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Record W2134225908 · doi:10.1109/tnsre.2007.897005

Kinematic and Kinetic Analysis of a Stepping-in-Place Task in Below-Knee Amputee Children Compared to Able-Bodied Children

2007· article· en· W2134225908 on OpenAlexaff
Hugo Centomo, A.K. David, Luc Martin, Franois Prince

Bibliographic record

VenueIEEE Transactions on Neural Systems and Rehabilitation Engineering · 2007
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsTask (project management)Physical medicine and rehabilitationKinematicsAnklePsychologyHip flexionGaitExcursionCerebral palsyPhysical therapyMedicineRange of motionSurgeryEngineering

Abstract

fetched live from OpenAlex

It has been demonstrated that below-knee amputee (BKA) subjects use specific compensation strategies to overcome their physical limitations. Biomechanical studies emphasize that the motor strategies adopted by BKA adults differ between their amputated limb and their nonamputated limb and from those employed by able-bodied (AB) subjects. The purpose of this investigation was to compare the motor solutions used by control AB and BKA children during a stepping-in-place (SIP) task and to assess how they regulate the coordination of their nonamputated and amputated limbs during this task. Eight BKA children and eight AB children paired for gender, age, weight and height participated in our study. One-way analysis of variances (ANOVAs) were performed on peaks of angular excursion, moment, and power at the hip, knee, and ankle to compare motor strategies between the BKA and AB groups. The main results of our experiment showed that even if BKA and AB children did the task with almost the same kinematics, the kinetic data revealed completely different mechanisms of the two groups to achieve the SIP task, and BKA children had a symmetrical interlimb strategy. SIP, a simple task compared to gait at the level of neuro-musculoskeletal demands, could thus offer a transition task to physical therapists for below-knee recently-amputated children.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.690
Threshold uncertainty score0.811

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
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 head0.005
GPT teacher head0.203
Teacher spread0.199 · 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 designSimulation or modeling
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

Citations10
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Transactions on Neural Systems and Rehabilitation EngineeringSame topicMuscle activation and electromyography studiesFrench-language works237,207