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Automated video-based movement assessment

Automated video-based movement assessment using machine learning to support personalized treatment of movement disorders

Smartphone based medical measurements

We developed a a machine learning pipeline to train models to automatically assess dystonia and choreoathetosis of children with dyskinetic cerebral palsy using 2D coordinates of body points extracted from videos.

Participating organisations

Amsterdam University Medical Centers, location VU
Moveshelf b.v.
Netherlands eScience Center
Life Sciences
Life Sciences

Impact

How machine learning could help Simone to play Ludo

Author(s): Netherlands eScience Center
Published in 2022

Output

A letter to my parents about my experience in a machine learning consultancy project

Author(s): Sven van der Burg
Published in 2022

Team

HH
Helga Haberfehlner
AB
Annemieke Buizer
co-Applicant
VU University Medical Center
IA
Ignazio Aleo
co-Applicant
Moveshelf b.v.
LB
Laura Bonouvrié
MvdK
Marjolein van der Krogt
SvdV
Shankara van de Ven
Florian Huber
Florian Huber
eScience Research Engineer
Netherlands eScience Center
Sonja Georgievska
Sonja Georgievska
Senior eScience Research Engineer
Netherlands eScience Center
Sven van der Burg
Sven van der Burg
eScience Research Engineer
Netherlands eScience Center
Jisk Attema
Programme Manager
Netherlands eScience Center

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