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Lower limb kinematic changes during a fatiguing 60 min cycling time trial
e142
Saturday 18 October Papers / Journal of Science and Medicine in Sport 18S (2014) e136–e162
hops at 2.2 ± 5% Hz. However, this was significantly lower (p = 0.01) with tactile (13/21) and visual (15/21) feedback and demonstrates a dual-task interference effect. There was a strong correlation between tactile and visual feedback for duration of hopping cycle (Spearman’s r = 0.74, p ≤ 0.01), signifying that either type of feedback resulted in a similar magnitude of dual task interference. Discussion: Although feedback resulted in maintenance of the target hop height, participants were unable to maintain hopping pace. The provision of augmented feedback, commonly used as a motor learning strategy, may result in altering the motor task that was intended to remain constant. http://dx.doi.org/10.1016/j.jsams.2014.11.142
Real-time estimation of lower limb joint angles through inverse kinematics during walking using a scaled OpenSim model C. D.G. Lloyd 1
http://dx.doi.org/10.1016/j.jsams.2014.11.143 18 Lower limb kinematic changes during a fatiguing 60 min cycling time trial
17
Pizzolato 1,∗ ,
Discussion: Real-time IK produced estimates of the joint angles the same as those determined using the offline processing. The small variations present were due to the filtering of trajectories in the offline method that should not affect musculotendon forces estimates. This is the first software to calculate, in real-time, 3D joint angles using the OpenSim IK from an individually scaled anatomical model. This enables real-time estimation muscle and joint contact forces in real-time using our current EMG-driven neuromusculoskeletal models.
M.
Reggiani 2 ,
L.
Modenese 1 ,
1 Centre for Musculoskeletal Research, School of Allied Health Sciences, Griffith Health Institute, Griffith University, Australia 2 Department of Management and Engineering, University of Padua, Italy
Background: Real-time estimates of three-dimensional (3D) joint angles and musculotendon forces can potentially enable rapid patient evaluation and biofeedback for gait retraining. We have recently demonstrated real-time estimation of musculotendon forces using our electromyography (EMG)-driven neuromusculoskeletal models. However, this needs real-time estimation of 3D joint angles using inverse kinematics (IK) in OpenSim software, which involves many processing steps and other software. This preclude it is real-time use. Thus we aimed to (i) develop real-time OpenSim IK procedures, (ii) integrate this within our EMG-driven neuromusculoskeletal models, and (iii) compare the real-time estimation of 3D joint angles and musculotendon forces to those using offline processing. This will ensure real-time estimates are not compromised by marker drop and other specific operations that enable real-time processing. Method: Custom software was written in C++ to read 3D markers trajectories from Vicon motion capture system in real-time. The OpenSim IK algorithm and software was modified to accept these markers trajectories on a frame-by-frame basis. 3D gait data was acquired using a full body marker set (68 markers) for a single subject walking on a treadmill. A static calibration trial was used to initially scale the OpenSim model to the subject’s segmental dimensions. During the walking trials the custom software was used to produce and save the IK joint angles, while the marker trajectories were also saved for subsequent offline processing. The IK joint angles from hip, knee, and ankle determined using the real-time and offline pathways were then compared using a modified coefficient of multiple correlation (CMC), which assessed the similarity of waveforms where a value of 1 indicates maximum similarity. Results: We found similar hip, knee and ankle joint angle waveforms, for three consecutive gait cycles, with CMC’s of 1 for the hip and knee, and 0.998 for the ankle. A delay between the subject’s motion and the real-time calculation of joint angles was approximately 30 ms. The real-time estimation of musculotendon forces is currently being evaluated.
M. Sayers University of the Sunshine Coast, Australia Introduction: The predominant movement patterns in cycling are centred around ankle, knee and hip flexion/extension. Importantly, the cycling action also contains lower limb movements in the frontal (e.g. hip adduction/abduction and knee varus/valgus) and transverse planes (e.g. hip and knee internal/external rotation), with some researchers linking these non-sagittal movements to the relatively high incidence of lower limb overuse injuries in road cycling. Our earlier research has indicated increased variation in tibial rotation variability at the mid-drive phase position during sustained cycling, but the quantification of movement variability using discrete analyses may under, or overestimate the degree of variability present throughout the pedal stroke. Accordingly, the purpose of this study was to quantify the degree of pelvis and lower limb movement variability during sustained cycling using Normalised Root Mean Square (NoRMS) analyses. Methods: Ten experienced male road cyclists (age 36 ± 3.6 years, mass 79.8 ± 5.8 kg, and height 1.817 ± 0.046 m) performed a 60 min cycling test at a workload equivalent to 88% of onset of blood lactate accumulation (OBLA). Previous testing has indicated that this workload enabled the participants to maximise their work output during the 60 min. Three-dimensional kinematic data (200 Hz) were recorded using a 9 camera infra-red motion capture system for 20 pedal revolutions during the last minute of each 10 min period. Analyses focused on lower limb and pelvis kinematics, with NoRMS analyses being used from angle-angle data to quantify pedal stroke consistency. Results: Analysis of the angle-angle graphs indicated that the participants increased the amount of posterior pelvic tilt by approximately 3◦ during the latter stages of the test, which caused a corresponding 5◦ increase in hip flexion throughout the pedal stroke. The greatest changes in angle-angle data were in the transverse plane hip, knee and ankle graphs. Significant increases in NoRMS data were also found in transverse plane hip and knee axial rotations during the latter stages of the test. Discussion: Our results indicated that changes in pelvis orientation and non-sagittal hip and knee kinematics movement patterns occur during sustained cycling. The degree of transverse plane movement variability also increases at some joints during a sustained high intensity ride. Our results may help explain the high incidence of lower back and knee injury experienced by well trained and high performance cyclists. http://dx.doi.org/10.1016/j.jsams.2014.11.144
Saturday 18 October Papers / Journal of Science and Medicine in Sport 18S (2014) e136–e162
hops at 2.2 ± 5% Hz. However, this was significantly lower (p = 0.01) with tactile (13/21) and visual (15/21) feedback and demonstrates a dual-task interference effect. There was a strong correlation between tactile and visual feedback for duration of hopping cycle (Spearman’s r = 0.74, p ≤ 0.01), signifying that either type of feedback resulted in a similar magnitude of dual task interference. Discussion: Although feedback resulted in maintenance of the target hop height, participants were unable to maintain hopping pace. The provision of augmented feedback, commonly used as a motor learning strategy, may result in altering the motor task that was intended to remain constant. http://dx.doi.org/10.1016/j.jsams.2014.11.142
Real-time estimation of lower limb joint angles through inverse kinematics during walking using a scaled OpenSim model C. D.G. Lloyd 1
http://dx.doi.org/10.1016/j.jsams.2014.11.143 18 Lower limb kinematic changes during a fatiguing 60 min cycling time trial
17
Pizzolato 1,∗ ,
Discussion: Real-time IK produced estimates of the joint angles the same as those determined using the offline processing. The small variations present were due to the filtering of trajectories in the offline method that should not affect musculotendon forces estimates. This is the first software to calculate, in real-time, 3D joint angles using the OpenSim IK from an individually scaled anatomical model. This enables real-time estimation muscle and joint contact forces in real-time using our current EMG-driven neuromusculoskeletal models.
M.
Reggiani 2 ,
L.
Modenese 1 ,
1 Centre for Musculoskeletal Research, School of Allied Health Sciences, Griffith Health Institute, Griffith University, Australia 2 Department of Management and Engineering, University of Padua, Italy
Background: Real-time estimates of three-dimensional (3D) joint angles and musculotendon forces can potentially enable rapid patient evaluation and biofeedback for gait retraining. We have recently demonstrated real-time estimation of musculotendon forces using our electromyography (EMG)-driven neuromusculoskeletal models. However, this needs real-time estimation of 3D joint angles using inverse kinematics (IK) in OpenSim software, which involves many processing steps and other software. This preclude it is real-time use. Thus we aimed to (i) develop real-time OpenSim IK procedures, (ii) integrate this within our EMG-driven neuromusculoskeletal models, and (iii) compare the real-time estimation of 3D joint angles and musculotendon forces to those using offline processing. This will ensure real-time estimates are not compromised by marker drop and other specific operations that enable real-time processing. Method: Custom software was written in C++ to read 3D markers trajectories from Vicon motion capture system in real-time. The OpenSim IK algorithm and software was modified to accept these markers trajectories on a frame-by-frame basis. 3D gait data was acquired using a full body marker set (68 markers) for a single subject walking on a treadmill. A static calibration trial was used to initially scale the OpenSim model to the subject’s segmental dimensions. During the walking trials the custom software was used to produce and save the IK joint angles, while the marker trajectories were also saved for subsequent offline processing. The IK joint angles from hip, knee, and ankle determined using the real-time and offline pathways were then compared using a modified coefficient of multiple correlation (CMC), which assessed the similarity of waveforms where a value of 1 indicates maximum similarity. Results: We found similar hip, knee and ankle joint angle waveforms, for three consecutive gait cycles, with CMC’s of 1 for the hip and knee, and 0.998 for the ankle. A delay between the subject’s motion and the real-time calculation of joint angles was approximately 30 ms. The real-time estimation of musculotendon forces is currently being evaluated.
M. Sayers University of the Sunshine Coast, Australia Introduction: The predominant movement patterns in cycling are centred around ankle, knee and hip flexion/extension. Importantly, the cycling action also contains lower limb movements in the frontal (e.g. hip adduction/abduction and knee varus/valgus) and transverse planes (e.g. hip and knee internal/external rotation), with some researchers linking these non-sagittal movements to the relatively high incidence of lower limb overuse injuries in road cycling. Our earlier research has indicated increased variation in tibial rotation variability at the mid-drive phase position during sustained cycling, but the quantification of movement variability using discrete analyses may under, or overestimate the degree of variability present throughout the pedal stroke. Accordingly, the purpose of this study was to quantify the degree of pelvis and lower limb movement variability during sustained cycling using Normalised Root Mean Square (NoRMS) analyses. Methods: Ten experienced male road cyclists (age 36 ± 3.6 years, mass 79.8 ± 5.8 kg, and height 1.817 ± 0.046 m) performed a 60 min cycling test at a workload equivalent to 88% of onset of blood lactate accumulation (OBLA). Previous testing has indicated that this workload enabled the participants to maximise their work output during the 60 min. Three-dimensional kinematic data (200 Hz) were recorded using a 9 camera infra-red motion capture system for 20 pedal revolutions during the last minute of each 10 min period. Analyses focused on lower limb and pelvis kinematics, with NoRMS analyses being used from angle-angle data to quantify pedal stroke consistency. Results: Analysis of the angle-angle graphs indicated that the participants increased the amount of posterior pelvic tilt by approximately 3◦ during the latter stages of the test, which caused a corresponding 5◦ increase in hip flexion throughout the pedal stroke. The greatest changes in angle-angle data were in the transverse plane hip, knee and ankle graphs. Significant increases in NoRMS data were also found in transverse plane hip and knee axial rotations during the latter stages of the test. Discussion: Our results indicated that changes in pelvis orientation and non-sagittal hip and knee kinematics movement patterns occur during sustained cycling. The degree of transverse plane movement variability also increases at some joints during a sustained high intensity ride. Our results may help explain the high incidence of lower back and knee injury experienced by well trained and high performance cyclists. http://dx.doi.org/10.1016/j.jsams.2014.11.144