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Record W2103317443 · doi:10.1109/health.2011.6026724

Ubiquitous WBAN-based Electrocardiogram monitoring system

2011· article· en· W2103317443 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Body Area Networks
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceBody area networkWearable computerWireless sensor networkRemote patient monitoringThe InternetReal-time computingStandardizationTelemedicineVital signsServerEmbedded systemData acquisitionBase stationComputer networkHealth careOperating system

Abstract

fetched live from OpenAlex

This paper presents a remote patient monitoring system within the scope of Body Area Network standardization. In this regime, wireless sensor networks are used to continuously acquire the patient's Electrocardiogram signs and transmit data to the base station via IEEE.802.15. The personal Server (PS) which is responsible to provide real-time displaying, storing, and analyzing the patient's vital signs is developed in MATLAB. It also transfers ECG streams in real-time to a remote client such as a physician or medical center through internet. The PS has the potential to be integrated with home or hospital computer systems. A prototype of this system has been developed and implemented. The developed system takes advantage of two important features for healthcare monitoring: (i) ECG data acquisition using wearable sensors and (ii) real-time data remote through internet. The fact that our system is interacting with sensor network nodes using MATLAB makes it distinct from other previous works.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score0.705

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 head0.015
GPT teacher head0.184
Teacher spread0.169 · 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

Citations12
Published2011
Admission routes2
Has abstractyes

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