MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

A sensor-based physical tool adaptation framework for facilitating motor skills learning

Author(s)
Qi, Yini
Thumbnail
DownloadFull printable version (2.019Mb)
Other Contributors
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Stefanie Mueller.
Terms of use
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582
Metadata
Show full item record
Abstract
Many motor skills that people learn throughout their lives involve mastering a physical tool, such as riding a bike, writing with a pen, or playing basketball. When learning these skills, people often use physical learning aids to provide support. However, currently these learning aids only come in predefined levels. For instance, training wheels on a bike are either mounted or taken off. This jump from an easy task to a much harder one makes the transition difficult in learning the skill. In this thesis, we address this challenge by adapting the physical tool according to the learner's progress. For instance, while learning to ride a bike, we monitor learners' balancing skills and as they improve, we gradually lift the training wheels to reduce support and increase the difficulty. Thus, this approach enables a step-by-step transition from an easy to hard level that, like existing adaptive learning systems for math and language skills, is personalized for each individual learner. To illustrate this idea, we built an end-to-end system that allows designers to setup adaptable tools that physically change when a learner's skill level increases. This system uses sensors integrated with the tools to measure progress; parametric 3D modeling to adapt the tool; and either actuation or re-fabrication to deploy the physical change.
Description
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.
 
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
 
Cataloged from student-submitted PDF version of thesis.
 
Includes bibliographical references (pages 45-46).
 
Date issued
2018
URI
http://hdl.handle.net/1721.1/120389
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

Collections
  • Graduate Theses

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.