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Record W4213128887 · doi:10.1002/aet2.10733

Characterizing the biomechanical differences between novice and expert point‐of‐care ultrasound practitioners using a low‐cost gyroscope and accelerometer integrated sensor: A pilot study

2022· article· en· W4213128887 on OpenAlexaff
Ross Prager, Paul Pageau, Timothy Hodges, Christina Yan, Michael Y. Woo, Marie‐Joe Nemnom, Scott J. Millington, Matthew Holden, Raphaël St-Gelais, Warren J. Cheung

Bibliographic record

VenueAEM Education and Training · 2022
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsCarleton UniversityOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsAccelerometerMedicineAccelerationUltrasoundAngular velocityAngular accelerationNuclear medicineRadiologyBiomedical engineeringMedical physicsComputer sciencePhysics

Abstract

fetched live from OpenAlex

Abstract Introduction Point‐of‐care ultrasound (POCUS) has become an important diagnostic tool in acute care medicine; however, little is known about the biomechanical differences between novice and expert practitioners. Methods A low‐cost ($50 CAD) gyroscope and accelerometer integrated sensor was assembled and affixed to an ultrasound probe. Seventeen participants, nine novices and eight experts, were recruited to perform three abdominal and four cardiac scans on a standardized patient. Participant demographics, time per scan, average acceleration, average angular velocity, decay in acceleration and angular velocity over time, and frequency of probe movements were analyzed. Video capture with blinded video review was scored. Results On video review, experts had higher image optimization and acquisition scores for both abdominal and cardiac scans. Experts had shorter scan times for abdominal (7 s vs. 26 s, p = 0.003) and cardiac (11 s vs. 26 s, p < 0.001) scans. There was no difference in average acceleration ( g ) between novices and experts performing abdominal (1.02 vs. 1.01, p = 0.50) and cardiac (1.01 vs. 1.01, p = 0.45) scans. Experts had lower angular velocity (°/s) for abdominal scans (10.00 vs. 18.73, p < 0.001) and cardiac scans (15.61 vs. 20.33, p = 0.02) There was a greater decay in acceleration over time for experts performing cardiac scans compared to novices (−0.194 vs. −0.050, p = 0.03) but not for abdominal scans or when measuring angular velocity. The frequency of movements (Hz) was higher for novices compared to experts for abdominal (16.68 vs. 13.79, p < 0.001) and cardiac (17.60 vs. 13.63, p = 0.002) scans. Discussion This study supports the feasibility of a low‐cost gyroscope and accelerometer integrated sensor to quantify the biomechanics of POCUS. It may also support the concept of “window shopping” as a method by which experts obtain abdominal and cardiac views, where sliding is used to find an acoustic window, then smaller rocking and tilting probe movements are used to refine the image.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.308
Threshold uncertainty score0.445

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 head0.136
GPT teacher head0.393
Teacher spread0.257 · 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 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

Citations6
Published2022
Admission routes1
Has abstractyes

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