Literature DB >> 23232435

A comparative analysis of speed profile models for wrist pointing movements.

Lev Vaisman, Laura Dipietro, Hermano Igo Krebs.   

Abstract

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.

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Year:  2012        PMID: 23232435      PMCID: PMC4689593          DOI: 10.1109/TNSRE.2012.2231943

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  56 in total

1.  The curvature and variability of wrist and arm movements.

Authors:  Steven K Charles; Neville Hogan
Journal:  Exp Brain Res       Date:  2010-04-11       Impact factor: 1.972

2.  Increasing productivity and quality of care: robot-aided neuro-rehabilitation.

Authors:  H I Krebs; B T Volpe; M L Aisen; N Hogan
Journal:  J Rehabil Res Dev       Date:  2000 Nov-Dec

3.  Robot-based hand motor therapy after stroke.

Authors:  Craig D Takahashi; Lucy Der-Yeghiaian; Vu Le; Rehan R Motiwala; Steven C Cramer
Journal:  Brain       Date:  2007-12-20       Impact factor: 13.501

4.  Submovement changes characterize generalization of motor recovery after stroke.

Authors:  Laura Dipietro; Hermano I Krebs; Susan E Fasoli; Bruce T Volpe; Neville Hogan
Journal:  Cortex       Date:  2008-06-14       Impact factor: 4.027

5.  The trajectory of human wrist movements.

Authors:  R B Stein; F W Cody; C Capaday
Journal:  J Neurophysiol       Date:  1988-06       Impact factor: 2.714

6.  Quantization of continuous arm movements in humans with brain injury.

Authors:  H I Krebs; M L Aisen; B T Volpe; N Hogan
Journal:  Proc Natl Acad Sci U S A       Date:  1999-04-13       Impact factor: 11.205

7.  Mechanisms underlying achievement of final head position.

Authors:  E Bizzi; A Polit; P Morasso
Journal:  J Neurophysiol       Date:  1976-03       Impact factor: 2.714

8.  The coordination of arm movements: an experimentally confirmed mathematical model.

Authors:  T Flash; N Hogan
Journal:  J Neurosci       Date:  1985-07       Impact factor: 6.167

9.  Guidance-based quantification of arm impairment following brain injury: a pilot study.

Authors:  D J Reinkensmeyer; J P Dewald; W Z Rymer
Journal:  IEEE Trans Rehabil Eng       Date:  1999-03

10.  Kinematic robot-based evaluation scales and clinical counterparts to measure upper limb motor performance in patients with chronic stroke.

Authors:  Caitlyn Bosecker; Laura Dipietro; Bruce Volpe; Hermano Igo Krebs
Journal:  Neurorehabil Neural Repair       Date:  2009-08-14       Impact factor: 3.919

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  5 in total

1.  Spatiotemporal dynamics of online motor correction processing revealed by high-density electroencephalography.

Authors:  Laura Dipietro; Howard Poizner; Hermano I Krebs
Journal:  J Cogn Neurosci       Date:  2014-02-24       Impact factor: 3.225

2.  Moving slowly is hard for humans: limitations of dynamic primitives.

Authors:  Se-Woong Park; Hamal Marino; Steven K Charles; Dagmar Sternad; Neville Hogan
Journal:  J Neurophysiol       Date:  2017-03-29       Impact factor: 2.714

3.  A Comparative Analysis of Speed Profile Models for Ankle Pointing Movements: Evidence that Lower and Upper Extremity Discrete Movements are Controlled by a Single Invariant Strategy.

Authors:  Konstantinos P Michmizos; Lev Vaisman; Hermano Igo Krebs
Journal:  Front Hum Neurosci       Date:  2014-11-27       Impact factor: 3.169

4.  Movement-generated afference paired with transcranial magnetic stimulation: an associative stimulation paradigm.

Authors:  Dylan J Edwards; Laura Dipietro; Asli Demirtas-Tatlidede; Ana H Medeiros; Gary W Thickbroom; Francis L Mastaglia; Hermano I Krebs; Alvaro Pascual-Leone
Journal:  J Neuroeng Rehabil       Date:  2014-03-05       Impact factor: 4.262

Review 5.  On the analysis of movement smoothness.

Authors:  Sivakumar Balasubramanian; Alejandro Melendez-Calderon; Agnes Roby-Brami; Etienne Burdet
Journal:  J Neuroeng Rehabil       Date:  2015-12-09       Impact factor: 4.262

  5 in total

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