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Record W2043668245 · doi:10.1109/ultsym.2013.0291

Development of wearable and flexible ultrasonic sensor for skeletal muscle monitoring

2013· article· en· W2043668245 on OpenAlexaff
Ibrahim AlMohimeed, Hisham Turkistani, Yuu Ono

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Sensor and Energy Harvesting Materials
Canadian institutionsCarleton University
FundersSaudi Arabian Cultural Bureau
KeywordsUltrasonic sensorWearable computerMaterials scienceBiomedical engineeringFlexibility (engineering)AcousticsComputer scienceEmbedded systemEngineering

Abstract

fetched live from OpenAlex

A wearable and flexible ultrasonic sensor was developed for monitoring of skeletal muscle contraction. The sensor was constructed using a PVDF piezoelectric polymer film without a matching layer or backing material. Due to its lightness (less than 1 gram), thinness (200 µm) and flexibility, this sensor was wearable and enabled non-invasive and continuous muscle monitoring without restricting muscle movement, which is not feasible using a conventional handheld ultrasonic probe. The developed sensor was used to monitor muscle contractions in the index finger by ultrasonic pulse-echo measurements and in the forearm by through-transmission measurements. It was successfully demonstrated that the tissue thickness variations were measured in accordance with the muscle contraction performed.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.169
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

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

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 head0.019
GPT teacher head0.233
Teacher spread0.214 · 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 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

Citations53
Published2013
Admission routes1
Has abstractyes

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