Robotic Simulators for Tissue Examination Training With Multimodal Sensory Feedback.


Journal

IEEE reviews in biomedical engineering
ISSN: 1941-1189
Titre abrégé: IEEE Rev Biomed Eng
Pays: United States
ID NLM: 101493803

Informations de publication

Date de publication:
2023
Historique:
medline: 7 4 2023
pubmed: 20 4 2022
entrez: 19 4 2022
Statut: ppublish

Résumé

Tissue examination by hand remains an essential technique in clinical practice. The effective application depends on skills in sensorimotor coordination, mainly involving haptic, visual, and auditory feedback. The skills clinicians have to learn can be as subtle as regulating finger pressure with breathing, choosing palpation action, monitoring involuntary facial and vocal expressions in response to palpation, and using pain expressions both as a source of information and as a constraint on physical examination. Patient simulators can provide a safe learning platform to novice physicians before trying real patients. This paper reviews state-of-the-art medical simulators for the training for the first time with a consideration of providing multimodal feedback to learn as many manual examination techniques as possible. The study summarizes current advances in tissue examination training devices simulating different medical conditions and providing different types of feedback modalities. Opportunities with the development of pain expression, tissue modeling, actuation, and sensing are also analyzed to support the future design of effective tissue examination simulators.

Identifiants

pubmed: 35439140
doi: 10.1109/RBME.2022.3168422
doi:

Types de publication

Review Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

514-529

Auteurs

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Classifications MeSH