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Record W2909765249 · doi:10.1109/iemcon.2018.8614753

Simple Heart Rate Monitoring System with a MEMS Gyroscope for Sleep Studies

2018· article· en· W2909765249 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicNon-Invasive Vital Sign Monitoring
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGyroscopeStandard deviationVibrating structure gyroscopeComputer scienceHeart rateHeart rate variabilityRespiratory ratePolysomnographyAccelerometerMedicineStatisticsMathematicsEngineeringBlood pressureApneaAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

Heart rate (HR), the number of heart beats every minute, is the most relied upon vital sign for detecting health deterioration. It is no surprise, then, that the recording of HR is required in sleep studies as well. However, the standard monitoring method, the electrocardiogram (ECG), can be uncomfortable and intrusive, especially during sleep. Here, we present an HR monitoring system that uses the angular rate data from a single axis of a MEMS gyroscope to detect heartbeats. With a mean absolute error (MAE) and standard deviation of the absolute error (SDAE) values of -0.3505bpm and +2.7167bpm, in average, when our tests are compared with a reference ECG signal, we show that our system is accurate enough to track HR changes. Furthermore, the simplicity of our proposed approach makes it an ideal candidate for its implementation as a real-time, portable embedded system.

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.

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 score0.069
Threshold uncertainty score0.774

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 science0.0000.000
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 head0.029
GPT teacher head0.277
Teacher spread0.248 · 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

Quick stats

Citations21
Published2018
Admission routes1
Has abstractyes

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