A deep-learning approach for automatically detecting gait-events based on foot-marker kinematics in children with cerebral palsy—Which markers work best for which gait patterns?

Yong Kuk Kim; Rosa MS Visscher; Elke Viehweger; Navrag B Singh; William R Taylor; Florian Vogl

A deep-learning approach for automatically detecting gait-events based on foot-marker kinematics in children with cerebral palsy—Which markers work best for which gait patterns?

Yong Kuk Kim, Rosa MS Visscher, Elke Viehweger, Navrag B Singh, William R Taylor, Florian Vogl

Careum School of Health

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	e0275878
Journal	PLoS ONE
Volume	17
Issue number	10
Publication status	Published - 2022

Cite this

@article{f45cfaeb72104af9b840416bef90927b,

title = "A deep-learning approach for automatically detecting gait-events based on foot-marker kinematics in children with cerebral palsy—Which markers work best for which gait patterns?",

author = "Kim, \{Yong Kuk\} and Visscher, \{Rosa MS\} and Elke Viehweger and Singh, \{Navrag B\} and Taylor, \{William R\} and Florian Vogl",

year = "2022",

language = "English",

volume = "17",

pages = "e0275878",

journal = "PLoS ONE",

issn = "1932-6203",