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Record W2012312483 · doi:10.1088/0967-3334/23/3/701

Progress in Ambulatory Assessment: Computer Assisted Psychological and Psychophysiological Methods in Monitoring and Field Studies

2002· article· en· W2012312483 on OpenAlexaboutno aff
Stuart J Meldrum

Bibliographic record

VenuePhysiological Measurement · 2002
Typearticle
Languageen
FieldEngineering
TopicNon-Invasive Vital Sign Monitoring
Canadian institutionsnot available
Fundersnot available
KeywordsAmbulatoryField (mathematics)PsychologyApplied psychologyComputer scienceMedicineData scienceEngineeringInternal medicine

Abstract

fetched live from OpenAlex

Edited by Jochen Fahrenberg and Michael Myrtek 2001 Seattle, Toronto, Bern and Gottingen: Hogrefe and Huber 627 pp hardcover ISBN 0-88937-225-X US$49.95 CAN$74.95 Euro49.95 SFr84.00 £32.45 During the 1950s, Holter and colleagues developed a number of portable recording devices which served to introduce the concept of `ambulatory monitoring'. Early devices were principally for cardiovascular monitoring, intended to allow patients' symptoms to be related to the underlying physiology. More recent devices, especially those based on portable computers, now allow various tests of cognitive and intellectual ability to be carried out on ambulatory subjects, and to relate performance in these tests to the physiological state. The book has its origins in a workshop on ambulatory assessment, which was held at the University of Freiburg, Germany, in 1999. Thirty-five chapters explore the use of computer assisted methods of ambulatory assessment, both as research tools and in applied settings. The perspective is largely a European one, with only a few of the 80 or so contributors from North America. The text is presented in two parts, the first dealing with psychological assessment and the second with more physiological aspects of the subject. While the second part of the book may be of greater interest to readers of this journal, the first part, dealing as it does with mental and emotional testing, may well provide more unfamiliar material. Here the first few chapters deal with posture and activity monitoring using accelerometry, and the influences these can have on other psychological variables. Several chapters follow this on aspects of blood pressure and heart rate monitoring. Several chapters then discuss monitoring of respiratory variables, particularly their role in the assessment of patients suffering from anxiety. Following chapters deal with monitoring in the workplace, in stressful situations such as working at night, as an air traffic controller, and flying an aircraft Towards the end of the book the emphasis is on developments in the technology that has made ambulatory monitoring possible. There is a review of recent recording devices, dealing principally with those that are commercially available. This is followed by a discussion on the transition from ambulatory assessment to telemedicine, reviewing the concepts and the problems to be overcome. The book concludes with an excellent overview of the historical development of ambulatory monitoring and assessment, written by one of the editors. The majority of chapters are supported by extensive bibliographies. In spite of the fact that the book is based on a meeting held in 1999, many chapters have been revised and updated to include references to papers published during 2000. Readers will find these bibliographies particularly useful as many of the papers cited are published in psychology journals which are not included in the popular medical databases.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.049
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0490.030

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 head0.210
GPT teacher head0.409
Teacher spread0.199 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations111
Published2002
Admission routes1
Has abstractyes

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