Publication date: Available online 5 September 2016
Source:Gait & Posture
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Δευτέρα 5 Σεπτεμβρίου 2016
Sagittal knee range of motion and gait speed recovery one year after total knee arthroplasty: Influence of BMI
Publication date: Available online 5 September 2016
Source:Gait & Posture
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Source:Gait & Posture
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Age-related changes in continuous kinematic and kinetic waveforms in typical developing children and adults
Publication date: Available online 5 September 2016
Source:Gait & Posture
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Source:Gait & Posture
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Does correction of femoral lever-arm influence the effect of Selective Dorsal Rhizotomy on gait in children with spastic Cerebral Palsy?
Publication date: Available online 5 September 2016
Source:Gait & Posture
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Source:Gait & Posture
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Patella tendon shortening for the correction of flexed knee gait in cerebral palsy – A randomized controlled trial
Publication date: Available online 5 September 2016
Source:Gait & Posture
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Source:Gait & Posture
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Time series of ground reaction forces following a single leg drop jump landing in elite youth soccer players consist of four distinct phases
Publication date: Available online 4 September 2016
Source:Gait & Posture
Author(s): Duncan P. Fransz, Arnold Huurnink, Vosse A. de Boode, Idsart Kingma, Jaap H. van Dieën
The single leg drop jump landing test may assess dynamic and static balance abilities in different phases of the landing. However objective definitions of different phases following landing and associated reliability are lacking.Therefore, we determined the existence of possible distinct phases of single leg drop jump landing on a force plate in 82 elite youth soccer players. Three outcome measures were calculated over moving windows of five sizes: center of pressure (COP) speed, COP sway and horizontal ground reaction force (GRF).Per outcome measure, a Factor Analysis was employed with all windows as input variables. It showed that four factors (patterns of variance) largely (>75%) explained the variance across subjects/trials along the 12s time series. Each factor was highly associated with a distinct phase of the time series signal: dynamic (0.4–2.7s), late dynamic (2.5–5.0s), static 1 (5.0–8.3s) and static 2 (8.1–11.7s).Intra-class correlations (ICC) between trials were lower for the dynamic phases (0.45–0.68) than for the static phases (0.60–0.86). The COP speed showed higher ICC’s (0.63–0.86) than COP sway (0.45–0.61) and GRF (0.57–0.71) for all four phases.In conclusion, following a drop jump landing unique information is available in four distinct phases. The COP speed is most reliable, with higher reliability in the static phases compared to the dynamic phases. Future studies should assess the sensitivity of information from dynamic, late dynamic and static phases.
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Source:Gait & Posture
Author(s): Duncan P. Fransz, Arnold Huurnink, Vosse A. de Boode, Idsart Kingma, Jaap H. van Dieën
The single leg drop jump landing test may assess dynamic and static balance abilities in different phases of the landing. However objective definitions of different phases following landing and associated reliability are lacking.Therefore, we determined the existence of possible distinct phases of single leg drop jump landing on a force plate in 82 elite youth soccer players. Three outcome measures were calculated over moving windows of five sizes: center of pressure (COP) speed, COP sway and horizontal ground reaction force (GRF).Per outcome measure, a Factor Analysis was employed with all windows as input variables. It showed that four factors (patterns of variance) largely (>75%) explained the variance across subjects/trials along the 12s time series. Each factor was highly associated with a distinct phase of the time series signal: dynamic (0.4–2.7s), late dynamic (2.5–5.0s), static 1 (5.0–8.3s) and static 2 (8.1–11.7s).Intra-class correlations (ICC) between trials were lower for the dynamic phases (0.45–0.68) than for the static phases (0.60–0.86). The COP speed showed higher ICC’s (0.63–0.86) than COP sway (0.45–0.61) and GRF (0.57–0.71) for all four phases.In conclusion, following a drop jump landing unique information is available in four distinct phases. The COP speed is most reliable, with higher reliability in the static phases compared to the dynamic phases. Future studies should assess the sensitivity of information from dynamic, late dynamic and static phases.
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Accelerometer-based determination of gait variability in older adults with knee osteoarthritis
Publication date: October 2016
Source:Gait & Posture, Volume 50
Author(s): Christian A. Clermont, John M. Barden
Knee osteoarthritis (KOA) can affect the spatiotemporal (ST) aspects of gait as well as the variability of select ST parameters based on standard linear measures of variability (e.g., standard deviation (SD) and coefficient of variation). Non-linear measures (e.g., fractal scaling index (FSI) and sample entropy) can be more sensitive to changes in gait variability, and have been used to quantify differences in the stride patterns of patients with Parkinson’s disease and the motion of ACL-deficient knees. However, the effect of KOA on the dynamic complexity of the stride pattern has not been investigated. Therefore, the purpose of this study was to investigate the effect of KOA on gait variability (linear and non-linear measures) in a group of older adults, and to compare these results to a healthy control group. Participants walked for 10min with a tri-axial accelerometer placed at the lower back. Mean and SDs of stride time and step time as well as the FSI for the entire series of stride times were calculated for each participant. Participants with KOA had significantly greater mean stride time (p=0.031) and step time (p=0.024) than control group participants. While stride and step time variability (SD) were greater in the KOA group, the differences were not significant, nor was the difference in the FSI. Low statistical power (β=0.40 and 0.30 for stride and step time SD, respectively) combined with the confounding effects of walking speed and heterogeneous KOA severity likely prevented significant differences from being found.
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Source:Gait & Posture, Volume 50
Author(s): Christian A. Clermont, John M. Barden
Knee osteoarthritis (KOA) can affect the spatiotemporal (ST) aspects of gait as well as the variability of select ST parameters based on standard linear measures of variability (e.g., standard deviation (SD) and coefficient of variation). Non-linear measures (e.g., fractal scaling index (FSI) and sample entropy) can be more sensitive to changes in gait variability, and have been used to quantify differences in the stride patterns of patients with Parkinson’s disease and the motion of ACL-deficient knees. However, the effect of KOA on the dynamic complexity of the stride pattern has not been investigated. Therefore, the purpose of this study was to investigate the effect of KOA on gait variability (linear and non-linear measures) in a group of older adults, and to compare these results to a healthy control group. Participants walked for 10min with a tri-axial accelerometer placed at the lower back. Mean and SDs of stride time and step time as well as the FSI for the entire series of stride times were calculated for each participant. Participants with KOA had significantly greater mean stride time (p=0.031) and step time (p=0.024) than control group participants. While stride and step time variability (SD) were greater in the KOA group, the differences were not significant, nor was the difference in the FSI. Low statistical power (β=0.40 and 0.30 for stride and step time SD, respectively) combined with the confounding effects of walking speed and heterogeneous KOA severity likely prevented significant differences from being found.
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