Workshops & Symposia
Workshops
The pre-conference workshops will take place on Monday August 19th at the Chateau Lacombe and are open to all registered delegates of CSB-SCB 2024. Delegates can indicate interest in attending the workshops during the registration process.
Workshop:
Recurrence quantification analysis for movement science
Aaron Likens, Seung Kyeom Kim, Tyler Wiles, Kolby Brink
University of Nebraska at Omaha
1:00pm – 5:00pm, Chateau Lacombe
Human movement entails coordination across many components (e.g., limbs, neural activity, and respiration), typically assessed using linear analyses (e.g., mean and standard deviation). However, these methods fail to capture changes in movements and coordination due to factors like age, disease, and context. To address the limitation, modern time series methods are needed that can reveal insights into how movement patterns change over time and covary with physiological processes. This workshop will introduce both basic and advanced forms of Recurrence Quantification Analysis (RQA). Attendees will learn the theories underlying RQA and its application on biological data. College-level algebra and a basic proficiency with MATLAB is recommended but not required. Attendees of all backgrounds including researchers, clinicians, and students of all levels are encouraged to attend.
Workshop:
Markerless motion capture best practices and considerations
Peter Sheahan, Jereme Outerlays
Theia Markerless
Queen’s University
12:30pm – 2:30pm, Chateau Lacombe
Presenters will discuss practical considerations for lab and field-based data collections with Theia3D.
Workshop:
Quantifying form of form-function relationships through statistical shape modelling
Allison Clouthier, Erin Lee, Michael Rainbow, Lauren Welte
University of Ottawa, Queen’s University, University of Alberta
3:00pm – 5:00pm, Chateau Lacombe
Bone and joint geometry play a key role in joint movement patterns and loading. A myriad of methods can quantify differences in shape, which fit under the umbrella of statistical shape modelling (SSM). We will introduce statistical shape modeling and experts in the field will provide a brief overview of SSM’s many applications. Next, we will cover the basics of statistical shape analysis with a simple hands-on MATLAB demo. Time will be provided to build and visualize a bone-based statistical shape model, from an open source database.
Symposia
The symposia sessions will take place during the conference program dates at the Chateau Lacombe and are open to all registered delegates of CSB-SCB 2024. The symposia sessions will take place in parallel with other contributed oral and awards sessions.
Symposium:
The clinical potential of markerless motion capture -Bringing biomechanics to the clinic
Elizabeth Condliffe, Elise Laende, Sachita Wijekoon, Stephen Scott, Dylan Kobsar, Jereme Outerleys
University of Calgary, University of Waterloo, Queen’s University, McMaster University
Markerless motion capture technology provides a potential solution to capturing biomechanical metrics in a clinical setting. This symposium aims to highlight the opportunities and challenges with using markerless motion capture to augment clinical assessments for patients with neurological or musculoskeletal disorders such as cerebral palsy, stroke, and osteoarthritis.
Symposium:
Big data in biomechanics: Challenges and opportunities
Scott Selbie, Jereme Outerleys, Kyle Wasserberger, Richard Moulton
Theia Markerless Inc, Queen’s University, Driveline Baseball, HAS-Motion
The advent of markerless motion capture has enabled researchers to collect much larger datasets than was possible using marker-based technologies. Markerless technologies have also opened the door for in-game tracking, multi-center trials, and reprocessing historical data, all of which have the potential to overwhelm current methods for managing biomechanical data as well as the tools we use for analysis. This symposium will bring together researchers and practitioners who are on the forefront of addressing these challenges to share their experiences and invite a discussion with the audience regarding how we can address the challenges inherent in big data and capitalize on the opportunities for biomechanics research.