Rodríguez Alejandro, Tembl José, Mesa-Gresa Patricia, Muñoz Miguel Ángel, Montoya Pedro, Rey Beatriz
Departamento de Ingeniería Gráfica, Universitat Politècnica de València, Camino de Vera s/n, Valencia, Spain.
Departamento de Neurología, Hospital Universitari i Politècnic La Fe, Valencia, Spain.
PLoS One. 2017 Jul 12;12(7):e0180253. doi: 10.1371/journal.pone.0180253. eCollection 2017.
The aim of this study is to characterize in resting-state conditions the cerebral blood flow velocity (CBFV) signals of fibromyalgia patients. The anterior and middle cerebral arteries of both hemispheres from 15 women with fibromyalgia and 15 healthy women were monitored using Transcranial Doppler (TCD) during a 5-minute eyes-closed resting period. Several signal processing methods based on time, information theory, frequency and time-frequency analyses were used in order to extract different features to characterize the CBFV signals in the different vessels. Main results indicated that, in comparison with control subjects, fibromyalgia patients showed a higher complexity of the envelope CBFV and a different distribution of the power spectral density. In addition, it has been observed that complexity and spectral features show correlations with clinical pain parameters and emotional factors. The characterization features were used in a lineal model to discriminate between fibromyalgia patients and healthy controls, providing a high accuracy. These findings indicate that CBFV signals, specifically their complexity and spectral characteristics, contain information that may be relevant for the assessment of fibromyalgia patients in resting-state conditions.
本研究的目的是在静息状态下对纤维肌痛患者的脑血流速度(CBFV)信号进行特征描述。在5分钟闭眼静息期,使用经颅多普勒(TCD)监测15名纤维肌痛女性患者和15名健康女性双侧半球的大脑前动脉和大脑中动脉。为了提取不同特征以描述不同血管中的CBFV信号,采用了基于时间、信息论、频率和时频分析的几种信号处理方法。主要结果表明,与对照组相比,纤维肌痛患者的CBFV包络复杂度更高,功率谱密度分布不同。此外,还观察到复杂度和频谱特征与临床疼痛参数和情绪因素相关。这些特征用于线性模型以区分纤维肌痛患者和健康对照,准确率较高。这些发现表明,CBFV信号,特别是其复杂度和频谱特征,包含的信息可能与静息状态下纤维肌痛患者的评估相关。