An automated deep learning-based gait event detection algorithm for various pathologies

Bernhard Dumphart, D. Slijepcevic , F. Unglaube, Andreas Kranzl, Arnold Baca, Matthias Zeppelzauer, Brian Horsak

Publications: Contribution to journal › Article › Peer Reviewed

Austrian Fields of Science 2012

@article{4077024f99e8474ab401d58a7e0b8375,

title = "An automated deep learning-based gait event detection algorithm for various pathologies",

author = "Bernhard Dumphart and D. Slijepcevic and F. Unglaube and Andreas Kranzl and Arnold Baca and Matthias Zeppelzauer and Brian Horsak",

year = "2021",

month = oct,

doi = "10.1016/j.gaitpost.2021.09.026",

language = "English",

volume = "90",

pages = "50--51",

journal = "Gait \& Posture",

issn = "0966-6362",

publisher = "ELSEVIER IRELAND LTD",

number = "Supplement 1",

}

TY - JOUR

T1 - An automated deep learning-based gait event detection algorithm for various pathologies

AU - Dumphart, Bernhard

AU - Slijepcevic , D.

AU - Unglaube, F.

AU - Kranzl, Andreas

AU - Baca, Arnold

AU - Zeppelzauer, Matthias

AU - Horsak, Brian

PY - 2021/10

Y1 - 2021/10

U2 - 10.1016/j.gaitpost.2021.09.026

DO - 10.1016/j.gaitpost.2021.09.026

M3 - Article

SN - 0966-6362

VL - 90

SP - 50

EP - 51

JO - Gait & Posture

JF - Gait & Posture

IS - Supplement 1

ER -