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Effects of Restricting Ankle Joint Motions on Muscle Activity: Preliminary Investigation with an Unpowered Exoskeleton

2022· article· en· W4312463231 on OpenAlexaff
R.K.P.S. Ranaweera, A.H. Weerasingha, W.P.K. Withanage, A.D.K.H. Pragnathilaka, R. A. R. C. Gopura, T.S.S. Jayawardana, George K. I. Mann

Bibliographic record

Venue2022 Moratuwa Engineering Research Conference (MERCon) · 2022
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsMemorial University of Newfoundland
FundersUniversity of Moratuwa
KeywordsExoskeletonAnkleJoint (building)Physical medicine and rehabilitationComputer scienceLeg muscleSimulationEngineeringStructural engineeringMedicineAnatomy

Abstract

fetched live from OpenAlex

The human ankle comprises multiple joints and supports triplanar motions to allow the foot to pronate or supinate during walking. However, ankle exoskeletons are mainly designed to assist propulsion whilst inhibiting other degrees of freedom. The kinematic constraints posed by the simplified joint mechanisms may negatively affect the wearer’s performance. In that context, this paper presents a preliminary investigation on the effects of restraining ankle motions during level walking with an unpowered ankle exoskeleton having compatible joint axes. The work investigated the changes in muscle activity in the lower limbs under various constraining conditions. A healthy male subject took part in five tests involving different combinations of kinematic restrictions of the ankle. The electrical activities of key muscles were recorded using a surface electromyography measurement system. The root-mean-square feature of signals was used for comparing results. The analysis confirms that constraining non-sagittal plane motions has caused significant changes to the activities of muscles. The investigation reveals the relative importance of developing ankle mechanisms that promote higher kinematic compliance. In the future, further studies should be conducted to reaffirm the statistical significance of muscle activity across multiple test subjects and assess human comfort to derive specific design guidelines for ankle devices.

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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.032
GPT teacher head0.261
Teacher spread0.230 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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