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骨锯触觉反馈的预测力模型。

Predictive force model for haptic feedback in bone sawing.

机构信息

Laboratory for Biomechanical Studies, Department of Mechanical Engineering, Tufts University, 200 College Avenue, Medford, MA 02155, USA.

出版信息

Med Eng Phys. 2013 Nov;35(11):1638-44. doi: 10.1016/j.medengphy.2013.05.012. Epub 2013 Jun 24.


DOI:10.1016/j.medengphy.2013.05.012
PMID:23806417
Abstract

Bone sawing simulators with force feedback represent a cost effective means of training orthopedic surgeons in various surgical procedures, such as total knee arthroplasty. To develop a machine with accurate haptic feedback, giving a sensation of both cutting force and rate of material removal, algorithms are required to forecast bone sawing forces based on user input. Presently, studies on forces generated while machining bone are not representative of the high cutting speeds and low depths of cut common to the bone sawing process. The objective of this research was to quantify sawing forces in cortical bone as a function of blade speed and depth of cut. A fixture was developed to simulate linear bone sawing over a range of speeds comparable to surgical reciprocating and oscillating (sagittal) bone saws. A single saw blade tooth was isolated and used to create a slotted cut in bovine cortical bone. Over a range in linear sawing speed from 1700 to 7000 mm/s, a t-test (α=0.05) revealed there was no statistically significant effect of blade speed on either cutting or thrust force. However, an increase in depth of cut from 2 to 10 μm resulted in a 30% increase in thrust force, while cutting force remained constant. The increase in thrust force with depth of cut was relatively linear, R(2)=0.80. Using a two factor, two level design of experiments approach, regression equations were developed to relate sawing forces to changes in blade speed and depth of cut. These equations can be used to predict forces in a haptic feedback model.

摘要

带力反馈的骨锯模拟器是一种经济有效的培训骨科医生进行各种手术的方法,如全膝关节置换术。为了开发一种具有精确触觉反馈的机器,提供切割力和材料去除率的感觉,需要算法根据用户输入预测骨锯力。目前,对加工骨时产生的力的研究不能代表骨锯过程中常见的高速切割和低切削深度。本研究的目的是量化皮质骨的锯切力作为刀片速度和切削深度的函数。开发了一种夹具来模拟线性骨锯切,其速度范围与手术往复式和摆动式(矢状面)骨锯相当。单个锯片齿被隔离并用于在牛皮质骨上制造开槽切割。在 1700 至 7000mm/s 的线性锯切速度范围内,t 检验(α=0.05)显示刀片速度对切削力或推力均无统计学显著影响。然而,切削深度从 2 到 10μm 的增加导致推力增加 30%,而切削力保持不变。随着切削深度的增加,推力的增加相对线性,R(2)=0.80。使用两因素、两水平的实验设计方法,开发了回归方程将锯切力与刀片速度和切削深度的变化联系起来。这些方程可用于预测触觉反馈模型中的力。

相似文献

[1]
Predictive force model for haptic feedback in bone sawing.

Med Eng Phys. 2013-6-24

[2]
Rounded cutting edge model for the prediction of bone sawing forces.

J Biomech Eng. 2012-7

[3]
Development and validation of a surgical training simulator with haptic feedback for learning bone-sawing skill.

J Biomed Inform. 2013-12-28

[4]
Effect of operating parameters on the removal of bone cement by a sawing process.

Proc Inst Mech Eng H. 2014-3

[5]
Effect of applied force and blade speed on histopathology of bone during resection by sagittal saw.

Med Eng Phys. 2014-1-7

[6]
Machining of bone: Analysis of cutting force and surface roughness by turning process.

Proc Inst Mech Eng H. 2015-11

[7]
Preliminarily measurement and analysis of sawing forces in fresh cadaver mandible using reciprocating saw for reality-based haptic feedback.

J Craniofac Surg. 2012-5

[8]
Design and experimental force analysis of a novel elliptical vibration assisted orthopedic oscillating saw.

Med Eng Phys. 2018-4

[9]
Simulation and evaluation of a bone sawing procedure for orthognathic surgery based on an experimental force model.

J Biomech Eng. 2014-3

[10]
A predictive bone drilling force model for haptic rendering with experimental validation using fresh cadaveric bone.

Int J Comput Assist Radiol Surg. 2016-8-22

引用本文的文献

[1]
Intraoperative physician assessment of bone: correlation to bone mineral density.

Osteoporos Int. 2023-6

[2]
Power-Tool Use in Orthopaedic Surgery: Iatrogenic Injury, Its Detection, and Technological Advances: A Systematic Review.

JB JS Open Access. 2021-11-19

[3]
A predictive bone drilling force model for haptic rendering with experimental validation using fresh cadaveric bone.

Int J Comput Assist Radiol Surg. 2016-8-22

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