LOPES II - Design and Evaluation of an Admittance Controlled Gait Training Robot with Shadow-Leg Approach

Research output: Contribution to journalArticleAcademicpeer-review

126 Citations (Scopus)
147 Downloads (Pure)

Abstract

Robotic gait training is gaining ground in rehabilitation. Room for improvement lies in reducing donning and doffing time, making training more task specific and facilitating active balance control, and by allowing movement in more degrees of freedom. Our goal was to design and evaluate a robot that incorporates these improvements. LOPES II uses an end-effector approach with parallel actuation and a minimum amount of clamps. LOPES II has eight powered degrees of freedom (hip flexion/extension, hip abduction/adduction, knee flexion/extension, pelvis forward/aft and pelvis mediolateral). All other degrees of freedom can be left free and pelvis frontal- and transversal rotation can be constrained. Furthermore arm swing is unhindered. The end-effector approach eliminates the need for exact alignment, which results in a donning time of 10-14 min for first-time training and 5-8 min for recurring training. LOPES II is admittance controlled, which allows for the control over the complete spectrum from low to high impedance. When the powered degrees of freedom are set to minimal impedance, walking in the device resembles free walking, which is an important requisite to allow task-specific training. We demonstrated that LOPES II can provide sufficient support to let severely affected patients walk and that we can provide selective support to impaired aspects of gait of mildly affected patients
Original languageEnglish
Article number7369983
Pages (from-to)352-363
Number of pages12
JournalIEEE transactions on neural systems and rehabilitation engineering
Volume24
Issue number3
DOIs
Publication statusPublished - 2016

Keywords

  • 2023 OA procedure

Fingerprint

Dive into the research topics of 'LOPES II - Design and Evaluation of an Admittance Controlled Gait Training Robot with Shadow-Leg Approach'. Together they form a unique fingerprint.

Cite this