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Record W3027359067 · doi:10.14447/jnmes.v22i2.a06

Research on Human Motion Test Based on Biomechanical Sensors Using Electromyography and Pressure Detection Systems

2020· article· en· W3027359067 on OpenAlexvenueno aff
Jianwei Deng, Li Cao

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2020
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsnot available
Fundersnot available
KeywordsElectromyographyHuman motionTest (biology)Motion (physics)Computer sciencePhysical medicine and rehabilitationAcousticsArtificial intelligenceMedicinePhysicsGeology

Abstract

fetched live from OpenAlex

As an important tool for studying the biological and sport dynamic principles of human motion, biomechanical sensors are widely used in the related studies.In order to clarify the role of biosensors in human motion, this paper designed Polyvinylidene Fluoride (PVDF) piezoelectric sensors and applied them to in situ high leg lift movement to analyze muscle biomechanics.The results showed that PVDF sensors had a good effect on the study of the biomechanics of human motion and could provide technical support for the study of human motion.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.000
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 head0.062
GPT teacher head0.308
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 designBench or experimental
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

Citations1
Published2020
Admission routes1
Has abstractyes

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Same venueJournal of New Materials for Electrochemical SystemsSame topicMuscle activation and electromyography studiesFrench-language works237,207