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Record W4407590345 · doi:10.1186/s12984-025-01542-x

Lower limb pointing to assess intersegmental dynamics after incomplete spinal cord injury and the associated role of proprioceptive impairments

2025· article· en· W4407590345 on OpenAlexafffund
Raza N. Malik, Daniel S. Marigold, Mason Chow, Gevorg Eginyan, Tania Lam

Bibliographic record

VenueJournal of NeuroEngineering and Rehabilitation · 2025
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsSimon Fraser UniversityInternational Collaboration On Repair DiscoveriesUniversity of British Columbia
FundersCanadian Institutes of Health ResearchUniversity of British Columbia
KeywordsProprioceptionPhysical medicine and rehabilitationSpinal cord injuryInverse dynamicsKnee JointMotor controlLower limbMedicineGaitPhysical therapyPsychologySpinal cordKinematicsSurgeryPhysics

Abstract

fetched live from OpenAlex

BACKGROUND: Disorders in the recovery of gait strategies in individuals with incomplete spinal cord injury (SCI) suggest difficulties in controlling lower limb intersegmental dynamics, which could relate to proprioceptive impairments. To probe discrete aspects of lower limb interjoint coordination, we present here a novel protocol to assess lower limb motor strategies and evaluate the influence of proprioceptive impairments following SCI. METHODS: Twelve able-bodied controls and 16 participants with SCI performed lower limb pointing to three targets that involved combined hip and knee flexion, or hip or knee flexion only while standing, with either full or obstructed visual feedback. We quantified lower limb proprioceptive sense in individuals with SCI using a robotic gait device. We used motion analysis to determine lower limb joint angles and foot trajectory, computed inverse dynamics to quantify joint and intersegmental dynamics, and derived muscle torque as an indicator of the motor strategies produced to control the motion to each target. We used linear mixed-effects models to assess differences between the control and SCI groups on end-point performance and muscle torque, and to assess the relationship of muscle torque with end-point performance and proprioceptive sense. RESULTS: Groups differed in motor strategies, but not end-point performance, when pointing to all three targets. Compared to controls, the SCI group had difficulty controlling knee muscle torque when performing the hip-flexion-only target (p = 0.008) or when flexing the hip and knee simultaneously (p = 0.0004). To complete the knee-flexion-only target, the SCI group had difficulties generating the required hip extensor muscle torque to maintain the thigh in neutral (p = 0.0001). These altered motor strategies in individuals with SCI were associated with proprioceptive impairments and end-point performance. CONCLUSION: This novel lower limb pointing task can identify disordered motor strategies in individuals with SCI, especially at the knee, and are associated with proprioceptive impairment. Variations of this paradigm can be employed to further understand differences in motor strategies between controls and individuals with SCI, and the impact of proprioceptive deficits.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.254
Teacher spread0.246 · 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 designObservational
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

Citations2
Published2025
Admission routes2
Has abstractyes

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