MétaCan
Menu
Back to cohort
Record W2978706367 · doi:10.2196/15203

Evaluating the Accuracy of an Integrated Vital Sign Measurement Wellness Device

2019· article· en· W2978706367 on OpenAlexvenueno aff
Nicole Polanco, Sharon Odametey, Neda Derakhshani, Mark Khachaturian, Connor Devoe, Kamal Jethwani, Sujay Kakarmath

Bibliographic record

VenueIproceedings · 2019
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsVital signsMedicineHeart rateHealth carePhysical therapyTest (biology)Respiratory rateMedical emergencyBlood pressureSurgeryInternal medicine

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. Building tools for patients to manage their health independently may benefit their health in the long run by improving health care providers’ (HCPs) awareness of their patients’ health information outside of the clinic. Increased access to portable wellness devices that track vital signs may increase how patients and HCPs track and monitor chronic conditions which can improve health outcomes. The VitalWellness is a portable wellness device that can potentially aid vital sign measuring for those interested in tracking their health. Objective In this diagnostic accuracy study, we evaluated the clinical performance of the VitalWellness, a wireless, compact, non-invasive device that measures four vital signs using the index finger and forehead against reference vital signs devices used in the hospital setting. Methods Volunteers age ≥18 years were enrolled to provide blood pressure (BP), heart rate (HR), respiratory rate (RR), and body temperature. We recruited volunteers with vital signs that fell within and outside of the normal physiological range, depending on the measurements they consented to undergo. A subgroup of eligible volunteers 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 We enrolled 265 volunteers in the study and 2 withdrew before study completion. The majority of 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 bewteen 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 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)0.006
metaresearch head score (Gemma)0.026
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.217
GPT teacher head0.467
Teacher spread0.250 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueIproceedingsSame topicBehavioral Health and InterventionsFrench-language works237,207