Haptic guidance for enhancing human motor learning: Application to a robot-assisted powered wheelchair trainer

Marchal Crespo, Laura (2009). Haptic guidance for enhancing human motor learning: Application to a robot-assisted powered wheelchair trainer. (Dissertation, University of California, Irvine, Mechanical and Aerospace Engineering)

[img] Text
out.pdf - Published Version
Restricted to registered users only
Available under License Publisher holds Copyright.

Download (20MB)

Achieving independent mobility is important for people with disabilities, but learning to drive a powered wheelchair can be difficult, time-consuming, and expensive. The primary motivation for this dissertation was to develop a robotic wheelchair trainer on which people with a disability can safely develop driving skills at their own pace with minimum assistance. The concept was to use a robotic joystick to guide movements to help people safely learn how to steer.
To provide a rational framework, we studied the conditions under which robotic guidance was effective for helping learn to steer, using a virtual reality simulator. Of concern was the long-standing “guidance” hypothesis which states that providing too much guidance impairs motor learning. We incorporated a novel guidance-as-needed strategy, which adjusts levels of guidance based on real-time errors. Training with guidance-as-needed improved the drivers’ steering ability more than training without guidance, apparently because it helped learn when to begin turns. Furthermore,
guidance’s benefits were skill-dependent.
Guidance appeared to help participants learn timing. We therefore developed a robotic device to study whether robotic guidance improved learning of a pure timing task (a pinball-like task). Guidance was not effective, probably because participants relied on the form of guidance used, which totally eliminated performance errors. When we modified the strategy so that guidance was proportional to timing errors, guidance was beneficial for participants with a lower skill level.
To incorporate these findings into the robotic wheelchair trainer, we equipped a powered pediatric wheelchair with a webcam to achieve a self steering function along a course, and a force-feedback joystick to implement an algorithm that demonstrates exemplary control to follow the course, while systematically modulating its strength. Consistent with the findings from the driving simulator, training with guidance from the smart wheelchair improved healthy children’s (age 3-10) steering ability more than training without guidance. In fact, training without guidance did not improve children’s steering ability.
These results appear to be the first direct evidence that haptic guidance can enhance motor learning. Haptic guidance enhances learning of timing tasks, such as driving and pinball, in less-skilled people, and is more beneficial when applied only as needed.

Item Type:

Thesis (Dissertation)

Division/Institute:

10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Motor Learning and Neurorehabilitation
04 Faculty of Medicine > Faculty Institutions > Teaching Staff, Faculty of Medicine
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - Gerontechnology and Rehabilitation

UniBE Contributor:

Marchal Crespo, Laura

Subjects:

600 Technology > 610 Medicine & health
600 Technology > 620 Engineering

Language:

English

Submitter:

Angela Amira Botros

Date Deposited:

30 Jul 2018 08:47

Last Modified:

05 Dec 2022 15:14

BORIS DOI:

10.7892/boris.117120

URI:

https://boris.unibe.ch/id/eprint/117120

Actions (login required)

Edit item Edit item
Provide Feedback