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Jaap H. van Dieën

Researcher at VU University Amsterdam

Publications -  482
Citations -  20482

Jaap H. van Dieën is an academic researcher from VU University Amsterdam. The author has contributed to research in topics: Trunk & Gait (human). The author has an hindex of 70, co-authored 452 publications receiving 17247 citations. Previous affiliations of Jaap H. van Dieën include University of British Columbia & University of Mannheim.

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Pelvis-thorax coordination in the transverse plane during walking in persons with nonspecific low back pain.

TL;DR: In this article, the effect of walking velocity on pelvis and thorax rotations in patients with low back pain was examined, and spectral analysis was performed to identify clinically useful measures for characterizing the quality of walking.
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Speeding up or slowing down?: Gait adaptations to preserve gait stability in response to balance perturbations

TL;DR: Not a lower walking speed, but a combination of decreased step length and increased step frequency and step width seems to be the strategy of choice to cope with medio-lateral balance perturbations, which increases MoS and thus decreases the risk of falling.
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Coordination of leg swing, thorax rotations, and pelvis rotations during gait: The organisation of total body angular momentum

TL;DR: The shift in pelvis-thorax coordination from in-phase to out of phase with increasing velocity was found to depend on the pelvis beginning to move in- phase with the femur, while the thorax continued to counter rotate with respect to the Femur.
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Steps to Take to Enhance Gait Stability: The Effect of Stride Frequency, Stride Length, and Walking Speed on Local Dynamic Stability and Margins of Stability

TL;DR: It is concluded that adaptations in stride frequency, stride length and/or walking speed can result in an increase of the medio-lateral and backward margins of stability, while these adaptations do not seem to affect local dynamic stability.
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Ambulatory Fall-Risk Assessment: Amount and Quality of Daily-Life Gait Predict Falls in Older Adults

TL;DR: Daily-life accelerometry contributes substantially to the identification of individuals at risk of falls, and can predict falls in 6 months with good accuracy, according to retrospective and prospective analyses.