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Robotic assistants in personal care: A scoping review

2017· review· en· W2736847593 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMedical Engineering & Physics · 2017
Typereview
Languageen
FieldMedicine
TopicHealthcare Technology and Patient Monitoring
Canadian institutionsMcMaster UniversityHamilton Health SciencesSt. Joseph’s Healthcare HamiltonUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRoboticsField (mathematics)Personal careArtificial intelligenceActivities of daily livingComputer scienceRobotHuman–computer interactionMedicineEngineering managementEngineeringPhysical therapy

Abstract

fetched live from OpenAlex

The aim of this study is to present an overview of the technological advances in the field of robotics developed for assistance with activities of daily living (ADL), and to present areas where further research is required. Four databases were searched for articles presenting either a novel design of one of these personal care robotic system or trial results relating to these systems. Articles presenting nine different robotic personal care systems were examined, six of which had been developed after 2005. These six also all have publications relating to their trials. In the majority of trials, patient independence was improved with operation of the robotic device for a specific subset of ADL. A map of the current state of the field of personal care robotics is presented in this study. Areas requiring further research include improving feedback and awareness, as well as refining control methods and pre-programmed behaviors. Developing an affordable, easy to use system would help fill the current gap in the commercial market.

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.653
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.155
GPT teacher head0.455
Teacher spread0.301 · 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