机译:使用多方面和支持向量机的正常和膝关节障碍触发信号的分类
School of Electronics Engineering Biomedical Technology Division VIT University Vellore India;
Department of Computer Science Engineering Easwari Engineering College Chennai India;
School of Electronics Engineering Biomedical Technology Division VIT University Vellore India;
School of Electronics Engineering Biomedical Technology Division VIT University Vellore India;
Knee joint disorder; Vibroarthrographic signals; Multifractal method; Feature extraction; Support vector machine;
机译:使用多方面和支持向量机的正常和膝关节障碍触发信号的分类
机译:使用蛛旋旋信号分析和多标准分类病理膝关节分类
机译:自适应过滤,建模和分类膝关节振动性关节炎信号,用于无创诊断关节软骨病理。
机译:基于k近邻算法的膝关节脉搏描记信号分类。
机译:支持向量机在拓扑滤波的合成孔径声纳信号上的分类性能。
机译:vibroarthrographic信号光谱特征在5级膝关节分类中
机译:利用时域和时频域特征和最小二乘支持向量机对关节关节影像学信号进行分类