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首页> 美国卫生研究院文献>Computational and Mathematical Methods in Medicine >Comparison of SVM and ANFIS for Snore Related Sounds Classification by Using the Largest Lyapunov Exponent and Entropy
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Comparison of SVM and ANFIS for Snore Related Sounds Classification by Using the Largest Lyapunov Exponent and Entropy

机译：SVM和ANFIS在使用最大Lyapunov指数进行打Sn相关声音分类中的比较和熵

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摘要

Snoring, which may be decisive for many diseases, is an important indicator especially for sleep disorders. In recent years, many studies have been performed on the snore related sounds (SRSs) due to producing useful results for detection of sleep apnea/hypopnea syndrome (SAHS). The first important step of these studies is the detection of snore from SRSs by using different time and frequency domain features. The SRSs have a complex nature that is originated from several physiological and physical conditions. The nonlinear characteristics of SRSs can be examined with chaos theory methods which are widely used to evaluate the biomedical signals and systems, recently. The aim of this study is to classify the SRSs as snore/breathing/silence by using the largest Lyapunov exponent (LLE) and entropy with multiclass support vector machines (SVMs) and adaptive network fuzzy inference system (ANFIS). Two different experiments were performed for different training and test data sets. Experimental results show that the multiclass SVMs can produce the better classification results than ANFIS with used nonlinear quantities. Additionally, these nonlinear features are carrying meaningful information for classifying SRSs and are able to be used for diagnosis of sleep disorders such as SAHS.
机译：打nor对于许多疾病可能是决定性的，尤其是对于睡眠障碍而言是重要的指标。近年来，由于产生了用于检测睡眠呼吸暂停/呼吸不足综合征（SAHS）的有用结果，因此对打on相关声音（SRS）进行了许多研究。这些研究的第一个重要步骤是通过使用不同的时域和频域特征来检测来自SRS的打ore。 SRS具有复杂的性质，其起源于几种生理和身体状况。最近，可以用混沌理论方法研究SRS的非线性特性，该方法广泛用于评估生物医学信号和系统。这项研究的目的是通过使用最大的Lyapunov指数（LLE）和熵以及多类支持向量机（SVM）和自适应网络模糊推理系统（ANFIS）将SRS分类为打sn /呼吸/沉默。针对不同的训练和测试数据集执行了两个不同的实验。实验结果表明，与使用了非线性量的ANFIS相比，多类SVM可以产生更好的分类结果。此外，这些非线性特征携带着有意义的信息，可以对SRS进行分类，并且可以用于诊断诸如SAHS的睡眠障碍。

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