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Identifying depressed patients with and without suicidal ideation by finger photo-plethysmography

机译:通过手指体积描记法识别有或没有自杀意念的抑郁症患者

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Major Depressive Disorder (MDD) is a serious mental disorder that if untreated not only affects physical health but also has a high risk of suicide. While the neurophysiological phenomena that contribute to the formation of Suicidal Ideation (SI) are still ill-defined, clear links between MDD and cardiovascular disease have been reported. The aim of this study is to extract suitable features from arterial pulse signals with a view to predicting SI within MDD and control groups. Sixteen unmedicated MDD patients with a history of SI (MDDSI+), sixteen without SI (MDDSI-) and twenty-nine healthy subjects (CONT) were recruited at a psychiatric clinic in the UAE. Depression severity and SI were assessed using the Hamilton Depression Rating Scale and Beck Depression Inventory. Pulse Wave Amplitude (PWA) was calculated as the difference between the peak (Systole) and the valley (Diastole) of the arterial pulse within each cardiac cycle. Then, 2D Tone-Entropy (TE) features were extracted from the Systole, Diastole and PWA time series. The TE features extracted from Diastole were the best markers for predicting MDDSI+. The overall classification accuracies of Classification and Regression Tree (CART) model by using TE features of Systole, Diastole and PWA were 88.52%, 90.2% and 88.52% respectively. When all TE features were combined, accuracy increased up to 93.44% in identifying MDDSI+/MDDSI-/Control groups.
机译:严重抑郁症(MDD)是一种严重的精神疾病,如果不加以治疗,不仅会影响身体健康,而且还具有很高的自杀风险。尽管导致自杀意念(SI)形成的神经生理现象仍然不明确,但已有报道称MDD与心血管疾病之间存在明确的联系。这项研究的目的是从动脉脉搏信号中提取合适的特征,以预测MDD和对照组中的SI。在阿联酋的一家精神病学诊所招募了16名具有SI病史(MDDSI +),没有SI(MDDSI-)的未经药物治疗的MDD患者和29名健康受试者(CONT)。使用汉密尔顿抑郁量表和贝克抑郁量表评估抑郁的严重程度和SI。计算脉搏波幅度(PWA),作为每个心动周期内动脉脉搏的峰值(收缩)和谷值(舒张)之间的差。然后,从收缩压,舒张压和PWA时间序列中提取2D音熵(TE)特征。从Diastole提取的TE特征是预测MDDSI +的最佳标记。利用Systole,Diastole和PWA的TE特征,分类和回归树(CART)模型的总体分类准确性分别为88.52%,90.2%和88.52%。合并所有TE功能后,在识别MDDSI + / MDDSI- /对照组时,准确性提高了93.44%。

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