A SVM-based approach for detecting tendon Injury

被引：0

作者：

Borzooei, Sahar ^{[1
]}

Tournier, Pierre-Henri ^{[2
]}

Dolean, Victorita ^{[1
]}

Migliaccio, Claire ^{[3
]}

机构：

[1] Univ Cote dAzur, CNRS, Lab Jean Alexandre Dieudonne LJAD, Nice, France

[2] Univ Paris Cite, Sorbonne Univ, CNRS, Lab Jacques Louis Lions LJLL,Inria, Paris, France

[3] Univ Cote dAzur, Lab Elect Antennes & Telecommun LEAT, Nice, France

来源：

2024 IEEE INTERNATIONAL SYMPOSIUM ON ANTENNAS AND PROPAGATION AND INC/USNCURSI RADIO SCIENCE MEETING, AP-S/INC-USNC-URSI 2024 | 2024年

关键词：

D O I：

10.1109/AP-S/INC-USNC-URSI52054.2024.10685863

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, a solution for the fast detection of shoulder's tendon injury based on numerical modeling and machine learning (ML) algorithm is proposed. The synthetic data for the ML algorithm are the set of scattering parameters which are produced by solving Maxwell's equations for each transmitting antenna of the microwave imaging (MWI) system. The corresponding data of various healthy and injured models are categorized into two classes. Using support vector machine (SVM) for classification, an accuracy of 100% is achieved.

引用

页码：1511 / 1512

页数：2

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