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Record W4411754536 · doi:10.54941/ahfe1006507

Vibration Exposure During Neonatal Patient Transport by Ground and Air Ambulance

2025· article· en· W4411754536 on OpenAlexaboutno aff
Keely Gibb, Michael Avarello, Patrick Kehoe, Andrew Law, Eric Chen, Eleanor Gerson, Kim Greenwood, Andrew Ibey, Jean Ngoie, Stephanie Redpath, Adrian D. C. Chan, James R. Green, Robert Langlois

Bibliographic record

VenueAHFE international · 2025
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsnot available
Fundersnot available
KeywordsVibrationAir transportAeronauticsMedicineEnvironmental scienceAcousticsEngineeringPhysics

Abstract

fetched live from OpenAlex

Neonatal transport is often necessary when newborn patients require specialized medical care. In Ontario, Canada, a standardized Neonatal Patient Transport System (NPTS) is used to ensure consistency and interoperability across healthcare facilities. Whether transport is conducted via ground ambulance, fixed-wing, or rotary-wing air ambulances, the transport system and patient are subjected to unique, and often high, levels of vibration. Vibration is transmitted throughout the NPTS and interface systems such that the patients may experience a different ride quality than transport team members, pilots, or drivers. We have investigated the vibration amplitudes and spectra from 1-150 Hz at multiple locations (floor, NPTS, pilot/driver floor, and pilot/driver seat) within four different vehicles used for neonatal transportation in Ontario (one ground ambulance, one helicopter, and two fixed-wing aircraft). Kinematics were used to evaluate locations where sensors were not present during data collection. A low-frequency range of 1-20 Hz was used for comparison of measured and predicted results, to reduce noise in kinematic acceleration evaluation while focusing on the range of human body resonance. The largest amplitude vibrations were measured in the vertical direction in all vehicles, with the ground ambulance acceleration being greatest. Amplification of ground vehicle motion to the patient location was present across much of frequency range of interest, although the highest transmissibility occurred in the helicopter vertical direction at 10 Hz. The vibration in the air ambulances was heavily dominated by the rotor or propeller frequency, while in the ground ambulance it was more significant at low frequencies related to vehicle suspension. Differing response spectra suggest efforts to improve ride quality for patients may need to be tailored to the vehicle type, in order to prevent patient exposure to high amplitude vibration.

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 score0.255
Threshold uncertainty score0.305

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 head0.007
GPT teacher head0.313
Teacher spread0.307 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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