MétaCan
Menu
← Back to cohort
Record W3101195611 · doi:10.1101/544601

An Objective Technology-based Assessment of Arm and Hand Sensorimotor Disability in Neurological Disorders

2019· preprint· en· W3101195611 on OpenAlexafffund
Christoph M. Kanzler, Mike D. Rinderknecht, Anne Schwarz, Ilse Lamers, Cynthia Gagnon, Jeremia P. O. Held, Peter Feys, Andreas R. Luft, Roger Gassert, Olivier Lambercy

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsUniversité de Sherbrooke
FundersStaatssekretariat für Bildung, Forschung und InnovationCanadian Institutes of Health ResearchEuropean CommissionJames S. McDonnell Foundation
KeywordsPhysical medicine and rehabilitationWristDiscriminant validityPsychologyPhysical therapyConstruct validityParesisElbowMedicineDevelopmental psychologyPsychometricsInternal consistency

Abstract

fetched live from OpenAlex

Abstract Background Detailed assessments of upper limb disability are essential to understand and monitor sensorimotor recovery. Usually, multiple timeconsuming assessments are required to define a holistic sensorimotor profile of proximal (shoulder-elbow) and distal (wrist-hand) impairments and their impact on the capacity to perform activities. We propose and evaluate a novel physiologically-motivated computational framework for objectively assessing sensorimotor profiles in neurological patients using a single, rapid technology-based assessment involving goal-directed arm and hand movements. Methods The Virtual Peg Insertion Test (VPIT) was administered to 121 healthy and 80 neurological subjects. The framework provides 25 kinematic and kinetic metrics expected to describe 12 sensorimotor components representative of ataxia and paresis and their influence on task performance, as well as one overall disability measure. The feasibility (protocol duration), structural validity (factor analysis and correlations ρ between sensorimotor components), concurrent validity (correlation with Action Research Arm Test; ARAT), and discriminant validity (comparing healthy controls and patients, and patients with different disability levels) were evaluated. Results The median VPIT protocol duration was 16.5min in neurological patients. The sensor-based metrics could unambiguously be grouped into 12 mostly independent (median | ρ |=0.14) components. Ten components showed significant differences between healthy and impaired subjects and nine components indicated clear trends across disability levels, without any ceiling effects. The VPIT overall disability measure and ARAT were moderately correlated ( ρ =−0.53, p <0.001). Conclusions This work demonstrates the possibility to rapidly, holistically, and objectively assess proximal and distal sensorimotor impairments and their influence on the capacity to perform activities with a single assessment.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.265
Teacher spread0.255 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2019
Admission routes2
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)→Same topicStroke Rehabilitation and Recovery→French-language works237,207→