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Record W2978308038 · doi:10.2196/16250

Evaluating the Accuracy of the VitalWellness Device

2019· article· en· W2978308038 on OpenAlexvenueno aff
Nicole Polanco, Sharon Odametey, Neda Derakhshani, Mark Khachaturian, Connor Devoe, Kamal Jethwani, Sujay Kakarmath

Bibliographic record

VenueIproceedings · 2019
Typearticle
Languageen
FieldEngineering
TopicNon-Invasive Vital Sign Monitoring
Canadian institutionsnot available
Fundersnot available
KeywordsVital signsHeart rateMedicineStandard deviationRespiratory rateGold standard (test)Blood pressurePhotoplethysmogramPhysical therapyStatisticsSurgeryInternal medicineComputer scienceMathematics

Abstract

fetched live from OpenAlex

Background Wellness devices for health tracking have gained popularity in recent years. Additionally, portable and readily accessible wellness devices have several advantages when compared to traditional medical devices found in clinical environments The VitalWellness device is a portable wellness device that can potentially aide vital sign measuring for those interested in tracking their health. Objective In this diagnostic accuracy study, we evaluated the performance of the VitalWellness device, a wireless, compact, non-invasive device that measures four vital signs (blood pressure (BP), heart rate (HR), respiratory rate (RR), and body temperature using the index finger and forehead. Methods Volunteers age ≥18 years were enrolled to provide blood pressure (BP), heart rate (HR), respiratory rate (RR), and body temperature. We recruited participants with vital signs that fell within and outside of the normal physiological range. A sub-group of eligible participants were asked to undergo an exercise test, aerobic step test and/or a paced breathing test to analyze the VitalWellness device’s performance on vital signs outside of the normal physiological ranges for HR and RR. Vital signs measurements were collected with the VitalWellness device and FDA-approved reference devices. Mean, standard deviation, mean difference, standard deviation of difference, standard error of mean difference, and correlation coefficients were calculated for measurements collected; these measurements were plotted on a scatter plot and a Bland-Altman plot. Sensitivity analyses were performed to evaluate the performance of the VitalWellness device by gender, skin color, finger size, and in the presence of artifacts. Results 265 volunteers enrolled in the study and 2 withdrew before study completion. Majority of the volunteers were female (62%), predominately white (63%), graduated from college or post college (67%), and employed (59%). There was a moderately strong linear relationship between VitalWellness BP and reference BP (r=0.7, P<.05) and VitalWellness RR and reference RR measurements (r=0.7, P<.05). The VitalWellness HR readings were significantly in line with the reference HR readings (r=0.9, P<.05). There was a weaker linear relationship between VitalWellness temperature and reference temperature (r=0.3, P<.05). There were no differences in performance of the VitalWellness device by gender, skin color or in the presence of artifacts. Finger size was associated with differential performance for RR. Conclusions Overall, the VitalWellness device performed well in taking BP, HR, and RR when compared to FDA-approved reference devices and has potential serve as a wellness device. To test adaptability and acceptability, future research may evaluate user’s interactions and experiences with the VitalWellness device at home. In addition, the next phase of the study will evaluate transmitting vital sign information from the VitalWellness device to an online secured database where information can be shared with HCPs within seconds of measurement.

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 score0.011
Threshold uncertainty score0.330

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 science0.0010.000
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 head0.032
GPT teacher head0.294
Teacher spread0.262 · 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".

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Citations0
Published2019
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Has abstractyes

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