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A Fitting Solution: An engineering approach to reducing measurement error in clinical gait analysis
Keynote Lecture KN17
S26
A Fitting Solution: An engineering approach to reducing measurement error in clinical gait analysis Richard Baker PhD CEng CSci, Director of the Gait CCRE, Murdoch Childrens Research Institute, Royal Children’s Hospital, Melbourne, Australia Identifying the problem: Several published studies over the last few years have drawn attention to the wide variability of measurements made by different clinical gait analysis laboratories when assessing the same subjects [1-3]. Studies from specialist centres have shown that it is possible to attain acceptable levels of repeatability measurements [4]. The discrepancy between these studies is that our present biomechanical models and highly dependent on the skill and expertise of the person placing the markers. Specifying the problem: Early studies of model repeatability hid this problem by using the Coefficient of Multiple Determination to quantify repeatability. This measure is highly insensitive to even quite large variability in measurements and reports the results in units that are difficult to interpret. A better approach is to determine variance components in degrees using maximum-likelihood estimation based on a multi-level random effects linear statistical model. We are able to clearly specify the problem and have a sensitive tool to investigate whether alternative approaches are more repeatable. Proposing a solution: The conventional Gait Model (CGM) [5-7] is based on simple vector geometry and requires accurate placement of markers over anatomical landmarks which may not be well defined themselves. An alternative technique is kinematic fitting [8-13]which uses functional movement tests to calibrate a linked rigid segment model to the patient reducing the dependence on the definition of the landmarks or the marker placer’s skill in identifying these. Realising the solution: Kinematic fitting allows great flexibility. The kinematic constraints of the links between segments can be chosen and this has been done on the results of a comprehensive review of the relevant literature. Marker locations and functional movements for calibration have been selected on the basis of a review of the literature and pilot studies. Provision of solution: Working in partnership with VICON in Oxford, UK we have developed a model “Kylie” within a broader kinematic fitting environment “OLGA II” which functions as an integrated component of commercially available gait analysis software. This has been tested in a repeatability study and shows results that show better repeatability than obtained by our most experiences and repeatable clinical marker placer.
References [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13]
Noonan et al. Journal of Pediatric Orthopaedics 2003;23:279-287. Gorton et al. Gait and Posture 2001;13:247. Gorton et al.. Gait and Posture 2002;16 (suppl 1):S65-66. Schwartz et al. Gait and Posture 2004;20:196-203. Davis et al. Human Movement Science 1991;10:575-587. Kadaba et al. Journal of Orthopaedic Research 1990;8:383-391. Kadaba et al. Journal of Orthopaedic Research 1989;7:849-860. Sommer H. Journal of Biomechanics 1980;102:311-7. Areblad M. PhD Thesis, Linkoping Institute of Technology, 1990. van der Bogert A et al. Journal of Biomechanics 1994;27:1477-1488. Lu and Connor. Journal of Biomechanics 1999;32:129-134. Charlton et al. Gait and Posture 2004;20:213-21. Reinbolt et al. Journal of Biomechanics 2005;38:621-6.
Journal of Biomechanics 40(S2)
XXI ISB Congress, Plenary Sessions, Tutorials and Keynote Lectures, Thursday 5 July 2007
S26
A Fitting Solution: An engineering approach to reducing measurement error in clinical gait analysis Richard Baker PhD CEng CSci, Director of the Gait CCRE, Murdoch Childrens Research Institute, Royal Children’s Hospital, Melbourne, Australia Identifying the problem: Several published studies over the last few years have drawn attention to the wide variability of measurements made by different clinical gait analysis laboratories when assessing the same subjects [1-3]. Studies from specialist centres have shown that it is possible to attain acceptable levels of repeatability measurements [4]. The discrepancy between these studies is that our present biomechanical models and highly dependent on the skill and expertise of the person placing the markers. Specifying the problem: Early studies of model repeatability hid this problem by using the Coefficient of Multiple Determination to quantify repeatability. This measure is highly insensitive to even quite large variability in measurements and reports the results in units that are difficult to interpret. A better approach is to determine variance components in degrees using maximum-likelihood estimation based on a multi-level random effects linear statistical model. We are able to clearly specify the problem and have a sensitive tool to investigate whether alternative approaches are more repeatable. Proposing a solution: The conventional Gait Model (CGM) [5-7] is based on simple vector geometry and requires accurate placement of markers over anatomical landmarks which may not be well defined themselves. An alternative technique is kinematic fitting [8-13]which uses functional movement tests to calibrate a linked rigid segment model to the patient reducing the dependence on the definition of the landmarks or the marker placer’s skill in identifying these. Realising the solution: Kinematic fitting allows great flexibility. The kinematic constraints of the links between segments can be chosen and this has been done on the results of a comprehensive review of the relevant literature. Marker locations and functional movements for calibration have been selected on the basis of a review of the literature and pilot studies. Provision of solution: Working in partnership with VICON in Oxford, UK we have developed a model “Kylie” within a broader kinematic fitting environment “OLGA II” which functions as an integrated component of commercially available gait analysis software. This has been tested in a repeatability study and shows results that show better repeatability than obtained by our most experiences and repeatable clinical marker placer.
References [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13]
Noonan et al. Journal of Pediatric Orthopaedics 2003;23:279-287. Gorton et al. Gait and Posture 2001;13:247. Gorton et al.. Gait and Posture 2002;16 (suppl 1):S65-66. Schwartz et al. Gait and Posture 2004;20:196-203. Davis et al. Human Movement Science 1991;10:575-587. Kadaba et al. Journal of Orthopaedic Research 1990;8:383-391. Kadaba et al. Journal of Orthopaedic Research 1989;7:849-860. Sommer H. Journal of Biomechanics 1980;102:311-7. Areblad M. PhD Thesis, Linkoping Institute of Technology, 1990. van der Bogert A et al. Journal of Biomechanics 1994;27:1477-1488. Lu and Connor. Journal of Biomechanics 1999;32:129-134. Charlton et al. Gait and Posture 2004;20:213-21. Reinbolt et al. Journal of Biomechanics 2005;38:621-6.
Journal of Biomechanics 40(S2)
XXI ISB Congress, Plenary Sessions, Tutorials and Keynote Lectures, Thursday 5 July 2007