2019
DOI: 10.1007/978-3-030-31635-8_240
|View full text |Cite
|
Sign up to set email alerts
|

Neuromechanical and Environment Aware Machine Learning Tool for Human Locomotion Intent Recognition

Abstract: Current research suggests the emergent need to recognize and predict locomotion modes (LMs) and LM transitions to allow a natural and smooth response of lower limb active assistive devices such as prostheses and orthosis for daily life locomotion assistance. This Master dissertation proposes an automatic and user-independent recognition and prediction tool based on machine learning methods. Further, it seeks to determine the gait measures that yielded the best performance in recognizing and predicting several … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 22 publications
(29 reference statements)
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?