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Record W4390767561 · doi:10.23977/jemm.2023.080414

Structural Design and Dynamics Simulation of Lower Limb Fitness Exoskeleton

2023· article· en· W4390767561 on OpenAlexvenueno aff
Lan Duan, D. Li, Chengwei Bao, Xueming Qian

Bibliographic record

VenueJournal of Engineering Mechanics and Machinery · 2023
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsnot available
FundersEducation Department of Shaanxi Province
KeywordsExoskeletonLower limbCardiorespiratory fitnessPhysical medicine and rehabilitationElbowDegrees of freedom (physics and chemistry)Computer scienceSimulationPhysical therapyMedicineAnatomyPhysics

Abstract

fetched live from OpenAlex

Human beings have given more attention to health as civilization has progressed. In this study, the structural properties of human lower limb joints and degrees of freedom in the lower limbs were investigated from a bionic perspective. The fitness exoskeleton structure of lower limbs was designed for exercising people's lower limb muscles and cardiorespiratory function by combining the functions, operating principle, and structural composition implemented by the exoskeleton. The fitness effect was obtained by applying loads to the elbow and knee joints and then overcoming them with leg movement. This exoskeleton, like any other typical human-computer integration system with bipedal walking characteristics, depends on human motion information to control the structure.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.215
Teacher spread0.205 · 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 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Engineering Mechanics and MachinerySame topicMuscle activation and electromyography studiesFrench-language works237,207