Coffee Talk – Innovation in gait analysis
This is a past event Grab your coffee and join us!
- Practical & interactive – exclusive insights and direct questions to experts.
- Relaxed & inspiring – Get the latest insights into gait analysis over a coffee.
- Networking & ideas – exchange ideas and discover new impulses.
15. May 4pmΙ MoveD – Open Research Data
Speaker: Michelle Haas PhD Student University Basel
The structured publication of data with complete metadata is becoming increasingly important – also in motion analysis. But how can transparent and sustainable data documentation be achieved?
In this webinar, the guidelines for Open Research Data developed by the ZHAW Zurich University of Applied Sciences will be presented. They provide valuable guidance for research teams and laboratories and accompany the entire data life cycle.
What the guidelines offer:
- Clear orientation: support with the documentation of data and metadata
- Tried and tested approaches: Tested in a joint project of ZHAW, ZHdK & Sphery
- Best-Practice: Presented as a Case Study for the 40th anniversary of Vicon
05. June 4pm Ι Computer Vision for movement analysis in everyday clinical practice
Speaker: Tim Unger PHD Student DART Lab @ LLUI / RELab ETH Zurich
WiHow reliable is markerless motion capture compared to conventional optical systems? A new type of markerless motion capture pipeline has been tested in recent months – based on just five webcams, evaluated on a data set from two years of research.
In this webinar, the results of the research will be presented and there will be exciting insights into the technical implementation, the validity of the system and the clinical applicability.
- Optic vs. markerless Motion Capture– Comparison of biomechanical models & joint kinematics
- Validation using a clinical example – analysing stroke patients during a drinking task
- Challenges & next steps- How can this technology be integrated into clinical practice?
19. June 4pm Ι IntellEvent: Deep learning-based algorithm for gait event recognition
Speaker: Bernhard Dumphart Junior Researcher Institute for Health Sciences
IntellEvent is a deep learning-based algorithm for the precise detection of gait events such as initial contact (IC) and foot off (FO) – with an accuracy of ≥99% and ≥95% respectively in just a few milliseconds. In this webinar, we will show how IntellEvent outperforms conventional methods and can also be used reliably for complex pathological gait patterns.
- Deep learning-based gait event recognition – comparison with traditional methods
- Reliability for pathological gait patterns – application for clubfoot, cerebral palsy and moreehr
- Challenges & next steps – How can IntellEvent be integrated into clinical practice?
