1st Joint ESMAC-GCMAS Meeting - Análise de Marcha

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Results At all speeds, the net influence of stance-side muscles was to slow forward progression during loading response and early single-limb support, and to propel the body forward during late single-limb support and preswing (Fig. 1). Braking and propulsion by stance-side muscles increased with walking speed. Individual muscle contributions to progression reflected this trend (Fig. 2). Discussion We generated subject-specific, muscle-actuated, 3D simulations of a child walking at three speeds. Increased walking speed arose from greater propulsion by hip flexors and ankle plantarflexors during late single-limb support and preswing. A Figure 1. Average fore-aft induced counterintuitive finding was that knee extensors generated accelerations from stance-side muscles. larger braking effects at higher speeds. The braking effects of dorsiflexors at the slowest and fastest walking speed were similar, suggesting unusually high dorsiflexor forces during slow walking. This finding is consistent with a prolonged internal dorsiflexion moment computed from the subject’s experimental data during slow walking. These results suggest that therapies aimed at increasing hip flexor and plantarflexor strength may be beneficial for patients with limited walking speed, since these two muscle groups are primarily responsible for increasing gait speed. Figure 2. Major muscle contributors to braking and propulsion. Top panel: Vasti and dorsiflexors were the primary sources of braking during loading response. Second panel: Vasti, gastrocnemius, and soleus provided braking during early single-limb support, with some assistance from rectus femoris (not shown). Third panel: Gastrocnemius and iliopsoas propelled the body forward during late singlelimb support. Smaller contributions from gluteus minimus, medial hamstrings, peroneal muscles (not shown), soleus, and dorsiflexors also assisted in propulsion, but were inconsistent across walking speeds. Bottom panel: Gastrocnemius, soleus, and iliopsoas provided propulsion during preswing, with smaller contributions from medial hamstrings and peroneal muscles that were inconsistent across walking speeds. References [1] den Otter, et al, (2004), Gait Posture, 19, 270-278 [2] Neptune et al, (2004), Gait Posture, 19, 194-205 [3] Liu et al, (in press), J Biomech [4] Thelen and Anderson, (2006), J Biomech, 39, 6, 1107-1115 - 153 -
O-43 AUTOMATIC IDENTIFICATION OF MUSCLE INSERTION SITES IN MR IMAGES USING ATLAS-BASED, NON-RIGID REGISTRATION Scheys Lennart, M.Sc. 1,2 , Jonkers Ilse 2 , PhD, Loeckx Dirk, M.Sc. 1 , Spaepen Arthur, M.Sc. Prof. 2 ; Suetens Paul, M.Sc. Prof. 1 1 Medical Image Computing - ESAT/PSI, U.Z. Gasthuisberg, Leuven, Belgium 2 Department of Biomedical Kinesiology, FABER/K.U.Leuven, Leuven, Belgium Summary/conclusions Atlas-based non-rigid image registration allows automatic identification of muscle attachments that can be incorporated in subject-specific musculoskeletal models applicable to the biomechanical analysis of gait. Introduction Gait analysis techniques have evolved from research instruments to an indispensable tool in the management of patients suffering from a wide variety of medical conditions. Recent studies show its added value over clinical examination data in selecting a patient-tailored surgical intervention strategy [1]. More recent, newly ‘derived’ parameters, related to musculoskeletal geometry (e.g. muscle length, muscle moment arms) as well as muscle–tendon dynamics (e.g. force generating capacity of muscles), have been introduced in the clinical decision making process. Consequently, generic biomechanical models used to date need to be accommodated for inter-individual variability in musculoskeletal geometry [2], especially when bony deformations and changes in muscle geometry are present. Highly accurate, subject-specific musculoskeletal models can be build using information of magnetic resonance (MR) images [3]. Since manual delineation of soft-tissue structures is required, parameterization of the muscle geometry, with identification of muscle paths from origin to insertion, is a time demanding step. Therefore, this approach is generally considered to be too labour-intensive and high-priced. This work presents the performance of a method to automatically identify muscle geometry (attachments and muscle path) by atlas-based non-rigid image registration. This approach decreases considerably the time required to build subject specific musculoskeletal models based on medical images (MRI) while demonstrating an accuracy comparable to manual delineation. Statement of clinical significance Automatic identification of muscle geometry based on medical imaging enhances the feasibility to build subject specific musculoskeletal models for detailed biomechanical analysis of gait deviations in patients. Methods The current work assumes that muscles can be modelled as a straight line running from origin to insertion, describing the muscle’s lines of action. This approach is based on the muscle model used in SIMM (Software for Interactive Musculoskeletal Modelling, Musculographics Inc.). Therefore, the identification of the attachment and insertion sites of the muscle is a crucial step in the process for which mostly a centroid approach is used. Via non-rigid registration, muscle attachment and insertion sites are identified in T1 MR images of a subject using the information of an atlas (i.e. a MR images from a non-pathologic adult man (25y) with labelled muscle attachments). In a first step the geometrical relation between both image volumes is determined by matching both image volumes using intensitybased non-rigid image registration. The non-rigid deformation of the atlas image is modelled by a B-spline deformation mesh [4]. The cost function uses mutual information [5] as a - 154 -
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O-01 KNEE EXTENSION AT TERMINAL SWI
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O-02 THE MODIFIED TARDIEU IN STANDI
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O-03 COORDINATION BETWEEN PELVIS, T
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O-04 CAN GAIT ANALYSIS GUIDE MANAGE
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O-05 DISTAL FEMORAL EXTENTSION OSTE
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O-06 THE EFFECT OF SHOES ON GAIT IN
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O-07 CORRELATIONS BETWEEN CLINICAL
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O-08 DOUBLE CALIBRATION VS GLOBAL O
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O-09 THE SYMMETRICAL AXIS OF ROTATI
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O-10 FEASIBILITY OF A NEW -JOINT CO
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O-11 A SINGLE GAIT CYCLE AS MEASURE
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O-12 IMPROVED TRACKING OF HIP ROTAT
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O-13 PROTOCOL CHANGES CAN IMPROVE T
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O-14 ALTERNATIVE METHODS FOR MEASUR
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O-15 OVERLAY PROJECTION OF 3D GAIT
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O-16 RELATIONSHIP BETWEEN THE ANTHR
Page 33 and 34: O-17 COMPARING THE RELIABILITY OF V
Page 35 and 36: O-18 3D HIP AND PELVIC GAIT PATTERN
Page 37 and 38: O-19 RELIABILITY AND VALIDITY OF AN
Page 39 and 40: O-20 HOW ACCURATE IS THE ESTIMATION
Page 41 and 42: O-21 IMPACT OF WHEELCHAIR PROPULSIO
Page 43 and 44: O-22 TOWARDS A NEW PROTOCOL FOR MOT
Page 45 and 46: O-23 KINEMATIC ANALYSIS OF UPPER LI
Page 47 and 48: O-24 KINEMATIC UPPER LIMB ANALYSIS
Page 49 and 50: O-25 3D KINEMATICS OF UPPER EXTREMI
Page 51 and 52: O-26 CLINICALLY SIGNIFICANT SHOULDE
Page 53 and 54: O-27 OBJECTIVE IDENTIFCATION OF GAI
Page 55 and 56: - 110 - O-28 NORMALCY GAIT INDEX AN
Page 57 and 58: O-29 GILLETTE GAIT INDEX IS CONSIST
Page 59 and 60: O-30 GAITABASE: NEW APPROACH TO CLI
Page 61 and 62: O-31 A MODIFIED GAIT CLASSIFICATION
Page 63 and 64: O-32 QUANTIFICATION OF KINEMATIC ME
Page 65 and 66: O-33 EXTRINSIC AND INTRINSIC VARIAT
Page 67 and 68: O-34 PAIRED OUTCOME ASSESSMENT OF A
Page 69 and 70: O-35 ENERGY EXPENDITURE DURING OVER
Page 71 and 72: O-36 HIGH FAILURE RATES WHEN AVOIDI
Page 73 and 74: O-37 SUBJECT SPECIFIC HIP GEOMETRY
Page 75 and 76: O-38 BIOMECHANICAL AND METABOLIC PE
Page 77 and 78: O-39 BIOMECHANICS OF GAIT IN CHARCO
Page 79 and 80: O-40 SAGITTAL PLANE LOWER EXTREMITY
Page 81 and 82: O-41 AN EXPLORATION OF THE FUNCTION
Page 83: O-42 DYNAMIC SIMULATIONS OF SLOW, F
Page 87 and 88: O-44 DYNAMIC MEASUREMENT OF GASTROC
Page 89 and 90: O-45 ASSESSING THE REGULATORY ACTIV
Page 91 and 92: O-46 ABNORMAL EMG-ACTIVITY IN PATHO
Page 93 and 94: O-47 AVERAGED EMG PROFILES IN RUNNI
Page 95 and 96: O-48 TRACKING DYNAMIC FOOT PRESSURE
Page 97 and 98: O-49 THE INFLUENCE OF FOOTWEAR SOLE
Page 99 and 100: O-50 GAIT ANALYSIS IN CHILDREN TREA
Page 101 and 102: O-51 A COMPARISON OF METHODS FOR US
Page 103 and 104: O-52 BIOMECHANICAL OPTIMIZATION OF
Page 105 and 106: O-53 EFFECT OF SENSORY-THRESHOLD EL
Page 107 and 108: O-54 THE IMPACT OF SINGLE EVENT MUL
Page 109 and 110: O-55 COMPREHENSIVE GAIT ANALYSIS OU
Page 111 and 112: O-56 THE EFFECT OF INCLUDING S2 ROO
Page 113 and 114: O-57 DYNAMIC FUNCTION AFTER ANTERIO
Page 115 and 116: O-58 RECOVERY OF MUSCLE STRENGTH FO
Page 117 and 118: O-59 AUDITORY-PACED WALKING FOLLOWI
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1st Joint ESMAC-GCMAS Meeting - Análise de Marcha

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