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Record W2617597639 · doi:10.11159/icbes17.131

Analysis of the Spatio-Temporal Parameters of an Amputee Patient vs. a Healthy Patient

2017· article· en· W2617597639 on OpenAlexvenueno aff
Brigette Paola Torres Bello, Yuliana Ruiz Piragauta, Esperanza Camargo Casallas

Bibliographic record

VenueProceedings of the World Congress on Electrical Engineering and Computer Systems and Science · 2017
Typearticle
Languageen
FieldComputer Science
TopicGaze Tracking and Assistive Technology
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceArtificial intelligenceMedicineComputer vision

Abstract

fetched live from OpenAlex

The purpose of this article is to evaluate the spatio-temporal parameters of an amputee versus a healthy patient, since it is a way of recognizing the failures and observations of the gait cycle as a result of the state of the prosthesis. For this study it is necessary to deepen the biomechanics of the lower extremities by investigating the similarity that exists between a prosthesis and the biological part of the amputated joint. The acquired data were taken from the sagittal and frontal plane, in an orthopedic and rehabilitation center for both types of patients (Transtibial Amputee and Person with intact extremities), these data were processed using inertial sensors of TechnNaid equipment and taken to a MarchaHumanaET software, which provides the values of the spatio-temporal gait parameters for each subject.

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 score0.860
Threshold uncertainty score0.338

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.009
GPT teacher head0.221
Teacher spread0.212 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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