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DEVELOPMENT AND ASSESSMENT OF ADVANCED ASSISTIVE ROBOTIC MANIPULATORS USER INTERFACES

Chung, Cheng-Shiu (2015) DEVELOPMENT AND ASSESSMENT OF ADVANCED ASSISTIVE ROBOTIC MANIPULATORS USER INTERFACES. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Abstract

Text BoxAssistive Robotic Manipulators (ARM) have shown improvement in self-care and increased independence among people with severe upper extremity disabilities. With an ARM mounted on the side of an electric powered wheelchair, an ARM may provide manipulation assistance, such as picking up object, eating, drinking, dressing, reaching out, or opening doors. However, existing assessment tools are inconsistent between studies, time consuming, and unclear in clinical effectiveness. Therefore, in this research, we have developed an ADL task board evaluation tool that provides standardized, efficient, and reliable assessment of ARM performance. Among powered wheelchair users and able-bodied controls using two commercial ARM user interfaces – joystick and keypad, we found that there were statistical differences between both user interface performances, but no statistical difference was found in the cognitive loading. The ADL task board demonstrated highly correlated performance with an existing functional assessment tool, Wolf Motor Function Test. Through this study, we have also identified barriers and limits in current commercial user interfaces and developed smartphone and assistive sliding-autonomy user interfaces that yields improved performance. Testing results from our smartphone manual interface revealed statistically faster performance. The assistive sliding-autonomy interface helped seamlessly correct the error seen with autonomous functions.
The ADL task performance evaluation tool may help clinicians and researchers better access ARM user interfaces and evaluated the efficacy of customized user interfaces to improve performance. The smartphone manual interface demonstrated improved performance and the sliding-autonomy framework showed enhanced success with tasks without recalculating path planning and recognition.


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Chung, Cheng-ShiuJoshua.Chung.CS@Gmail.com0000-0002-9997-5558
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairCooper, Rory Arcooper@pitt.eduRCOOPER
Committee MemberSrinivasa, Siddharthasiddh@cs.cmu.edu
Committee MemberKelleher, Annmarieakellehe@pitt.eduAKELLEHE
Committee MemberDing, Dandad5@pitt.eduDAD5
Date: 28 September 2015
Date Type: Publication
Defense Date: 16 July 2015
Approval Date: 28 September 2015
Submission Date: 24 July 2015
Access Restriction: 2 year -- Restrict access to University of Pittsburgh for a period of 2 years.
Number of Pages: 181
Institution: University of Pittsburgh
Schools and Programs: School of Health and Rehabilitation Sciences > Rehabilitation Science and Technology
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Robotics, Assistive Technology, Rehabilitation, Wheelchair, Performance Evaluation, Assessment
Date Deposited: 28 Sep 2016 05:00
Last Modified: 28 Sep 2017 05:15
URI: http://d-scholarship.pitt.edu/id/eprint/25771

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