Reduced-Order Extended Kalman Filter for Deformable Tissue Simulation

Song, Jialu; Xie, Hujin; Zhong, Yongmin; Li, Jiankun; Gu, Chengfan; Choi, Kup‐Sze

doi:10.1016/j.jmps.2021.104696

Cited by 16 publications

(4 citation statements)

References 25 publications

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“…To analyze the nonlinear soft tissue behavior, an extended (nonlinear) Kalman filter is combined with the traditional nonlinear FEM [84]. The computational head can be further reduced by lowering the number of states of model without compromising its physics [85]. quently applied in soft tissue mechanics [85], [89].…”

Section: ) Mesh-based Modeling Methodsmentioning

confidence: 99%

“…The computational head can be further reduced by lowering the number of states of model without compromising its physics [85]. quently applied in soft tissue mechanics [85], [89]. Gao and Shang [89] achieved real-time simulation in vascular interventional surgery using POD to decompose position and then singular value decomposition (SVD) to minimize the cost function.…”

Section: ) Mesh-based Modeling Methodsmentioning

confidence: 99%

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Toward a Digital Twin for Arthroscopic Knee Surgery: A Systematic Review

et al. 2022

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The use of digital twins to represent a product or process digitally is trending in many engineering disciplines. This term has also been recently introduced in the medical field. In arthroscopic surgery education, the paradigm shift from apprenticeship to simulation training has driven the need for better simulators, and the current focus is on improving simulators with respect to computational efficiency and system accuracy. However, expanding surgical simulations towards digital twins has not yet been explored. This paper introduces the digital twin concept for arthroscopic surgery, and explores its potential in light of the existing scientific literature. Thus, a systematic review was conducted to summarize and analyze the literature with respect to fast and robust design of an arthroscopic digital twin using patientspecific information, and methods for interactive surgical soft tissue simulation. The review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol with three reliable scientific search engines: IEEE Explore, ScienceDirect and PubMed. Eighty papers were included in the review, and the extracted data included modeling methods, tissue types, constitutive behavior, computational efficiency or accuracy, hardware configuration, haptic device description, software tools, and system architectures. Considering the review, a novel macro-level conceptual arthroscopic digital twin system is presented, and the applicability of the review findings for the identified subsystems are discussed. The proposed system integrates patient-specific images, diagnostic data, intraoperative sensor data, and surgical practice as inputs, and conceptually enables surgical skills training, preoperative planning, and a database of virtual surgeries.

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Section: ) Mesh-based Modeling Methodsmentioning

confidence: 99%

Section: ) Mesh-based Modeling Methodsmentioning

confidence: 99%

Toward a Digital Twin for Arthroscopic Knee Surgery: A Systematic Review

et al. 2022

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“…In future work, the interpolation and Kalman filter-based force computation strategies should be explored together with a more sophisticated implementation of FEM, such as the corotational formulation [39], total Lagrangian explicit dynamics (TLED) [40] or reduced-order extended Kalman filter FEM [41]- [43]. Novel position tracking systems, such as that recently demonstrated for knee arthroscopy by Ma et al [44], combined with a 6 DOF force-torque sensor, could provide the basis for in-vivo intraoperative data collection for other arthroscopic procedures.…”

Section: User Groupmentioning

confidence: 99%

Intraoperative Data-Based Haptic Feedback for Arthroscopic Partial Meniscectomy Punch Simulation

et al. 2022

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The use of intraoperative tool-tissue interaction data for arthroscopic digital twins has the potential to enhance haptic feedback in surgical simulations. This study demonstrates the implementation of an interpolation-based method, and a Kalman filter-based method using intraoperative interaction data to provide nonlinear haptic feedback in a partial meniscectomy punch simulation. These methods were demonstrated using a novel inexpensive haptic system for simulating an arthroscopic partial meniscectomy punch. Tool-tissue interaction data were collected from a cadaveric meniscus and used for the simulations. The software, computer-aided design models, and collected data are provided open-source on GitHub. The face validity of the methods was evaluated in user studies, including six experienced orthopedic surgeons, and five non-professionals. The findings showed that experienced surgeons could distinguish between a nonlinear interpolation-based force signal, and a linear-elastic ideally-plastic finite element-based reference signal in a partial meniscectomy punch simulation. Surgeons preferred the interpolation method as a haptic rendering strategy in this study. The Kalman filter method was not as effective as interpolation in recreating nonlinear haptic feedback for the tested parameters, but demonstrated coupling of haptic force signals from intraoperative data and an idealized finite element method in a partial meniscectomy punch simulation.

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“…e computation is very time consuming when the model dimension is very large. e modified finite element method can improve the simulation efficiency [25,26], and it may be able to provide effective guidance for relevant calculation.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Loess Collapsibility Based on Random Field Theory in Xi’an, China

Zhang

Han

et al. 2022

Mathematical Problems in Engineering

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The engineering properties of collapsible loess have significant uncertainty. Accurate prediction of collapsible deformation is crucial for the safety of engineering construction in loess areas. Taking the typical collapsible loess stratum as the research object in Xi’an, based on the random field theory, combined with the Monte Carlo strategy and modulus reduction method, the stochastic finite element analysis of loess self-weight collapsibility is carried out to study the influence of the spatial variability of compression modulus on the self-weight collapsibility of loess. The results show that the loess tends to be stratified and average along the depth direction with the increase of transverse correlation distance. The random field result of self-weight collapsibility considering the spatial variability of compression modulus is significantly greater than the deterministic result of layered average and the calculated value of loess code. Considering the low compression modulus dominance effect of compression modulus with positive skewed distribution of random field, the equivalent characteristic value of the compression modulus calculated by the layered average modeling for the collapsibility evaluation of typical loess strata in Xi'an area is proposed.

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Reduced-Order Extended Kalman Filter for Deformable Tissue Simulation

Cited by 16 publications

References 25 publications

Toward a Digital Twin for Arthroscopic Knee Surgery: A Systematic Review

Toward a Digital Twin for Arthroscopic Knee Surgery: A Systematic Review

Intraoperative Data-Based Haptic Feedback for Arthroscopic Partial Meniscectomy Punch Simulation

Evaluation of Loess Collapsibility Based on Random Field Theory in Xi’an, China

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