Rosa M S Visscher1, Sailee Sansgiri2, Marie Freslier3, Jaap Harlaar4, Reinald Brunner5, William R Taylor6, Navrag B Singh7. 1. Laboratory for Movement Biomechanics, Institute for Biomechanics, ETH Zurich, Leopold-Ruzicka-Weg 4, 8093, Zurich, Switzerland. Electronic address: rosa.visscher@hest.ethz.ch. 2. Department of Biomechanical Engineering, Delft University of Technology, Delft, The Netherlands & Dept. Orthopaedics, Erasmus Medical Center, Rotterdam, The Netherlands. Electronic address: S.Sansgiri@student.tudelft.nl. 3. Laboratory of Movement Analysis, University Children's Hospital Basel (UKBB), University of Basel, Spitalstrasse 33, 4056, Basel, Switzerland. Electronic address: marie.freslier@ukbb.ch. 4. Department of Biomechanical Engineering, Delft University of Technology, Delft, The Netherlands & Dept. Orthopaedics, Erasmus Medical Center, Rotterdam, The Netherlands. Electronic address: j.harlaar@tudelft.nl. 5. Laboratory of Movement Analysis, University Children's Hospital Basel (UKBB), University of Basel, Spitalstrasse 33, 4056, Basel, Switzerland. Electronic address: reinaldbrunner@sunrise.ch. 6. Laboratory for Movement Biomechanics, Institute for Biomechanics, ETH Zurich, Leopold-Ruzicka-Weg 4, 8093, Zurich, Switzerland. Electronic address: bt@ethz.ch. 7. Laboratory for Movement Biomechanics, Institute for Biomechanics, ETH Zurich, Leopold-Ruzicka-Weg 4, 8093, Zurich, Switzerland. Electronic address: navragsingh@ethz.ch.
Abstract
BACKGROUND: To analyse and interpret gait patterns in pathological paediatric populations, accurate determination of the timing of specific gait events (e.g. initial contract - IC, or toe-off - TO) is essential. As currently used clinical identification methods are generally subjective, time-consuming, or limited to steps with force platform data, several techniques have been proposed based on processing of marker kinematics. However, until now, validation and standardization of these methods for use in diverse gait patterns remains lacking. RESEARCH QUESTIONS: 1) What is the accuracy of available kinematics-based identification algorithms in determining the timing of IC and TO for diverse gait signatures? 2) Does automatic identification affect interpretation of spatio-temporal parameters?. METHODS: 3D kinematic and kinetic data of 90 children were retrospectively analysed from a clinical gait database. Participants were classified into 3 gait categories: group A (toe-walkers), B (flat IC) and C (heel IC). Five kinematic algorithms (one modified) were implemented for two different foot marker configurations for both IC and TO and compared with clinical (visual and force-plate) identification using Bland-Altman analysis. The best-performing algorithm-marker configuration was used to compute spatio-temporal parameters (STP) of all gait trials. To establish whether the error associated with this configuration would affect clinical interpretation, the bias and limits of agreement were determined and compared against inter-trial variability established using visual identification. RESULTS: Sagittal velocity of the heel (Group C) or toe marker configurations (Group A and B) was the most reliable indicator of IC, while the sagittal velocity of the hallux marker configuration performed best for TO. Biases for walking speed, stride time and stride length were within the respective inter-trial variability values. SIGNIFICANCE: Automatic identification of gait events was dependent on algorithm-marker configuration, and best results were obtained when optimized towards specific gait patterns. Our data suggest that correct selection of automatic gait event detection approach will ensure that misinterpretation of STPs is avoided.
BACKGROUND: To analyse and interpret gait patterns in pathological paediatric populations, accurate determination of the timing of specific gait events (e.g. initial contract - IC, or toe-off - TO) is essential. As currently used clinical identification methods are generally subjective, time-consuming, or limited to steps with force platform data, several techniques have been proposed based on processing of marker kinematics. However, until now, validation and standardization of these methods for use in diverse gait patterns remains lacking. RESEARCH QUESTIONS: 1) What is the accuracy of available kinematics-based identification algorithms in determining the timing of IC and TO for diverse gait signatures? 2) Does automatic identification affect interpretation of spatio-temporal parameters?. METHODS: 3D kinematic and kinetic data of 90 children were retrospectively analysed from a clinical gait database. Participants were classified into 3 gait categories: group A (toe-walkers), B (flat IC) and C (heel IC). Five kinematic algorithms (one modified) were implemented for two different foot marker configurations for both IC and TO and compared with clinical (visual and force-plate) identification using Bland-Altman analysis. The best-performing algorithm-marker configuration was used to compute spatio-temporal parameters (STP) of all gait trials. To establish whether the error associated with this configuration would affect clinical interpretation, the bias and limits of agreement were determined and compared against inter-trial variability established using visual identification. RESULTS: Sagittal velocity of the heel (Group C) or toe marker configurations (Group A and B) was the most reliable indicator of IC, while the sagittal velocity of the hallux marker configuration performed best for TO. Biases for walking speed, stride time and stride length were within the respective inter-trial variability values. SIGNIFICANCE: Automatic identification of gait events was dependent on algorithm-marker configuration, and best results were obtained when optimized towards specific gait patterns. Our data suggest that correct selection of automatic gait event detection approach will ensure that misinterpretation of STPs is avoided.
Authors: Tecla Bonci; Francesca Salis; Kirsty Scott; Lisa Alcock; Clemens Becker; Stefano Bertuletti; Ellen Buckley; Marco Caruso; Andrea Cereatti; Silvia Del Din; Eran Gazit; Clint Hansen; Jeffrey M Hausdorff; Walter Maetzler; Luca Palmerini; Lynn Rochester; Lars Schwickert; Basil Sharrack; Ioannis Vogiatzis; Claudia Mazzà Journal: Front Bioeng Biotechnol Date: 2022-06-02
Authors: Yong Kuk Kim; Rosa M S Visscher; Elke Viehweger; Navrag B Singh; William R Taylor; Florian Vogl Journal: PLoS One Date: 2022-10-13 Impact factor: 3.752