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Record W2130342165 · doi:10.1109/iembs.2008.4650426

Exploring the human grip force system: A preliminary study

2008· article· en· W2130342165 on OpenAlexaff
Alejandro Villasenor-Herrera, Sophie J. De Serres, R. Wagner, Robert E. Kearney

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsLatency (audio)Nonlinear systemReflexAmplitudeControl theory (sociology)Computer sciencePsychologyNeuroscienceControl (management)PhysicsArtificial intelligenceTelecommunications

Abstract

fetched live from OpenAlex

It has been postulated that cutaneo-receptors from the digits contribute to the control of manipulatory functions of the hand. However, few studies have examined the dynamics of the human grip force system (HGFS) in terms of the dynamic relationship between the vertical loads, taken as an input and the resulting grip force, taken as the output. This paper describes the experimental procedures we have developed to explore the HGFS and presents some initial experimental results. These demonstrate that the step response of the HGFS is biphasic. The first, short latency phase, likely involves only passive and intrinsic components. The second, longer latency phase is likely related to reflex mechanisms since it is preceded by a strong burst of EMG. Moreover, the HGFS response depended nonlinearly on the amplitude and direction of the load applied. These results indicate that further investigation of HGFS dynamics will require the use of nonlinear identification methods.

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)0.001
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 score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.075
GPT teacher head0.229
Teacher spread0.154 · 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

Citations2
Published2008
Admission routes1
Has abstractyes

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