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Enregistrement W971864676

Design of a Multiple-User Intelligent Feeding Robot for Elderly and Disabled

2007· article· en· W971864676 sur OpenAlexaff
Homeyra Pourmohammadali

Notice bibliographique

RevueUWSpace (University of Waterloo) · 2007
Typearticle
Langueen
DomaineMedicine
ThématiqueChild Nutrition and Feeding Issues
Établissements canadiensUniversity of Waterloo
Organismes subventionnairesnon disponible
Mots-clésMeal preparationService (business)Activities of daily livingElderly peoplePopulationRobotPersonal careIndependence (probability theory)GerontologyNursingMedicineComputer sciencePsychologyBusinessMarketingPhysical therapyArtificial intelligenceEnvironmental healthFamily medicine
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The number of elderly people around the world is growing rapidly. This has led to an increase in the number of people who are seeking assistance and adequate service either at home or in long-term- care institutions to successfully accomplish their daily activities. Responding to these needs has been a burden to the health care system in terms of labour and associated costs and has motivated research in developing alternative services using new technologies. 
\nVarious intelligent, and non-intelligent, machines and robots have been developed to meet the needs of elderly and people with upper limb disabilities or dysfunctions in gaining independence in eating, which is one of the most frequent and time-consuming everyday tasks. However, in almost all cases, the proposed systems are designed only for the personal use of one individual and little effort to design a multiple-user feeding robot has been previously made. The feeding requirements of elderly in environments such as senior homes, where many elderly residents dine together at least three times per day, have not been extensively researched before. 
\nThe aim of this research was to develop a machine to feed multiple elderly people based on their characteristics and feeding needs, as determined through observations at a nursing home. Observations of the elderly during meal times have revealed that almost 40% of the population was totally dependent on nurses or caregivers to be fed. Most of those remaining, suffered from hand tremors, joint pain or lack of hand muscle strength, which made utensil manipulation and coordination very difficult and the eating process both messy and lengthy. In addition, more than 43% of the elderly were very slow in eating because of chewing and swallowing problems and most of the rest were slow in scooping and directing utensils toward their mouths. Consequently, one nurse could only respond to a maximum of two diners simultaneously. In order to manage the needs of all elderly diners, they required the assistance of additional staff members. The limited time allocated for each meal and the daily progression of the seniors’ disabilities also made mealtime very challenging. 
\nBased on the caregivers’ opinion, many of the elderly in such environments can benefit from a machine capable of feeding multiple users simultaneously. Since eating is a slow procedure, the idle state of the robot during one user’s chewing and swallowing time can be allotted for feeding another person who is sitting at the same table. 
\nThe observations and studies have resulted in the design of a food tray, and selection of an appropriate robot and applicable user interface. The proposed system uses a 6-DOF serial articulated robot in the center of a four-seat table along with a specifically designed food tray to feed one to four people. It employs a vision interface for food detection and recognition. Building the dynamic equations of the robotic system and simulation of the system were used to verify its dynamic behaviour before any prototyping and real-time testing.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,256
Score d'incertitude au seuil0,363

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,031
Tête enseignante GPT0,244
Écart entre enseignants0,213 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations5
Publié2007
Routes d'admission1
Résumé présentoui

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