Khandoker A H, Luthra V, Abouallaban Y, Saha S, Ahmed K I, Mostafa R, Chowdhury N, Jelinek H F
Annu Int Conf IEEE Eng Med Biol Soc. 2016 Aug;2016:1842-1845. doi: 10.1109/EMBC.2016.7591078.
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.
重度抑郁症（MDD）是一种严重的精神障碍，若不治疗，不仅会影响身体健康，还具有很高的自杀风险。虽然导致自杀意念（SI）形成的神经生理现象仍不明确，但已有报道称MDD与心血管疾病之间存在明确联系。本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组和对照组中的SI。在阿联酋的一家精神病诊所招募了16名有SI病史的未服药MDD患者（MDDSI+）、16名无SI的患者（MDDSI-）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严重程度和SI。脉搏波振幅（PWA）计算为每个心动周期内动脉脉搏的峰值（收缩期）与谷值（舒张期）之间的差值。然后，从收缩期、舒张期和PWA时间序列中提取二维音调熵（TE）特征。从舒张期提取的TE特征是预测MDDSI+的最佳指标。使用收缩期、舒张期和PWA的TE特征的分类与回归树（CART）模型的总体分类准确率分别为88.52%、90.2%和88.52%。当所有TE特征结合起来时，在识别MDDSI+/MDDSI-/对照组时准确率提高到93.44%。
