Literature DB >> 24760936

Test-retest reliability of robotic assessment measures for the evaluation of upper limb recovery.

Roberto Colombo, Ivana Cusmano, Irma Sterpi, Alessandra Mazzone, Carmen Delconte, Fabrizio Pisano.   

Abstract

Rehabilitation robots have built-in technology and sensors that allow accurate measurement of movement kinematics and kinetics, which can be used to derive measures related to upper limb performance and highlight changes in motor behavior due to rehabilitation. This study aimed to assess the test-retest reliability of some robot-measured parameters by analyzing their intra-session and inter-session (day-by-day) variability. The study was carried out in two groups: 31 patients after stroke and 15 healthy subjects. Both groups practiced two different motor tasks consisting of point-to-point reaching movements in the shape of two geometrical figures that were selected for the assessment of global and directional (eight directions of the workspace) test-retest reliability. The reliability of six parameters measuring movement velocity, accuracy, efficiency and smoothness was assessed intra-session and inter-session by the ICC, SEM, and CV. Healthy subjects exhibited very high ICC values (> 0.85) and low SEM for all parameters. Patients had high ICC values and low SEM but their global reliability was generally lower compared to healthy subjects. In addition, their inter-session reliability showed very high ICC values (> 0.91) and low SEM for all parameters. Direction analysis showed that in some parameters the reliability was generally high but not homogeneous in all directions. In addition, some directions showed systematic error. This study demonstrates that robot-measured parameters are reliable and can be considered ideal candidates for use in combination with impairment and functional clinical scales to evaluate motor improvement during robot-assisted neurorehabilitation.

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Year:  2014        PMID: 24760936     DOI: 10.1109/TNSRE.2014.2306571

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


  12 in total

1.  Feasibility of Incorporating Test-Retest Reliability and Model Diversity in Identification of Key Neuromuscular Pathways During Head Position Tracking.

Authors:  Ahmed Ramadan; Jongeun Choi; Jacek Cholewicki; N Peter Reeves; John M Popovich; Clark J Radcliffe
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2019-01-10       Impact factor: 3.802

2.  Principal Components Analysis Using Data Collected From Healthy Individuals on Two Robotic Assessment Platforms Yields Similar Behavioral Patterns.

Authors:  Michael D Wood; Leif E R Simmatis; Jill A Jacobson; Sean P Dukelow; J Gordon Boyd; Stephen H Scott
Journal:  Front Hum Neurosci       Date:  2021-05-06       Impact factor: 3.169

3.  Robotic and clinical evaluation of upper limb motor performance in patients with Friedreich's Ataxia: an observational study.

Authors:  Marco Germanotta; Gessica Vasco; Maurizio Petrarca; Stefano Rossi; Sacha Carniel; Enrico Bertini; Paolo Cappa; Enrico Castelli
Journal:  J Neuroeng Rehabil       Date:  2015-04-23       Impact factor: 4.262

4.  Movement distributions of stroke survivors exhibit distinct patterns that evolve with training.

Authors:  Felix C Huang; James L Patton
Journal:  J Neuroeng Rehabil       Date:  2016-03-09       Impact factor: 4.262

5.  Movement Velocity and Fluidity Improve after Armeo®Spring Rehabilitation in Children Affected by Acquired and Congenital Brain Diseases: An Observational Study.

Authors:  Emilia Biffi; Cristina Maghini; Beatrice Cairo; Elena Beretta; Elisabetta Peri; Daniele Altomonte; Davide Mazzoli; Meris Giacobbi; Paolo Prati; Andrea Merlo; Sandra Strazzer
Journal:  Biomed Res Int       Date:  2018-11-18       Impact factor: 3.411

6.  Smallest real differences for robotic measures of upper extremity function after stroke: Implications for tracking recovery.

Authors:  José Zariffa; Matthew Myers; Marge Coahran; Rosalie H Wang
Journal:  J Rehabil Assist Technol Eng       Date:  2018-09-17

7.  Kinematic Parameters for Tracking Patient Progress during Upper Limb Robot-Assisted Rehabilitation: An Observational Study on Subacute Stroke Subjects.

Authors:  Michela Goffredo; Stefano Mazzoleni; Annalisa Gison; Francesco Infarinato; Sanaz Pournajaf; Daniele Galafate; Maurizio Agosti; Federico Posteraro; Marco Franceschini
Journal:  Appl Bionics Biomech       Date:  2019-10-21       Impact factor: 1.781

8.  Test-retest reliability of Kinect's measurements for the evaluation of upper body recovery of stroke patients.

Authors:  A Mobini; S Behzadipour; M Saadat
Journal:  Biomed Eng Online       Date:  2015-08-04       Impact factor: 2.819

9.  Reliability, validity and discriminant ability of the instrumental indices provided by a novel planar robotic device for upper limb rehabilitation.

Authors:  Marco Germanotta; Arianna Cruciani; Cristiano Pecchioli; Simona Loreti; Albino Spedicato; Matteo Meotti; Rita Mosca; Gabriele Speranza; Francesca Cecchi; Giorgia Giannarelli; Luca Padua; Irene Aprile
Journal:  J Neuroeng Rehabil       Date:  2018-05-16       Impact factor: 4.262

10.  Technology-aided assessment of functionally relevant sensorimotor impairments in arm and hand of post-stroke individuals.

Authors:  Christoph M Kanzler; Anne Schwarz; Jeremia P O Held; Andreas R Luft; Roger Gassert; Olivier Lambercy
Journal:  J Neuroeng Rehabil       Date:  2020-09-25       Impact factor: 4.262

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