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Record W2143210349 · doi:10.1027/0269-8803.19.3.195

Comparability of Spot Versus Band Electrodes for Impedance Cardiography

2005· article· en· W2143210349 on OpenAlexafffund
Jennifer J. McGrath, William H. O’Brien, Hilary J. Hassinger, Purvi Shah

Bibliographic record

VenueJournal of Psychophysiology · 2005
Typearticle
Languageen
FieldNeuroscience
TopicEEG and Brain-Computer Interfaces
Canadian institutionsConcordia University
FundersCanadian Institutes of Health Research
KeywordsImpedance cardiographyElectrodeAmbulatoryStroke volumeCardiologyElectrical impedanceMedicineBiomedical engineeringMaterials scienceInternal medicineEjection fractionChemistryPhysicsHeart failure

Abstract

fetched live from OpenAlex

Abstract. Although band and spot electrodes have been compared in prior research, they have not been evaluated (a) at identical anatomical locations, (b) during a single laboratory session, (c) with measures taken in close temporal proximity, (d) using a single impedance cardiograph unit, or (e) using sufficiently powerful statistical tests. Thirty-one healthy young adults completed a psychophysiological assessment which consisted of baseline, mental arithmetic stressor, and recovery conditions. Data from spot and band electrodes were collected by alternating between electrode types every minute of the experiment. Correlations between spot and band electrodes at absolute levels of all cardiovascular measures (cardiac output, impedance derivative, basal impedance level, Heather index, heart rate, left ventricular ejection time, pre-ejection period, stroke volume) were of high magnitude (r avg = .78), while the correlations for difference scores were lower (r avg = .50). Analyses of mean levels indicated spot electrodes yielded significantly lower values for the impedance derivative, Heather index, and basal impedance, and higher values for cardiac output and stroke volume, than band electrodes. The advantages and disadvantages associated with spot and band electrode configurations, as well as their use in ambulatory recording, are discussed.

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 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 score0.011
Threshold uncertainty score0.368

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 head0.038
GPT teacher head0.337
Teacher spread0.299 · 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 teacher head, 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

Citations11
Published2005
Admission routes2
Has abstractyes

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