By Topic

An active foot lifter orthosis based on a PCPG algorithm

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Duvinage, M. ; TCTS Lab., Univ. of Mons, Mons, Belgium ; Jimenez-Fabian, R. ; Castermans, T. ; Verlinden, O.
more authors

Central pattern generators (CPGs) are known to play an important role in the generation of rhythmic movements in gait, both in animals and humans. The comprehension of their underlying mechanism has led to the development of an important family of algorithms at the basis of autonomous walking robots. Recently, it has been shown that human gait could be modeled using a subclass of those algorithms, namely a Programmable Central Pattern Generator (PCPG). In this paper, we present a foot lifter orthosis driven by this algorithm. After a learning phase, the PCPG is able to generate adequate rhythmic gait patterns both for constant speeds and acceleration phases. Its output is used to drive the orthosis actuator during the swing phase, in order to help patients suffering from foot drop (the orthosis just follows the movement during the stance phase). The most interesting property of this algorithm is the possibility to generate a smooth output signal even during speed transitions. In practice, given that human gait is not perfectly periodic, the phase of this signal needs to be reset with actual movement. Therefore, two phase-resetting procedures were studied: one standard hard phase-resetting leading to discontinuities and one original soft phase-resetting allowing to recover the correct phase in a smooth way. The simulation results and complete design of the orthosis hardware and software are presented.

Published in:

Rehabilitation Robotics (ICORR), 2011 IEEE International Conference on

Date of Conference:

June 29 2011-July 1 2011