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Record W1521259444 · doi:10.1049/cp:20081099

Activity prediction for in-home activity monitoring

2008· article· en· W1521259444 on OpenAlexaff
G. Virone, Andrew Sixsmith

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicContext-Aware Activity Recognition Systems
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsComputer scienceActivities of daily livingSoftwareEveryday lifeBaseline (sea)Period (music)CognitionApplied psychologyGerontologyPsychologyMedicine

Abstract

fetched live from OpenAlex

In this paper, we propose an extension to a generic model developed for elaborating person's lifestyle patterns and changes in those patterns which could be related to health decline. The baseline model aims at a better understanding of the behaviours engaged in various housing contexts such as conventional housing or Assisted Living (AL) facilities and exploring irregularities within the life rhythm of the resident's everyday life activities. The model, embedded into a customized software program, has been extended to predict the progression of a particular activity on the basis of a circadian period (24- hour period) in order to detect unexpected events such as slowdowns or disruptions which could indicate changes in health status, cognitive or motor impairments. The objective is to help caregivers provide better assessment of functional health status and preventative assistance. A case study, elaborated through software simulations, is presented to show the potential of the software application to determine life patterns in conjunction with activity trend indicators that may indicate health deterioration. (4 pages)

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.666
Threshold uncertainty score0.618

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 communication0.0000.002
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 head0.069
GPT teacher head0.281
Teacher spread0.212 · 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 designObservational
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

Citations6
Published2008
Admission routes1
Has abstractyes

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