Changing stroke rehab and research worldwide now.Time is Brain! trillions and trillions of neurons that DIE each day because there are NO effective hyperacute therapies besides tPA(only 12% effective). I have 523 posts on hyperacute therapy, enough for researchers to spend decades proving them out. These are my personal ideas and blog on stroke rehabilitation and stroke research. Do not attempt any of these without checking with your medical provider. Unless you join me in agitating, when you need these therapies they won't be there.

What this blog is for:

My blog is not to help survivors recover, it is to have the 10 million yearly stroke survivors light fires underneath their doctors, stroke hospitals and stroke researchers to get stroke solved. 100% recovery. The stroke medical world is completely failing at that goal, they don't even have it as a goal. Shortly after getting out of the hospital and getting NO information on the process or protocols of stroke rehabilitation and recovery I started searching on the internet and found that no other survivor received useful information. This is an attempt to cover all stroke rehabilitation information that should be readily available to survivors so they can talk with informed knowledge to their medical staff. It lays out what needs to be done to get stroke survivors closer to 100% recovery. It's quite disgusting that this information is not available from every stroke association and doctors group.

Tuesday, November 10, 2020

Clinical usefulness and validity of robotic measures of reaching movement in hemiparetic stroke patients

Useless, measurement does NOTHING for getting to 100% recovery.

Clinical usefulness and validity of robotic measures of reaching movement in hemiparetic stroke patients

2015, Journal of neuroengineering and rehabilitation

 

Eri Otaka 1, 
Yohei Otaka 1*, 
Shoko Kasuga 1, 
Atsuko Nishimoto 1, 
Kotaro Yamazaki 1, 
Michiyuki Kawakami 1,
Junichi Ushiba 2
and Meigen Liu 1

Abstract

Background:
 Various robotic technologies have been developed recently for objective and quantitative assessment of movement. Among them, robotic measures derived from a reaching task in the KINARM Exoskeleton device are characterized by their potential to reveal underlying motor control in reaching movements. The aim of this study was to examine the clinical usefulness and validity of these robot-derived measures in hemiparetic stroke patients.
Methods:
 Fifty-six participants with a hemiparetic arm due to chronic stroke were enrolled. The robotic assessment was performed using the Visually Guided Reaching (VGR) task in the KINARM Exoskeleton, which allows free arm movements in the horizontal plane. Twelve parameters were derived based on motor control theory. The following clinical assessments were also administered: the proximal upper limb section in the Fugl-Meyer Assessment(FMA-UE(A)), the proximal upper limb part in the Stroke Impairment Assessment Set (SIAS-KM), the Modified Ashworth Scale for the affected elbow flexor muscles (MAS elbow), and seven proximal upper limb tasks in the Wolf Motor Function Test (WMFT). To explore which robotic measures represent deficits of motor control in the affected arm, the VGR parameters in the paretic arm were compared with those in the nonparetic arm using the Wilcoxon signed rank test. Then, to explore which VGR parameters were related to overall motor control regardless of the paresis, correlations between the paretic and nonparetic arms were examined. Finally, to investigate the relationships between the robotic measures and the clinical scales, correlations between the VGR parameters and clinical scales were investigated. Spearman

s rank correlation coefficients were used for all correlational analyses.
Results:
 Eleven VGR parameters on the paretic side were significantly different from those on the non-paretic side with large effect sizes (|effect size| = 0.76–0.87). Ten VGR parameters correlated significantly with FMA-UE(A)(|r| = 0.32–0.60). Eight VGR parameters also showed significant correlations with SIAS-KM (|r| = 0.42–0.49),  MASelbow (|r| = 0.44–0.48), and the Functional Ability Scale of the WMFT (|r| = 0.52–0.64).
Conclusions:
 The robot-derived measures could successfully differentiate between the paretic arm and the nonparetic arm and were valid in comparison to the well-established clinical scales.
* Correspondence: otaka119@mac.com
1
Department of Rehabilitation Medicine, Keio University School of Medicine, Tokyo, JapanFull list of author information is available at the end of the article
JNER
 JOURNAL OF NEUROENGINEERINGAND REHABILITATION
© 2015 Otaka et al.
 Open Access
 This article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated.
Otaka
 et al. Journal of NeuroEngineering and Rehabilitation
 
DOI 10.1186/s12984-015-0059-8
 

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