1st Joint ESMAC-GCMAS Meeting - Análise de Marcha

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Results Matching of groups: Relevant clinical data showed that the old and new samples, while substantially different in size (N = 278 new, 995 old), were largely the same in terms of factors likely to impact oxygen cost. For example, distribution of the CP subtypes hemiplegiadiplegia-triplegia-quadriplegia were 12%-68%-13%-7% respectively for the new protocol and 13%-60%-16%-11% respectively for the old protocol. Birth weight, weeks of gestation, and weeks in the neonatal intensive care unit were statistically equal (p>0.05). The O2 cost vs. nondimensional speed regressions showed essentially unchanged polynomial fits for the old and new data, suggesting that the samples were well matched, and the protocols were unbiased [Figure 1]. Reduction of variability: The mean square error (MSE) in the old protocol (MSEold = .262) was substantially higher than that in the new (MSEnew = .050). This represents a ≈5x reduction in variability. The reported MSE reduction does not take into account that fact that 90 outliers with large errors were removed from the old protocol; therefore the “true” MSE reduction is even larger than reported. Net Nondimensional Oxygen Cost 5 4 3 2 1 Old Protocol 0 0.0 0.1 0.2 0.3 0.4 0.5 Nondimensional Speed Figure 1. Cost vs. speed plots show a reduction in variability with the new protocol. The quadratic regression is nearly identical suggesting that the protocols are unbiased and the groups are equivalent. Note that 90 extreme outliers (standardized residuals > 3) were eliminated from the regression fit for the old protocol – no such outliers existed for the new protocol. Thus the variability reduction reported is a conservative estimate. Discussion A protocol utilizing a 10 minute resting period and a statistical determination of steady state substantially reduced the variability in O2 cost data. Decreased variability is likely to lead to greater clinical utility, since smaller changes in O2 cost can be reliably interpreted. Changes in both rest period (duration), and steady state determination (method) occurred. Thus it is not clear how much each factor influenced the improvement. While it is possible that the reduction in variability could be due to differences in samples, the groups appear to be well matched, except for age, where the subjects tested with the new protocol were significantly older than those tested with the old protocol (age = 8.3 yrs. new, 10.9 yrs. old). References 1. Brehm MA and Harlaar J, Proc. 10 th Ann. GCMAS, 2005 2. Schwartz MH et al., Gait Posture, in press. 3. Bowen TR et al., JPO, 18:738-742, 1998. 4. Kendall MG, Time Series, New York, Hafner Press, 1973. - 69 - New Protocol 0.0 0.1 0.2 0.3 0.4 0.5
O-14 ALTERNATIVE METHODS FOR MEASURING TIBIAL TORSION Rozumalski, Adam, MS 1 , Sohrweide, Sue, PT 1 , Schwartz, Michael, PhD 1,2 1 Gillette Childrens Specialty Healthcare, St Paul, MN USA 2 University of Minnesota, Minneapolis, MN USA Summary/conclusions This study introduces several new techniques for determining tibial torsion using motion analysis data. Analysis of correlations suggests that the new techniques may be more clinically valuable than the traditional bi-malleolar axis measurement. Introduction Long bone torsions are notoriously difficult to measure [1]. The most common measure of tibial torsion is the bi-malleolar axis angle. Bony landmark ambiguities combine with line-ofsight problems resulting in an angle that is hard to accurately measure. Efforts to reduce the variability in several torsion measurements within the Gillette Children’s Specialty Healthcare Center for Gait and Motion Analysis have been largely unsuccessful. This study uses motion analysis data to determine estimates of knee and ankle axes and thereby estimate tibial torsion. These “technical” measurements can be compared to the bi-malleolar axis angle. Statement of clinical significance Better methods for measuring tibial torsion can lead to improved clinical decisions regarding tibial derotational osteotomies. Determination of tibial torsion using motion analysis data appears to be more useful than a bi-malleolar axis measurement. Methods Data from 20 young, able-bodied volunteers was used in this study (ages 5-14 yrs). Four different tibial torsion measurements were acquired; one from a physical exam and three from motion analysis data. For the physical exam measure, the bi-malleolar axis angle was used. For the motion analysis methods the locations of the medial and lateral malleoli were estimated using virtual circles [2]. The centers of those virtual circles were then used to define a bimalleolar axis. The knee axis was estimated using three different techniques. The first used the center of a virtual circle around the medial femoral condyle and a physical knee marker (virtual knee axis). The second was determined via placement of a knee alignment device (KAD knee axis). The third used a functional method (functional knee axis) described by Schwartz, et al. [3]. Note that the functional knee axis is defined independently from the virtual and KAD knee axes. For the tibial torsion measures calculated from the motion analysis data, the ankle and knee axes were projected onto a plane perpendicular to the long axis of the tibia. Tibial torsion was then taken to be the average of the angle between the projected knee and ankle axes during a static trial. Results The results show that there is no significant correlation (p > 0.05) between physical exam based tibial torsion and tibial torsion measured using the motion analysis data [Figure 1]. It is also shown that the three motion analysis based measurements are significantly correlated to each other (p < 0.01). - 70 -
Page 1 and 2: O-01 KNEE EXTENSION AT TERMINAL SWI
Page 3 and 4: O-02 THE MODIFIED TARDIEU IN STANDI
Page 5 and 6: O-03 COORDINATION BETWEEN PELVIS, T
Page 7 and 8: O-04 CAN GAIT ANALYSIS GUIDE MANAGE
Page 9 and 10: O-05 DISTAL FEMORAL EXTENTSION OSTE
Page 11 and 12: O-06 THE EFFECT OF SHOES ON GAIT IN
Page 13 and 14: O-07 CORRELATIONS BETWEEN CLINICAL
Page 15 and 16: O-08 DOUBLE CALIBRATION VS GLOBAL O
Page 17 and 18: O-09 THE SYMMETRICAL AXIS OF ROTATI
Page 19 and 20: O-10 FEASIBILITY OF A NEW -JOINT CO
Page 21 and 22: O-11 A SINGLE GAIT CYCLE AS MEASURE
Page 23 and 24: O-12 IMPROVED TRACKING OF HIP ROTAT
Page 25: O-13 PROTOCOL CHANGES CAN IMPROVE T
Page 29 and 30: O-15 OVERLAY PROJECTION OF 3D GAIT
Page 31 and 32: 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 and 84:
O-42 DYNAMIC SIMULATIONS OF SLOW, F
Page 85 and 86:
O-43 AUTOMATIC IDENTIFICATION OF MU
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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