Bone density classification method for robotic drilling system

Koyo Yu; Yuki Saito; Yusuke Kasahara; Hiromasa Kawana; Shin Usuda; Kouhei Ohnishi

doi:10.1541/ieejias.133.328

Bone density classification method for robotic drilling system

Koyo Yu, Yuki Saito, Yusuke Kasahara, Hiromasa Kawana, Shin Usuda, Kouhei Ohnishi

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

It is important to classify the bone density for dental implants. In this paper, a method for estimating the bone density is proposed by modeling the relationship between the cutting force and the bone density. The bone density can be obtained in real time by comparing the force from a reaction force observer with the force from a thrust force formula with pre-estimated bone density parameters. The validity of the proposed method was confirmed through experiments using different types of wood mentioned in Misch's bone density classification. The experimental results indicated that the error of contact detection was +50 μm and the error of bone density detection was 0.16 mm.

Original language	English
Pages (from-to)	328-334
Number of pages	7
Journal	ieej transactions on industry applications
Volume	133
Issue number	3
DOIs	https://doi.org/10.1541/ieejias.133.328
Publication status	Published - 2013

Keywords

Acceleration control
Bone density estimation
Drilling system
Misch's classification
Motion control
Reaction force observer

ASJC Scopus subject areas

Industrial and Manufacturing Engineering
Electrical and Electronic Engineering

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10.1541/ieejias.133.328

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title = "Bone density classification method for robotic drilling system",

abstract = "It is important to classify the bone density for dental implants. In this paper, a method for estimating the bone density is proposed by modeling the relationship between the cutting force and the bone density. The bone density can be obtained in real time by comparing the force from a reaction force observer with the force from a thrust force formula with pre-estimated bone density parameters. The validity of the proposed method was confirmed through experiments using different types of wood mentioned in Misch's bone density classification. The experimental results indicated that the error of contact detection was +50 μm and the error of bone density detection was 0.16 mm.",

keywords = "Acceleration control, Bone density estimation, Drilling system, Misch's classification, Motion control, Reaction force observer",

author = "Koyo Yu and Yuki Saito and Yusuke Kasahara and Hiromasa Kawana and Shin Usuda and Kouhei Ohnishi",

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T1 - Bone density classification method for robotic drilling system

AU - Yu, Koyo

AU - Saito, Yuki

AU - Kasahara, Yusuke

AU - Kawana, Hiromasa

AU - Usuda, Shin

AU - Ohnishi, Kouhei

PY - 2013

Y1 - 2013

N2 - It is important to classify the bone density for dental implants. In this paper, a method for estimating the bone density is proposed by modeling the relationship between the cutting force and the bone density. The bone density can be obtained in real time by comparing the force from a reaction force observer with the force from a thrust force formula with pre-estimated bone density parameters. The validity of the proposed method was confirmed through experiments using different types of wood mentioned in Misch's bone density classification. The experimental results indicated that the error of contact detection was +50 μm and the error of bone density detection was 0.16 mm.

AB - It is important to classify the bone density for dental implants. In this paper, a method for estimating the bone density is proposed by modeling the relationship between the cutting force and the bone density. The bone density can be obtained in real time by comparing the force from a reaction force observer with the force from a thrust force formula with pre-estimated bone density parameters. The validity of the proposed method was confirmed through experiments using different types of wood mentioned in Misch's bone density classification. The experimental results indicated that the error of contact detection was +50 μm and the error of bone density detection was 0.16 mm.

KW - Acceleration control

KW - Bone density estimation

KW - Drilling system

KW - Misch's classification

KW - Motion control

KW - Reaction force observer

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Bone density classification method for robotic drilling system

Abstract

Keywords

ASJC Scopus subject areas

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