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Record W2009767985 · doi:10.4018/jaci.2009062204

Intelligent Recognition of Activities of Daily Living for Assisting Memory and/or Cognitively Impaired Elders in Smart Homes

2009· article· en· W2009767985 on OpenAlexafffund
Mehdi Najjar, François Courtemanche, Habib Hamam, Alexandre Dion, Jérémy Bauchet

Bibliographic record

VenueInternational Journal of Ambient Computing and Intelligence · 2009
Typearticle
Languageen
FieldComputer Science
TopicContext-Aware Activity Recognition Systems
Canadian institutionsUniversité de MonctonUniversité de SherbrookeUniversité de Montréal
FundersUniversité de Sherbrooke
KeywordsActivities of daily livingComputer scienceArchitectureActivity recognitionModular designHome automationAssisted livingHuman–computer interactionEmbedded systemArtificial intelligencePsychologyGerontologyOperating systemMedicine

Abstract

fetched live from OpenAlex

The article describes a recognition approach of undertaken activities of daily living (ADLs) performed by memory and/or cognitively impaired elders in smart homes. The proposed technique is materialized via a recognition module inserted in a modular generic architecture which aims to offer a framework to conceive intelligent ADLs assistance systems.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.985
Threshold uncertainty score0.576

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.050
GPT teacher head0.311
Teacher spread0.261 · 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 designOther design
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

Citations18
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Ambient Computing and IntelligenceSame topicContext-Aware Activity Recognition SystemsFrench-language works237,207