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
Why this work is in the frame
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Bibliographic record
Abstract
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.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it