Matsui Takemi, Shinba Toshikazu, Sun Guanghao
a Graduate School of System Design , Tokyo Metropolitan University , Tokyo , Japan.
b Department of Psychiatry , Shizuoka Saiseikai General Hospital , Shizuoka , Japan.
J Med Eng Technol. 2018 Feb;42(2):121-127. doi: 10.1080/03091902.2018.1435744. Epub 2018 Mar 23.
12.6% of major depressive disorder (MDD) patients have suicide intent, while it has been reported that 43% of patients did not consult their doctors for MDD, automated MDD screening is eagerly anticipated. Recently, in order to achieve automated screening of MDD, biomarkers such as multiplex DNA methylation profiles or physiological method using near infra-red spectroscopy (NIRS) have been studied, however, they require inspection using 96-well DNA ELIZA kit after blood sampling or significant cost. Using a single-lead electrocardiography (ECG), we developed a high-precision MDD screening system using transient autonomic responses induced by dual mental tasks. We developed a novel high precision MDD screening system which is composed of a single-lead ECG monitor, analogue to digital (AD) converter and a personal computer with measurement and analysis program written by LabView programming language. The system discriminates MDD patients from normal subjects using heat rate variability (HRV)-derived transient autonomic responses induced by dual mental tasks, i.e. verbal fluency task and random number generation task, via linear discriminant analysis (LDA) adopting HRV-related predictor variables (hear rate (HR), high frequency (HF), low frequency (LF)/HF). The proposed system was tested for 12 MDD patients (32 ± 15 years) under antidepressant treatment from Shizuoka Saiseikai General Hospital outpatient unit and 30 normal volunteers (37 ± 17 years) from Tokyo Metropolitan University. The proposed system achieved 100% sensitivity and 100% specificity in classifying 42 examinees into 12 MDD patients and 30 normal subjects. The proposed system appears promising for future HRV-based high-precision and low-cost screening of MDDs using only single-lead ECG.
12.6%的重度抑郁症(MDD)患者有自杀意图,而据报道43%的MDD患者未就其病情咨询过医生,因此人们急切期待实现MDD的自动化筛查。最近,为了实现MDD的自动化筛查,已经对诸如多重DNA甲基化谱或使用近红外光谱(NIRS)的生理方法等生物标志物进行了研究,然而,这些方法需要在采血后使用96孔DNA酶联免疫吸附测定(ELISA)试剂盒进行检测,或者成本高昂。我们利用单导联心电图(ECG),开发了一种基于双重心理任务诱发的瞬时自主反应的高精度MDD筛查系统。我们开发了一种新型高精度MDD筛查系统,该系统由单导联ECG监测仪、模数(AD)转换器以及一台装有由LabView编程语言编写的测量和分析程序的个人计算机组成。该系统通过采用与心率变异性(HRV)相关的预测变量(心率(HR)、高频(HF)、低频(LF)/HF)的线性判别分析(LDA),利用双重心理任务(即言语流畅性任务和随机数生成任务)诱发的HRV衍生瞬时自主反应,将MDD患者与正常受试者区分开来。该系统在静冈西新井综合医院门诊部接受抗抑郁治疗的12名MDD患者(32±15岁)和来自东京都市大学的30名正常志愿者(37±17岁)身上进行了测试。在将42名受试者分为12名MDD患者和30名正常受试者的分类中,该系统实现了100%的灵敏度和100%的特异性。所提出的系统对于未来仅使用单导联ECG进行基于HRV的MDD高精度、低成本筛查似乎很有前景。