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State-of-the-Art Assistive Technology for People with Dementia

2011· book-chapter· en· W2301566833 on OpenAlexaff
Clifton Phua, Patrice Roy, Hamdi Aloulou, Jit Biswas, Andrei Tolstikov, Victor Siang-Fook Foo, Aung-Phyo-Wai Aung, Weimin Huang, Mohamed Ali Feki, Alvin Kok-Weng Chu, Duangui Xu

Bibliographic record

VenueAdvances in computational intelligence and robotics book series · 2011
Typebook-chapter
Languageen
FieldComputer Science
TopicContext-Aware Activity Recognition Systems
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsMental healthDementiaScope (computer science)Work (physics)Independent livingHealth carePlan (archaeology)Computer scienceTelecareHome automationApplied psychologyHuman–computer interactionPsychologyKnowledge managementEngineeringTelemedicineGerontologyMedicinePsychiatryTelecommunications

Abstract

fetched live from OpenAlex

The work is motivated by the expanding demand and limited supply of long-term personal care for People with Dementia (PwD), and assistive technology as an alternative. Telecare allows PwD to live in the comfort of their homes for a longer time. It is challenging to have remote care in smart homes with ambient intelligence, using devices, networks, and activity and plan recognition. Our scope is limited to mostly related work on existing execution environments in smart homes, and activity and plan recognition algorithms which can be applied to PwD living in smart homes. PwD and caregiver needs are addressed in a more holistic healthcare approach, domain challenges include doctor validation and erroneous behaviour, and technical challenges include high maintenance and low accuracy. State-of-the-art devices, networks, activity and plan recognition for physical health are presented; ideas for developing mental training for mental health and social networking for social health are explored. There are two implications of this work: more needs to be done for assistive technology to improve PwD’s mental and social health, and assistive software is not highly accurate and persuasive yet. Our work applies not only to PwD, but also the elderly without dementia and people with intellectual disabilities.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.321
Threshold uncertainty score0.853

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 communication0.0000.001
Open science0.0010.000
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 head0.023
GPT teacher head0.257
Teacher spread0.234 · 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 designTheoretical or conceptual
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

Citations5
Published2011
Admission routes1
Has abstractyes

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