INVESTIGATION OF PHASE VARIABLES IN HUMAN LOCOMOTION FOR APPLICATIONS IN ROBOTIC PROSTESES
Topic: All | Applicative
Séance du mercredi 4 mai 2016, Salle L 224, 14h00.
Dario VILLAREAL, University of Texas at DALLAS
INVESTIGATION OF PHASE VARIABLES IN HUMAN LOCOMOTION FOR APPLICATIONS IN ROBOTIC PROSTESES
This research aims to develop high-performance wearable control systems (e.g., prostheses and orthoses) to enable mobility and improve quality of life for individuals with disabilities. Current powered prosthetic legs independently control different joints and time periods of the gait cycle, requiring clinicians to spend significant amounts of time tuning each control model to the individual, and risking falls when environmental
disturbances trigger the wrong control mode at the wrong time. These limitations are a consequence of the current paradigm for viewing gait patterns as a function of time. However, recent bipedal robots can stably
walk, run and climb stairs with one control model that drives joint patterns as function of a single mechanical variable. This variable continuously represents the robot’s progression through the gait cycle,
i.e., gives a sense of phase to the robot. In this seminar we will talk about how this research attempts to translate these breakthroughs into prosthetic and orthotic technology by shifting the way in which the human gait cycle is viewed. We will discuss how this work enables the design of wearable robots with a single control model that measures a biologically-inspired phase variable to match the human’s volitional movement and respond to perturbations. The implementation of an experimental protocol that allows us to study biologically-inspired phase variable candidates is presented as well as experimental results using a custom made robotic prosthetic leg.
Dario VILLAREAL, University of Texas at DALLAS
INVESTIGATION OF PHASE VARIABLES IN HUMAN LOCOMOTION FOR APPLICATIONS IN ROBOTIC PROSTESES
This research aims to develop high-performance wearable control systems (e.g., prostheses and orthoses) to enable mobility and improve quality of life for individuals with disabilities. Current powered prosthetic legs independently control different joints and time periods of the gait cycle, requiring clinicians to spend significant amounts of time tuning each control model to the individual, and risking falls when environmental
disturbances trigger the wrong control mode at the wrong time. These limitations are a consequence of the current paradigm for viewing gait patterns as a function of time. However, recent bipedal robots can stably
walk, run and climb stairs with one control model that drives joint patterns as function of a single mechanical variable. This variable continuously represents the robot’s progression through the gait cycle,
i.e., gives a sense of phase to the robot. In this seminar we will talk about how this research attempts to translate these breakthroughs into prosthetic and orthotic technology by shifting the way in which the human gait cycle is viewed. We will discuss how this work enables the design of wearable robots with a single control model that measures a biologically-inspired phase variable to match the human’s volitional movement and respond to perturbations. The implementation of an experimental protocol that allows us to study biologically-inspired phase variable candidates is presented as well as experimental results using a custom made robotic prosthetic leg.