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Record W4382072723 · doi:10.59934/jaiea.v2i3.199

Design and Development of a Realtime Human Heart Rate Measurement System Using IOT-Based Pulse Sensors

2023· article· en· W4382072723 on OpenAlexaff
Surja Arafat, Akim Manaor Hara Pardede

Bibliographic record

VenueJournal of Artificial Intelligence and Engineering Applications (JAIEA) · 2023
Typearticle
Languageen
FieldEngineering
TopicNon-Invasive Vital Sign Monitoring
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsHeart ratePulse (music)Heart rate monitorComputer sciencePulse rateReal-time computingMedicineTelecommunicationsInternal medicineBlood pressure

Abstract

fetched live from OpenAlex

The heart is one of the important organs that humans have, whose function is to pump blood throughout the body and accommodate it again after cleaning the lungs. Heart rate beats per minute (bpm) is a parameter to show the condition of the heart, and the way to find out the condition of the heart is to know the frequency of the heart rate. This heart rate monitoring tool is designed based on the NodeMCU ESP8266 and a pulse sensor to detect heart rate. This study aims to make it easier to know the heart rate frequency in realtime. A heart rate monitoring tool based on NodeMCU ESP8266 has been designed with a pulse sensor to detect heart rate. Heart rate data from monitoring results will then be sent via a wifi network connection and displayed on the Smartphone.

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)0.000
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0030.001

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 head0.102
GPT teacher head0.284
Teacher spread0.183 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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