Open AccessData assimilation using particle filter for real‐time identification of organ properties
Author(s) -
Nakano Sojuro,
Miura Satoshi,
Victor Parque,
Torisaka Ayako,
Miyashita Tomoyuki
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2018.9410
Subject(s) - data assimilation , computer science , identification (biology) , assimilation (phonology) , particle filter , euler method , statics , finite element method , robot , euler's formula , filter (signal processing) , algorithm , artificial intelligence , mathematics , computer vision , engineering , structural engineering , physics , meteorology , mathematical analysis , linguistics , philosophy , botany , classical mechanics , biology
The number of operations using surgical robots are continuously increasing. To perform accurate surgeries, it is necessary to know the behaviour of intervened organs, especially their mechanical properties, which must be accurately determined. However, the physical properties of organs vary depending on age, gender, and environment, and thus, each organ exhibits particular mechanical properties. The authors propose a real‐time assimilation system that identifies organ properties. Specifically, a 2D model using the finite element method and data assimilation, which is mostly used in Earth science, allows the identification of the physical parameters of organs. Data assimilation relies on a particle filter for efficiently solving the non‐linear identification of parameters from a statics viewpoint. In addition, the semi‐implicit Euler method discretises the proposed model and improves efficiency. The proposed approach can serve to the future implementation of a real‐time and accurate framework for identifying mechanical properties of organs.