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Record W2951203356 · doi:10.82308/38431

Perceptuo-motor control of walking and navigation in post- stroke unilateral spatial neglect: en route towards the development of a novel assessment and advancement of current clinical practices

2018· article· en· W2951203356 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueeScholarship@McGill (McGill) · 2018
Typearticle
Languageen
FieldNeuroscience
TopicSpatial Neglect and Hemispheric Dysfunction
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchMcGill University
KeywordsPhysical medicine and rehabilitationStroke (engine)PerceptionMotor controlRehabilitationPsychologyAffect (linguistics)CognitionNeglectControl (management)Cognitive psychologyMedicineNeuroscienceComputer scienceCommunicationArtificial intelligencePsychiatry

Abstract

fetched live from OpenAlex

Unilateral spatial neglect (USN), a debilitating deficit that commonly occurs following a stroke, is characterized by a difficulty in orienting to or responding to events that generally occur in the space opposite to that of the brain lesion. USN is known to severely affect the stroke recovery, including mobility. The research in the field of USN impacts on mobility is scarce, where a handful of studies collectively present inconsistent findings and design shortcomings. Another important practice gap in the field of post-stroke USN refers to its assessment. Clinicians are currently limited in the use of traditional tools to evaluate USN that are consistently reported failing to pick up mild but clinically significant deficits. With the emerging fields of virtual reality (VR) and knowledge translation (KT) in rehabilitation, it is possible to address those important practice and knowledge gaps. The main objective of this PhD was addressed in 5 manuscripts and was to investigate the perceptuo-motor control in locomotion and navigation in post-stroke USN and thereby, to work towards the development and implementation of a novel VR-based USN assessment. In Manuscript 1, the effects of USN on goal-directed locomotion in conditions of different perceptual/cognitive demands were examined. In this study, participants with (n=15) and without (n=15) USN and healthy age-matched control individuals (n=15) performed goal-directed locomotion trials to actual, remembered, and shifting targets while immersed in a 3-D VR environment. We determined that post-stroke USN affects goal-directed locomotion to left and right targets, where USN clinical measures along with walking speed explained only 30% of locomotor deficit variance. However, USN+ participants were also found to be slower walkers than those without USN. Thus, in Manuscript 2, an analogous, joystick-driven navigation and target detection experiment, minimizing locomotor demands, was employed with the same participants. It was determined that USN attentional-perceptual deficits across the visual spectrum alter far-space navigation, independently of locomotor deficits. Other elements that could contribute to the observed locomotor deficits were explored in Manuscript 3, where we aimed to estimate the extent to which contrast sensitivity, shape discrimination, optic flow direction and coherence abilities are affected in post-stroke USN and how they relate to goal-directed locomotion alterations. USN was found to significantly impact all tested visual-perceptual abilities. Moreover, these emerged to be highly sensitive in detecting deficits otherwise left undetected by using conventional tools; and together with a USN clinical measure and walking speed, they were found to predict nearly 70% of the locomotor deficit variance. Further, in Manuscript 4, we aimed to examine the feasibility of a newly designed assessment, EVENS, that is fully immersive and is represented by simple and complex 3-D scenes, where object detection and far-space navigation tasks are performed in sitting. Negative and significant USN effects on navigational and detection abilities were determined, particularly in the complex scene. However, EVENS is yet to be implemented in clinical practice. As a first step in that direction, in Manuscript 5, we aimed to explore the barriers and facilitators perceived by clinicians (n=11) in the use of VR for USN evaluation; and to identify additional optimal features for EVENS as per clinicians and experts in the field (n=3) using qualitative methods. While clinicians were found to be open to the use of VR for post-stroke USN management, several barriers were identified. Participants also reported numerous features for the VR tool optimization.Collectively, this work laid solid grounds for clinical practice changes towards improved management of this common and highly debilitating deficit.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.491
Threshold uncertainty score0.738

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.058
GPT teacher head0.351
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it