Robotic Simulators for Tissue Examination Training With Multimodal Sensory Feedback

Liang He, Perla Maiolino, Florence Leong, Thilina Dulantha Lalitharatne, Simon de Lusignan, Mazdak Ghajari, Fumiya Iida, Thrishantha Nanayakkara

IEEE Reviews in Biomedical Engineering, 2022

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.

Cite as (BibTeX)

@article{he-2022-robotic-simulators-for-tissue,
  title={Robotic Simulators for Tissue Examination Training With Multimodal Sensory Feedback},
  author={Liang He and Perla Maiolino and Florence Leong and Thilina Dulantha Lalitharatne and Simon de Lusignan and Mazdak Ghajari and Fumiya Iida and Thrishantha Nanayakkara},
  journal={IEEE Reviews in Biomedical Engineering},
  year={2022},
  doi={10.1109/rbme.2022.3168422}
}