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Record W2333422805 · doi:10.1213/ane.0b013e31825d638c

A Vibro-Tactile Display for Clinical Monitoring

2012· article· en· W2333422805 on OpenAlexafffund
Maryam Dosani, Kate Hunc, Guy A. Dumont, Dustin Dunsmuir, Pierre Barralon, Stephan Schwarz, Joanne Lim, J. Mark Ansermino

Bibliographic record

VenueAnesthesia & Analgesia · 2012
Typearticle
Languageen
FieldMedicine
TopicHealthcare Technology and Patient Monitoring
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsMedicineUsabilityAirwaySoftwareAnesthesiaReal-time computingSimulationBiomedical engineeringComputer scienceHuman–computer interaction

Abstract

fetched live from OpenAlex

BACKGROUND: Vibro-tactile displays use human skin to convey information from physiological monitors to anesthesiologists, providing cues about changes in the status of the patient. In this investigation, we evaluated, in a real-time clinical environment, the usability and wearability of a novel vibro-tactile display belt recently developed by our group, and determined its accuracy in identifying events when used by anesthesiologists. METHODS: A prospective observational study design was used. During routine anesthesia, a standard physiological monitor was connected to a software tool that used algorithms to automatically identify changing trends in mean noninvasive arterial blood pressure, expired minute ventilation, peak airway pressure, and end-tidal carbon dioxide partial pressure. The software was wirelessly interfaced to a vibro-tactile belt worn by the anesthesiologist. Each physiological variable was mapped to 1 of 4 tactor locations within the belt. The direction (increase/decrease) and 2 levels of change (small/large) were encoded in the stimulation patterns. A training session was completed by each anesthesiologist. The system was activated in real-time during anesthesia alongside routine physiological monitors. When the algorithms detected changes in the patient, the belt vibrated at the appropriate location with the pattern corresponding to the level and direction of change. Using a touch screen monitor the anesthesiologist was to enter the vibro-tactile message by first identifying the variable, then identifying the level and direction of change. Usability and wearability questionnaires were to be completed. The percentage of correct identification of the physiological trend, the direction of change, and the level of change were primary outcome variables. The mean usability score and wearability results were secondary outcome variables. We hypothesized that anesthesiologists would correctly identify the events communicated to them through the vibro-tactile belt 90% of the time, and that anesthesiologists would find the vibro-tactile belt usable and wearable. RESULTS: Seventeen anesthesiologists evaluated the display during 57 cases. The belt was operational for a mean (SD) duration of 75 (41) minutes per case. Seven cases were excluded from analysis because of technical failures. Eighty-one percent (confidence interval [CI], 77% to 84%) of all stimuli were decoded. The physiological trend, the direction of change, and the level of change were correctly identified for 97.7% (CI 96%-99%), 94.9% (CI 92%-97%), and 93.5% of these stimuli (CI, 91%-96%), respectively. Fourteen anesthesiologists completed the usability and wearability questionnaires. The mean usability score was 4.8 of a maximum usability score of 7. CONCLUSIONS: Anesthesiologists found a vibro-tactile belt to be wearable and usable and could accurately decode vibro-tactile messages in a real-time clinical environment.

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)0.004
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.116
GPT teacher head0.427
Teacher spread0.311 · 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

Citations21
Published2012
Admission routes2
Has abstractyes

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