TY - CHAP
T1 - Detection of subject’s intention to trigger transitions between sit, stand and walk with a lower limb exoskeleton
AU - Trincado-Alonso, Fernando
AU - del Ama-Espinosa, Antonio J.
AU - Asín-Prieto, Guillermo
AU - Piñuela-Martín, Elisa
AU - Pérez-Nombela, Soraya
AU - Gil-Agudo, Ángel
AU - Pons, Jose L
AU - Moreno, Juan C.
N1 - Funding Information:
This work is supported by The Biomot Project, funded by the Commission of the European Union under Grant Agreement number IFP7-ICT-2013-10-611695.
Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - In this study we explore a way of controlling a lower limb exoskeleton based on the detection of the user intention by recording and classifying information from force sensors placed on both knees and hips. The classifier is based on Linear Discriminant Analysis and has been tested offline in 5 healthy subjects, obtaining an average accuracy of 91.11 % for the sit-to-stand transition, 72.5 % for the stand-to-walk transition and 70 % for the stand-to-sit transition.
AB - In this study we explore a way of controlling a lower limb exoskeleton based on the detection of the user intention by recording and classifying information from force sensors placed on both knees and hips. The classifier is based on Linear Discriminant Analysis and has been tested offline in 5 healthy subjects, obtaining an average accuracy of 91.11 % for the sit-to-stand transition, 72.5 % for the stand-to-walk transition and 70 % for the stand-to-sit transition.
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U2 - 10.1007/978-3-319-46532-6_41
DO - 10.1007/978-3-319-46532-6_41
M3 - Chapter
AN - SCOPUS:85028461832
T3 - Biosystems and Biorobotics
SP - 249
EP - 253
BT - Biosystems and Biorobotics
PB - Springer International Publishing
ER -