By Topic

A Comparative Analysis of Speed Profile Models for Wrist Pointing Movements

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Vaisman, L. ; Sch. of Med., Dept. of Anatomy & Neurobiol., Boston Univ., Boston, MA, USA ; Dipietro, L. ; Krebs, H.I.

Following two decades of design and clinical research on robot-mediated therapy for the shoulder and elbow, therapeutic robotic devices for other joints are being proposed: several research groups including ours have designed robots for the wrist, either to be used as stand-alone devices or in conjunction with shoulder and elbow devices. However, in contrast with robots for the shoulder and elbow which were able to take advantage of descriptive kinematic models developed in neuroscience for the past 30 years, design of wrist robots controllers cannot rely on similar prior art: wrist movement kinematics has been largely unexplored. This study aimed at examining speed profiles of fast, visually evoked, visually guided, target-directed human wrist pointing movements. One thousand three-hundred ninety-eight (1398) trials were recorded from seven unimpaired subjects who performed center-out flexion/extension and abduction/adduction wrist movements and fitted with 19 models previously proposed for describing reaching speed profiles. A nonlinear, least squares optimization procedure extracted parameters' sets that minimized error between experimental and reconstructed data. Models' performances were compared based on their ability to reconstruct experimental data. Results suggest that the support-bounded lognormal is the best model for speed profiles of fast, wrist pointing movements. Applications include design of control algorithms for therapeutic wrist robots and quantitative metrics of motor recovery.

Published in:

Neural Systems and Rehabilitation Engineering, IEEE Transactions on  (Volume:21 ,  Issue: 5 )