1st Joint ESMAC-GCMAS Meeting - Análise de Marcha

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likelihood estimation was used in Stata 9.1 statistical software to estimate these models. The model was extended to analyse data from all points in the gait cycle simultaneously by including fixed effects for percentage point of the gait cycle. Results Inter-trial, inter-session and total error estimates (incorporating both trial and session variability) varied across gait parameters and assessors. As an example, Figure 1 illustrates differences in total pelvic tilt error from the 6 assessors. The magnitude of error in key gait parameters appeared related to experience, with the most experienced (ME) assessors generally recording lower errors than less experienced (LE) assessors. This was particularly evident in key parameters sensitive to marker misplacement such as pelvic tilt (ME 2.5deg), hip rotation (ME 5 deg) and foot progression (ME 2 deg). Standard deviation (deg) Total variability 0 1 2 3 0 1 2 3 Pelvic Tilt: Total of session and trial variability 0 50 100 0 50 % of gait cycle 100 0 50 100 Figure 1: Errors in pelvic tilt for a single subject measured by 6 assessors. Each graph represents the total of session and trial variability from a single assessor Discussion Quantification of the error sources associated with 3D analysis has varied applications. Knowledge of a single assessor’s typical inter-session error may be relevant in laboratories with a single staff assessor, or where a designated assessor routinely repeats 3DGA on patients returning for evaluations. Determination of inter-assessor error within a laboratory will assist in defining gait parameters which reflect systematic assessor deviations in marker placement protocols. Evaluation of inter-assessor error within and across laboratories is relevant for multi-centre collaborative research and in construction of shared gait databases. Quantitative feedback of individual and within-laboratory assessor reliability offers opportunities to more specifically direct quality assurance activities including biomechanical model review and marker placement training and practice. This method may also permit a closer evaluation of the relationships between assessor experience, training and error profiles. This report uses data from a single unimpaired subject to illustrate the potential application of this approach. The techniques are equally applicable to multiple subjects from relevant clinical populations with gait pathology. References [1] Gorton G et al. (2002) Gait and Posture,16 (suppl 1): p. S65-66. [2] Schwartz MH et al. (2004), Gait and Posture, 20, 296-203. [3] Dunn G (2004) Statistical Evaluation of Measurement Errors. - 119 -
O-33 EXTRINSIC AND INTRINSIC VARIATION IN KINEMATIC DATA FROM THE GAIT OF HEALTHY ADULT SUBJECTS Eve Linda, McNee Anne, Shortland Adam One Small Step Gait Laboratory, Guy’s Hospital, London, UK Summary/Conclusions 3D kinematic data from 10 healthy adult subjects were collected from 3 sessions within a week. In one session, marker placement was guided by indelible pen marks made on the subjects in a data collection 2 days previously. Using this experimental design, we were able to distinguish variation due to marker placement and that due to the intrinsic variation of human walking. We found that, under near ideal circumstances, marker placement accounted for only a small amount of inter-sessional variation, with the greater proportion due to intrinsic differences in the gait patterns of the study subjects. Introduction 3D gait analysis is used clinically to assist treatment planning and assess outcome following intervention. The ability to report changes in gait with confidence is reliant on repeatable data collection. The validity of gait analysis has been questioned (1,2) with variation in the data collected, in the interpretation of the results and in the subsequent recommendations. Previous studies have reported better repeatability in kinematic data recorded on the same day than from sessions recorded on different days, with the greater variability attributed to marker placement (3,4,5,6). In this study, we wished to quantify the variation in kinematic data due to marker placement and the intrinsic inter-sessional variability of normal walking. Statement of clinical significance Our results suggest when a single therapist applies retroreflective markers on subjects of moderate body-mass index, the portion of the inter-sessional standard error due to marker misplacement is less than 0.3 degrees for a set of commonly used kinematic variables. Most of the inter-sessional variation observed in pathological groups is likely to be due to intrinsic variation in human walking. Methods 3D gait data was collected from 10 adult volunteers (mean age 31.4 years, mean BMI 22.65), with no history of musculo-skeletal abnormality, using Vicon 612 motion analysis system. A lower limb marker set was applied (modified Helen Hayes), by the same experienced therapist to each subject, on 3 separate occasions within a week. On one of the occasions, indelible ink was used to mark the skin over the anatomical locations prior to application of the marker set. These pen marks were then used to guide the marker placement for the subsequent data collection session 2 days later. One other data collection session was conducted two days before or after the marked sessions (randomised). The ink marks made on the skin were not visible during this session. In each session, data were collected during five walking trials with the subjects walking at their own self selected speed. Data were processed using the plug-ingait model (Vicon Workstation) at which time thigh rotation was adjusted to correct the knee varus curve in swing (7). The intra- and inter- sessional standard errors (SEs) were calculated (6) for each of 9 commonly-used kinematic variables and for a combination of all these variables (Table 1). The average SE over the gait cycle was calculated for those trials belonging to a single session (intra-sessional), for those trials in marked and unmarked sessions (inter-sessional, including marker error), and for those belonging to the two marked sessions (inter-sessional, excluding marker error). Data were analysed using a two factor ANOVA (subjects, source of error). Post-hoc paired t-tests were conducted to establish if there were significant differences in the size of the error sources. - 120 -
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 and 26: O-13 PROTOCOL CHANGES CAN IMPROVE T
Page 27 and 28: O-14 ALTERNATIVE METHODS FOR MEASUR
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: O-32 QUANTIFICATION OF KINEMATIC ME
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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