Characterization of tissue properties in epidural needle insertion on human specimen and synthetic materials

Esterer, Benjamin; Hollensteiner, Marianne; Schrempf, Andreas; Winkler, M.; Gabauer, Stefan; Fürst, David; Merwa, Robert; Panzer, Stephanie; Püschel, Klaus; Augat, Peter

doi:10.1016/j.jmbbm.2020.103946

Cited by 8 publications

(19 citation statements)

References 11 publications

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“…Previous studies showed the characteristics of the insertion force throughout the whole LP process (Ambastha et al, 2018; Esterer et al, 2020; Tran et al, 2009). From these studies, the common trend of the insertion force during a LP surgery can be evaluated.…”

Section: Control Algorithm and Intelligent Penetration Recognitionmentioning

confidence: 99%

“…This worsens test results and treatments and causes pain to the children and their families. The one-time success rate is lower than 60% (Esterer et al, 2020). Repeated punctures then result in high infection and complication rates.…”

Section: Introductionmentioning

confidence: 96%

“…Relatively few researches are cast on LPs and mostly without assistance from any imaging modality (Sikka et al, 2015). The absence of visual guidance requires the surgeon to deduce the needle tip position with haptic sensation (Esterer et al, 2020). It is not until the past two decades that haptic force feedback is studied, mostly in the form of LP simulators (Dong-Soo et al, 2001).…”

Section: Introductionmentioning

confidence: 99%

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Penetration detection with intention recognition for cooperatively controlled robotic needle insertion

Wang

2022

Transactions of the Institute of Measurement and Control

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In lumbar puncture surgeries, force and position information throughout the insertion procedure is vital for needle tip localization, because it reflects different tissue properties. Especially in pediatric cases, the changes are always insignificant for surgeons to sense the crucial feeling of loss of resistance. In this study, a robot system is developed to tackle the major clinical difficulties. Four different control algorithms with intention recognition ability are applied on a novel lumbar puncture robot system for better human–robot cooperation. Specific penetration detection based on force and position derivatives captures the feeling of loss of resistance, which is deemed crucial for needle tip location. Kinematic and actuation modeling provides a clear description of the hardware setup. The control algorithm experiment compares the human–robot cooperation performance of proposed algorithms. The experiment also dictates the clear role of designed penetration detection criteria in capturing the penetration, improving the success rate, and ensuring operational safety.

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Section: Control Algorithm and Intelligent Penetration Recognitionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

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Penetration detection with intention recognition for cooperatively controlled robotic needle insertion

Wang

2022

Transactions of the Institute of Measurement and Control

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“…Figure 6 describes these phases and the total axial force pattern due to the penetration of the needle. These models have still been used in recent works such as [7,11,13,13,14,[24][25][26][27][28][29][30][31][32][33][34]. Recently, works focused on the ability to render multiple layers of tissues, using piece-wise exponential models [13] or nested boxes [25] rendering each one its stiffness and cutting forces according to [35].…”

Section: Deformation Based Modelsmentioning

confidence: 99%

“…In deformation based models, a method to obtain parameters is fitting functions to experimental data obtained during needle insertions [27,28,32,33] or traction/compression experiments [45]. Usually, these experiments are performed on cadaveric (ex vivo) or animal tissues (in vivo or ex vivo).…”

Section: Constitutive Models Representing Specific Tissues and Parame...mentioning

confidence: 99%

Review on Needle Insertion Haptic Simulation

et al. 2022

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This short review updates an exhaustive one written by Correa et al in 2019 about haptic training simulation on needle insertion in the medical field. b) Recent findings: Latest works refine wellknown models and enhance setups and methods to facilitate generically getting experimental data. c) Summary:We provide a complementary focus on device specifications and recent models to render this specific haptic feedback on Computer-Based Simulators. Assessment approaches and the issues encountered when introducing such simulators into curricula are also discussed. FEM-based approaches still do not permit real-time computation but hybrid approaches as proposed by [1] may become a good compromise. Nonetheless, psychophysical studies should be performed to determine the haptic fidelity of the various approaches found in the literature, and embed them efficiently in medical curricula. This would permit to delay the necessary final hands-on training on patients that raises ethical issues.

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Digital Multiphase Composites via Additive Manufacturing

Smith,

MacCurdy

2024

Advanced Materials

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Mechanical properties of traditional engineering materials are typically coupled to each other, presenting a challenge to practitioners with multi‐dimensional material property requirements. In this work we demonstrate continuous, independent control over multiple mechanical properties in composite materials realized using additive manufacturing. For the first time, we experimentally characterize composites additively manufactured from rigid plastic, soft elastomer, and liquid constituents, demonstrating materials which span four orders of magnitude in modulus and two orders of magnitude in toughness. By forming analytical mappings between relative concentrations of constituents at the microscale and resulting macroscale material properties, we enable inverse material design; we showcase the method by printing artifacts with prescribed toughness and elasticity distributions. We place the properties of these composites in the context of biological tissues, showing they have promise as mechanically plausible tissue mimics.This article is protected by copyright. All rights reserved

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Characterization of tissue properties in epidural needle insertion on human specimen and synthetic materials

Cited by 8 publications

References 11 publications

Penetration detection with intention recognition for cooperatively controlled robotic needle insertion

Penetration detection with intention recognition for cooperatively controlled robotic needle insertion

Review on Needle Insertion Haptic Simulation

Digital Multiphase Composites via Additive Manufacturing

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