Journal article
Robotic simulators for tissue examination training with multimodal sensory feedback
- Abstract:
- 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.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 5.2MB, Terms of use)
-
- Publisher copy:
- 10.1109/RBME.2022.3168422
Authors
- Publisher:
- IEEE
- Journal:
- IEEE Reviews in Biomedical Engineering More from this journal
- Volume:
- 16
- Pages:
- 514-529
- Publication date:
- 2022-04-19
- Acceptance date:
- 2022-03-30
- DOI:
- EISSN:
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1941-1189
- ISSN:
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1937-3333
- Language:
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English
- Keywords:
- Pubs id:
-
1250284
- Local pid:
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pubs:1250284
- Deposit date:
-
2022-04-12
Terms of use
- Copyright holder:
- IEEE
- Copyright date:
- 2022
- Rights statement:
- © 2022 IEEE
- Notes:
- This is the accepted manuscript version of the article. The final version is available online from IEEE at: https://doi.org/10.1109/RBME.2022.3168422
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