Literature DB >> 22120028

Development and validation of the first robotic scale for the clinical assessment of upper extremity motor impairments in stroke patients.

Omer Einav1, Diklah Geva, Doron Yoeli, Marina Kerzhner, Karl-Heinz Mauritz.   

Abstract

PURPOSE: We aimed to develop and validate the first robotic-based instrument and procedure for assessing upper extremity motor impairments in patients with stroke and to test its discriminative power.
METHODS: The ReoGo robotic rehabilitation platform was used to design a novel, upper limb functionality assessment tool, the Reo Scale Assessment (RSA). We used the RSA to evaluate 100 patients with stroke. The RSA items were tested for internal consistency and submitted to factor analysis. The Fugl-Meyer (FM) motor test, the Wolf Motor Function Test (WMFT), and the Action Research Arm Test (ARAT) were used to examine the validity of the RSA. RSA scores were compared and correlated with the scores of the 3 scales. The discriminative power of the RSA was tested against the FM impairment levels by analysis of variance.
RESULTS: The total RSA score correlated closely with the upper extremity scores of the FM, WMFT, and ARAT (r = 0.95, 0.93, and 0.90, respectively). The RSA was able to discriminate between low, moderate, and high functioning patients (86% agreement with FM). Principal component analysis revealed that the RSA coefficients loaded on 3 tested components: proximal, distal, and force.
CONCLUSIONS: Our results provide strong evidence that the validity of the RSA is comparable with that of the FM, WMFT, and ARAT. The objective measuring and scoring systems of the robotic RSA make it an efficient tool for assessing motor function of stroke patients in clinical and research settings. Additional studies are needed to test the reliability and sensitivity of the RSA.

Entities:  

Mesh:

Year:  2011        PMID: 22120028     DOI: 10.1310/tsr18s01-587

Source DB:  PubMed          Journal:  Top Stroke Rehabil        ISSN: 1074-9357            Impact factor:   2.119


  7 in total

1.  Validity of Robot-Based Assessments of Upper Extremity Function.

Authors:  Alison McKenzie; Lucy Dodakian; Jill See; Vu Le; Erin Burke Quinlan; Claire Bridgford; Daniel Head; Vy L Han; Steven C Cramer
Journal:  Arch Phys Med Rehabil       Date:  2017-05-05       Impact factor: 3.966

2.  Using clinical and robotic assessment tools to examine the feasibility of pairing tDCS with upper extremity physical therapy in patients with stroke and TBI: a consideration-of-concept pilot study.

Authors:  Addie Middleton; Stacy L Fritz; Derek M Liuzzo; Roger Newman-Norlund; Troy M Herter
Journal:  NeuroRehabilitation       Date:  2014       Impact factor: 2.138

3.  Robotic assessment of the influence of age on upper-limb sensorimotor function.

Authors:  Ana Llinares; Francisco Javier Badesa; Ricardo Morales; Nicolas Garcia-Aracil; J M Sabater; Eduardo Fernandez
Journal:  Clin Interv Aging       Date:  2013-07-10       Impact factor: 4.458

4.  Instrumental indices for upper limb function assessment in stroke patients: a validation study.

Authors:  Maria Longhi; Andrea Merlo; Paolo Prati; Meris Giacobbi; Davide Mazzoli
Journal:  J Neuroeng Rehabil       Date:  2016-06-08       Impact factor: 4.262

5.  A robotic object hitting task to quantify sensorimotor impairments in participants with stroke.

Authors:  Kathrin Tyryshkin; Angela M Coderre; Janice I Glasgow; Troy M Herter; Stephen D Bagg; Sean P Dukelow; Stephen H Scott
Journal:  J Neuroeng Rehabil       Date:  2014-04-02       Impact factor: 4.262

6.  A Comparative Analysis of 2D and 3D Tasks for Virtual Reality Therapies Based on Robotic-Assisted Neurorehabilitation for Post-stroke Patients.

Authors:  Luis D Lledó; Jorge A Díez; Arturo Bertomeu-Motos; Santiago Ezquerro; Francisco J Badesa; José M Sabater-Navarro; Nicolás García-Aracil
Journal:  Front Aging Neurosci       Date:  2016-08-26       Impact factor: 5.750

7.  Translation and Initial Validation of the Chinese Version of the Action Research Arm Test in People with Stroke.

Authors:  Jiang-Li Zhao; Pei-Ming Chen; Wen-Feng Li; Rui-Hao Bian; Ming-Hui Ding; Hai Li; Qiang Lin; Zhi-Qin Xu; Yu-Rong Mao; Dong-Feng Huang
Journal:  Biomed Res Int       Date:  2019-01-21       Impact factor: 3.411

  7 in total

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