MétaCan
Menu
Back to cohort
Record W1991170186 · doi:10.1016/j.pmrj.2013.02.003

Use of Segmental Coordination Analysis of Nonparetic and Paretic Limbs During Obstacle Clearance in Community‐Dwelling Persons After Stroke

2013· article· en· W1991170186 on OpenAlexafffund
Michael J. MacLellan, Carol L. Richards, Joyce Fung, Bradford J. McFadyen

Bibliographic record

VenuePM&R · 2013
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsMcGill UniversityJewish Rehabilitation HospitalNeuroDevNetCentre for Interdisciplinary Research in RehabilitationUniversité LavalCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of Canada
FundersCanadian Institutes of Health Research
KeywordsPhysical medicine and rehabilitationKinematicsStroke (engine)ObstacleMotor controlGaitMedicinePsychologyNeurosciencePhysics

Abstract

fetched live from OpenAlex

OBJECTIVE: To use a segment coordination analysis to identify coordination differences between the paretic and nonparetic limbs for obstacle clearance in community-dwelling persons after stroke. DESIGN: Within-participant design. SETTING: Gait analysis laboratory. PARTICIPANTS: Six community-dwelling persons with a stroke (excluding cerebellar stroke). METHODS: Participants stepped over obstacles of 2 different heights (7.5% and 15% of leg length), leading alternately with their paretic and nonparetic limbs. MAIN OUTCOME MEASUREMENTS: Kinematic data were collected, and segment elevation angles (absolute segment angular position with respect to vertical) were calculated for the thigh, shank, and foot segments. Established mathematical techniques related to the planar law of intersegmental coordination (principal component analysis to quantify covariance and temporal phase relationships among elevation angles) were then applied to compare and contrast the coordination of these segment elevation angle trajectories between paretic and nonparetic limbs. RESULTS: Segment covariance in elevation angles followed the planar law of intersegmental coordination during level walking (ie, 3 elevation angles that form a plane and the variance explained by 2 principal components) for both paretic and nonparetic limbs. During obstacle clearance, however, relationships between covariance plane characteristics and phase differences for elevation angles of adjacent segments differed in the nonparetic limb, likely related to a need for greater limb elevation for obstacle clearance during paretic limb support or an altered foot trajectory, which resulted from preobstacle foot placement. CONCLUSIONS: The present coordination analysis suggests the preservation of basic control mechanisms in the paretic limb during obstacle clearance after stroke and also reveals its specific motor control compensations. However, a larger study with differing levels of stroke severity must be conducted to understand how the evaluation of intersegmental coordination during walking could guide treatment of specific locomotor control deficits in stroke rehabilitation.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.024
Threshold uncertainty score0.360

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.030
GPT teacher head0.315
Teacher spread0.285 · 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 teacher head, 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

Citations18
Published2013
Admission routes2
Has abstractyes

Explore more

Same venuePM&RSame topicBalance, Gait, and Falls PreventionFrench-language works237,207