: testing the hamstrings 79 Figure 8 Components of the PAD: testing the tibialis anterior 80 Figure 9 Left gastrocnemius trial: Raw data from sEMG recordings for AB (abdominals), AH (abductor hallucis), ES (erector spinae), GA (gastrocnemius), GM (gluteus maximus), HA (hamstrings), QA (quadriceps), and TA (tibialis anterior) 87 Figure 10 Left gastrocnemius trial: Raw (left) and filtered (right) data from sEMG recordings for GA (gastrocnemius), HA (hamstrings), TA (tibialis anterior), and AH (abductor hallucis) 89 Figure 11 Left gastrocnemius trial: three MVIC trials and ensemble graph This graph shows the composite data of the three trials, with the bold line showing the average 90 Figure 12 Participant with 35 spherical markers using a Plug-in Gait Full Body Marker set 94 Figure 13 Distance from Stance to Initiation in the x-axis 104 Figure 14 Distance from Initiation to GB Peak in the x-axis 105 Figure 15 Distance from GB Peak to End in the x-axis 106 Figure 16 Distance from Stance to Initiation in the y-axis 108 Figure 17 Distance from Initiation to GB Peak in the y-axis 109 Figure 18 Distance from GB Peak to End in the y-axis 110 Figure 19 Graph of left AB by condition by event by level 121 Figure 20 Graph of right AB by condition by event by level 121 Figure 21 Graph of left AH by condition by event by level 122 Figure 22 Graph of right AH by condition by event by level 122 Figure 23 Graph of left ES by condition by event by level 123 Figure 24 Graph of right ES by condition by event by level 123 Figure 25 Graph of left GA by condition by event by level 124 Figure 26 Graph of right GA by condition by event by level 124 Figure 27 Graph of left GM by condition by event by level 125 Figure 28 Graph of right GM by condition by event by level 125 Figure 29 Graph of left HAM by condition by event by level 126 Figure 30 Graph of right HAM by condition by event by level 126 Figure 31 Graph of left QA by condition by event by level 127 Figure 32 Graph of right QA by condition by event by level 127 Figure 33 Graph of left TA by condition by event by level 128 Figure 34 Graph of right TA by condition by event by level 128 7 Tables Table 1 Means and standard deviations in cm for distance of weight transfer for COG Full Trunk, COG Pelvis, COG Upper Trunk, and COM for three intervals: Stance to Initiation, Initiation to Peak, Peak to End 100 Table 2 Significance levels (F values, degrees of freedom, and p values) for the COG Full Trunk, COG Pelvis, COG Upper Trunk, and COM, for all three intervals (STN to GBI, GBI to GBP, and GBP to END) in both axes at α = .05 102 Table 3 Significance levels (p values) for condition pairwise comparisons for COG Full Trunk, COG Pelvis, COG Upper Trunk, and COM for three intervals: Stance to Initiation, Initiation to Peak, Peak to End 103 Table 4 Muscle Activation Variables for All Muscles, Events, and Conditions in all participants 119 Table 5 Linear Mixed Effects Regression Model examining muscle activation for all muscles, events, and conditions in all participants 120 Table 6 Results of Analysis of Muscle X Condition X Event in all participants 129 Table 7 Results (p-values) of Analysis of Muscle X Training Level 130 8 ACKNOWLEDGEMENTS I would like to acknowledge M.