Evidence map›Paper›PMID 31244757›Full record

ArticleFrontiers in neurology2019

Automated and Quantitative Assessment of Tactile Mislocalization After Stroke.

Mike D Rinderknecht, Julio A Dueñas, Jeremia P Held, Olivier Lambercy, Fabio M Conti, Leopold Zizlsperger, Andreas R Luft, Marie-Claude Hepp-Reymond, Roger Gassert

Abstract readCase Reports
In one paragraph

Article in Frontiers in neurology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Mike D RinderknechtRehabilitation Engineering Laboratory, Department of Health Sciences and Technology, Institute of Robotics and Intelligent Systems, ETH Zurich, Zurich, Switzerland.
Julio A DueñasRehabilitation Engineering Laboratory, Department of Health Sciences and Technology, Institute of Robotics and Intelligent Systems, ETH Zurich, Zurich, Switzerland.
Jeremia P HeldDivision of Vascular Neurology and Neurorehabilitation, Department of Neurology, University of Zurich and University Hospital Zurich, Zurich, Switzerland.
Olivier LambercyRehabilitation Engineering Laboratory, Department of Health Sciences and Technology, Institute of Robotics and Intelligent Systems, ETH Zurich, Zurich, Switzerland.
Fabio M ContiClinica Hildebrand Centro di Riabilitazione Brissago, Brissago, Switzerland.
Leopold ZizlspergerDivision of Vascular Neurology and Neurorehabilitation, Department of Neurology, University of Zurich and University Hospital Zurich, Zurich, Switzerland.
Andreas R LuftDivision of Vascular Neurology and Neurorehabilitation, Department of Neurology, University of Zurich and University Hospital Zurich, Zurich, Switzerland.
Marie-Claude Hepp-ReymondInstitute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.
Roger GassertRehabilitation Engineering Laboratory, Department of Health Sciences and Technology, Institute of Robotics and Intelligent Systems, ETH Zurich, Zurich, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Topesthesia, the recognition of tactile stimulation location on the skin, can be severely affected by neurological injuries, such as stroke. Despite topesthesia being crucial for manipulating objects and interacting with the environment during activities of daily living, deficits cannot be quantitatively captured with current clinical assessments and are, as a consequence, not well-understood. The present work describes a novel automated assessment tool for tactile mislocalization in neurological patients with somatosensory deficits. We present two cases of ischemic stroke patients, describe their tactile localization deficits with the automated assessment, and compare the results to a standard manual clinical assessment. Using the automated assessment tool, it was possible to identify, locate, precisely quantify, and depict the patients' deficits in topesthesia. In comparison, the clinical assessment was not sensitive enough and some deficits would remain undetected due to ceiling effects. In addition, an MRI structural analysis of the lesion supported the existence of somatosensory deficits. This novel and quantitative assessment may not only help to raise awareness of the implications of deficits in topesthesia, but would also allow monitoring recovery throughout the rehabilitation process, informing treatment design, and objectively evaluating treatment efficacy.

Indexed as

localization deficitsquantitative measurementroboticstroketopesthesiatopognosistouchvibration

Identifiers

PMID31244757
PMCPMC6581709

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.