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Intelligent IoT (I<sup>2</sup>oT) Biomedical Wearable System based on Smartphone Application

2020· article· en· W3108180771 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
TopicIntravenous Infusion Technology and Safety
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsWearable computerSyringeComputer scienceSoftware deploymentEmbedded systemSyringe driverHealth careModalitiesSmartphone appRemote patient monitoringWearable technologyHuman–computer interactionOperating systemEngineering

Abstract

fetched live from OpenAlex

This work presents a novel way to realize lightweight, microliter-precision and wirelessly controlled syringe pump using a smartphone application developed by App Inventor. The syringe infusion pumps are used at home by the patients or during ambulation cases to medical services, for that lightweight device and physician supervision are highly required. To reduce syringe infusion pumps weight, some electronic parts are removed, and replaced by a Smartphone application to manage and control the syringe infusion pump. Also, The Smartphone technology can be transformative to the deployment, monitoring and remote control in healthcare providing systems. Thanks to its ubiquitous availability, mobile-based solutions can open new applications, resolve many remaining healthcare providing problems though remote control and big data management, in addition to a plethora of network communications protocols and modalities.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.966
Threshold uncertainty score0.999

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)0.0000.002

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 head0.007
GPT teacher head0.188
Teacher spread0.181 · 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