Research seminar

Research Seminar: Deep learning for gait analysis

Seminar with Kjartan Halvorsen, affiliated researcher at the School of Health and Welfare.
Date: , kl 10:30 - 12:00
Location: Eva Ekeblad, and online (Zoom)

Deep Learning in Gait Analysis

Speaker: Kjartan Halvorsen

Room: Eva Ekeblad

Zoom: join samtal130

Abstract:  Gait analysis is a widely used method to quantitatively describe and study gait, and to determine the effect of medical, surgical and physio-therapeutic interventions to improve the gait of patients.  Traditionally, the gait has been captured using laboratory-based camera systems or sets of wearable sensors, and has involved substantial manual steps to obtain results that can be interpreted clinically. Machine learning, and in particular deep learning opens up for new ways to analyze data collected for gait analysis. These new methods claim to automatize the extraction of gait-related variables from raw data, classify types of gaits, and even to provide quantitative assessment of gait deviation. We can expect a fast-increasing interest in the application of machine learning and deep learning for gait analysis.




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Senior Lecturer Information and Communications Technology
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