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Record W2111716526 · doi:10.1109/iembs.2007.4353263

Optimizing the Tactile Display of Physiological Information: Vibro-Tactile vs. Electro-Tactile Stimulation, and Forearm or Wrist Location

2007· article· en· W2111716526 on OpenAlexaff
G. Ng, Pierre Barralon, Guy A. Dumont, Stephan Schwarz, J. Mark Ansermino

Bibliographic record

VenueConference proceedings · 2007
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsWristTactile displayForearmSensory stimulation therapyTactile sensorTactile perceptionComputer scienceComputer visionNeuroprostheticsStimulationPhysical medicine and rehabilitationArtificial intelligenceMedicinePsychologyPerceptionNeuroscienceAnatomyRobot

Abstract

fetched live from OpenAlex

Anesthesiologists use physiological data monitoring systems with visual and auditory displays of information to monitor patients in the operating room (OR). The efficacy of visual-audio systems may impose an increase in patient risk when the demand for constant switching of attention between the patient and the visual monitoring system is high. This is evidenced by auditory alarms frequently being neglected in a noisy OR environment. Hence, the use of a complementary patient data monitoring system, which utilizes other sensory modalities, could be of great value. In this paper, we describe a series of experiments designed to determine the performances of a tactile display that could be used to convey patient's physiological information to the attending anesthesiologist. We tested both vibro-tactile and electro-tactile display prototypes in their ability to convey information using an alert scheme of four distinct tactile stimuli. Using pseudo-clinical data, the display was designed, for example, to provide an alert when a change in the monitored heart rate occurred. Based on previous research in human physiology and psychophysics, we selected the forearm and wrist of the user's non-dominant hand as the stimulation site. In our study of 30 subjects, we evaluated the response time and accuracy of tactile pattern recognition to compare (1) the performance of a vibro-tactile display on the forearm (VF) and an electro-tactile display on the forearm (EF), and (2) the localization of stimulation between the forearm (VF) and a vibro-tactile display on the wrist (VW). A post-study questionnaire was completed by each subject to assess the comfort and usability of the three prototypes. We found that both VF and VW were superior to the EF in both accuracy and comfort and, that there were no differences between the wrist and the forearm. In conclusion, the tactile-display prototypes designed to alert the clinician of adverse changes in a patient's physiological state efficaciously and unobtrusively delivered these data and warranted further investigation and development.

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)0.003
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.043
GPT teacher head0.294
Teacher spread0.251 · 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

Citations39
Published2007
Admission routes1
Has abstractyes

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