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https://doi.org/10.1109/fuzz-i...
Article . 2012 . Peer-reviewed
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DBLP
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An automated calibration by using fuzzy control for a measurement system of Lachman test

Authors: Shogo Kawaguchi; Kouki Nagamune; Daisuke Araki; Tomoyuki Matsumoto; Seiji Kubo; Takehiko Matsushita; Ryosuke Kuroda; +1 Authors

An automated calibration by using fuzzy control for a measurement system of Lachman test

Abstract

Lachman test is one of a manual tests for examining the anterior cruciate ligament (ACL). A medical personnel discriminates degree of the ACL injury by the feeling of stress on the finger. This method is subjective and dependent on the skill of medical personnel. Hence, a measurement device for Lachman test has been developed. This measurement system consists of finger braces and force sensors on each fingers. However due to low accuracy of the system, improvement of current device has been proposed by calibrating the finger braces for different finger thickness. The calibration made for the device was successfully detect the true force applied to the finger braces. Nevertheless, the system was only able to measure low load with high accuracy. Future works are already in progress to improve the resolution of A/D converter and to measure the force distribution during Lachman test with high accuracy using the force sensor.

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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