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Record W2008571347 · doi:10.4262/denkiseiko.74.155

Development of an Electric Powered Wheelchair in which the Angle of Recline of the User's Body Controls the Direction

2003· article· en· W2008571347 on OpenAlexaboutno aff
Toshio Endo, Akira Iida, Shinichi Tanaka, Tutomu Kunitachi

Bibliographic record

VenueDENKI-SEIKO · 2003
Typearticle
Languageen
FieldComputer Science
TopicGaze Tracking and Assistive Technology
Canadian institutionsnot available
Fundersnot available
KeywordsWheelchairQuarter (Canadian coin)Tilt (camera)PopulationLife styleWork (physics)Control (management)Human–computer interactionComputer scienceSimulationEngineeringPsychologyPhysical medicine and rehabilitationApplied psychologySociologyGeographyMechanical engineeringMedicineArtificial intelligenceWorld Wide Web

Abstract

fetched live from OpenAlex

Japan is experiencing a situation where its population demographic is aging more rapidly than any other country in the world. It is estimated that in 15 years a quarter of the total population will be 65 years old or above. With the advent of this aging society, it is important that senior citizens can have a self-sustainable life-style. In an attempt to assist senior citizens to experience self-reliance, the authors have studied the development of an electric-powered wheelchair in which the user can control the direction of travel by changing the angle of their body. The wheelchair is made full use of the latest sensing and information technologies. We have completed a prototype electric wheelchair that can detect the tilt angle of the user's body by incorporating an acceleration sensor and which controls the directions of travel by employing a personal computer. Furthermore, after successful trials that have been carried out by senior citizens, we would like to expand our work to practical applications.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.012
GPT teacher head0.240
Teacher spread0.229 · 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 designBench or experimental
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

Citations0
Published2003
Admission routes1
Has abstractyes

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Same venueDENKI-SEIKOSame topicGaze Tracking and Assistive TechnologyFrench-language works237,207