Performance Evaluation Methods for Assistive Robotic Technology

  • Katherine M. Tsui
  • David J. Feil-Seifer
  • Maja J. Matarić
  • Holly A. Yanco


Robots have been developed for several assistive technology domains, including intervention for Autism Spectrum Disorders, eldercare, and post-stroke rehabilitation. Assistive robots have also been used to promote independent living through the use of devices such as intelligent wheelchairs, assistive robotic arms, and external limb prostheses. Work in the broad field of assistive robotic technology can be divided into two major research phases: technology development, in which new devices, software, and interfaces are created; and clinical, in which assistive technology is applied to a given end-user population. Moving from technology development towards clinical applications is a significant challenge. Developing performance metrics for assistive robots poses a related set of challenges. In this paper, we survey several areas of assistive robotic technology in order to derive and demonstrate domain-specific means for evaluating the performance of such systems. We also present two case studies of applied performance measures and a discussion regarding the ubiquity of functional performance measures across the sampled domains. Finally, we present guidelines for incorporating human performance metrics into end-user evaluations of assistive robotic technologies.


Autism Spectrum Disorder Autism Spectrum Disorder Autism Diagnostic Observation Schedule Vineland Adaptive Behavior Scale Assistive Robot 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work is funded in part by the National Science Foundation (IIS-0534364, IIS-0546309, IIS-0713697, CNS-0709296), the National Academies Keck Futures Initiative (NAKFI), the USC NIH Aging and Disability Resource Center (ADRC) pilot program, and the Nancy Laurie Marks Family Foundation. The authors thank Kristen Stubbs of UMass Lowell.


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Katherine M. Tsui
    • 1
  • David J. Feil-Seifer
    • 2
  • Maja J. Matarić
    • 2
  • Holly A. Yanco
    • 1
  1. 1.Department of Computer ScienceUniversity of Massachusetts LowellLowellUSA
  2. 2.Department of Computer ScienceUniversity of Southern CaliforniaLos AngelesUSA

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