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Motor Control of Exercise that Emphasizes Speed Post-stroke

2012· article· en· W6025236 on OpenAlexfundno aff
Vicki L. Gray

Bibliographic record

VenueAnnals of Internal Medicine · 2012
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
FundersHeart and Stroke Foundation of Canada
KeywordsPhysical medicine and rehabilitationStroke (engine)Motor controlControl (management)MedicinePsychologyComputer scienceEngineeringNeuroscienceArtificial intelligenceMechanical engineering

Abstract

fetched live from OpenAlex

Purpose: To investigate whether a single session of closed kinetic chain (CKC) and open kinetic chain (OKC) exercises emphasizing speed post-stroke could evoke changes in the motor control and whether these improvements would transfer to postural tasks.\nMethods: Thirty-two individuals post-stroke and 32 age- and sex- matched controls performed a single session of 50 fast squats and steps (Chapter 3). Internal perturbations (arm raise/load drop) were used to assess postural responses before exercises (Pre), immediately after exercises (Post) and 15 minutes after exercises (Retention) (Chapter 4). Eleven individuals post-stroke performed a single session of 50 fast knee and ankle OKC exercises and postural responses were assessed Pre and Post exercises (Chapter 5). Electromyographic (EMG) activity was measured bilaterally in the rectus femoris (RF), biceps femoris (BF), tibialis anterior (TA), and soleus (SOL) muscles.\nResult: The squat was performed slower in the stroke group than controls, with impaired temporal coupling between the knee movement and postural sway. The paretic BF EMG was delayed with a reduced slope and the paretic RF EMG area was reduced. The squat was initiated with the non-paretic leg as a compensatory strategy in the low motor recovery group whereas the paretic leg was used in an adaptive manner in the high motor recovery group (Chapter 2). The temporal coupling improved and EMG area of the paretic TA, BF and RF increased in the squats. In the steps, the paretic BF and RF EMG area increased in the stepping leg and the paretic SOL and RF EMG area increased in the stance leg (Chapter 3). The paretic BF EMG area and slope increased after exercises in the arm raise task. In the load drop task, the paretic BF EMG deactivation improved and was retained after 15 minutes. Weight bearing symmetry also improved with exercise (Chapter 4). The paretic BF, RF, TA EMG area increased along with an increase in peak velocity and power during the OKC exercises. The arm acceleration and BF EMG area increased in the arm raise task (Chapter 5).\nConclusion: This dissertation reveals the positive effects of exercise emphasizing speed on motor control post-stroke.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.039
GPT teacher head0.338
Teacher spread0.300 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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