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The diagnosis of psychiatric disorders, such as major depressive disorder (MDD), depends on clinical interviews and assessment of symptoms. However, due to the fact that mental states cannot be objectively assessed, diagnosis procedures are often influenced by clinical experience of psychiatrist. Hence, the aim of this study is to develop a simple, objective, highly accurate self-check system for screening of psychiatric disorders based on heart rate variability (HRV) measured from single- lead electrocardiography (ECG) or photoplethysmogram (PPG) for home healthcare monitoring. HRV is widely used as objective biomarker for assessment of autonomic nerve system. The low frequency (LF) of HRV originates from the sympathetic and parasympathetic nerves. The high frequency (HF) originates from the parasympathetic nerves. In our previous clinical trial, we confirmed that HRV of MDD patients is less reactive than healthy subjects during a mental task (generate random numbers) condition. However, mental task alone is difficult to assess HRV accurately owing to influence of measurement condition and individual differences. In this study, we implemented a single-lead ECG system based on reactivity of HRV, and combined mental task and paced deep breathing thereby improving the screening accuracy. Moreover, support vector machine (SVM) model was applied for classification of HRV indices. We tested the system on 16 healthy subjects and 7 psychiatric patients with depression or somatoform disorder. A significant difference was found between the healthy group and the patient group for the response of the HRV indices on dual mental tasks. The SVM non-linear classification model achieved a sensitivity of 71.4% and specificity of 93.8%.

Since objective biomarkers for major depressive disorder (MDD) are not readily available, clinical psychiatrists diagnose patients with MDD subjectively based on clinical interviews and diagnostic criteria. It often raises various concerns, including false responses by patients, subjective factors, and inexperience of the attendants leading to incorrect diagnosis. Here, we developed a self-monitoring system for simple and objective screening of MDD using a photoplethysmography (PPG) sensor and a 24-GHz microwave radar, which was based on the analysis of heart rate variability (HRV) during paced respiration and mental task conditions. In our previous study, we assessed the reactivity of HRV measurements during a mental task (random number generation) condition in patients with MDD and healthy control subjects. The HRV indices are less reactive in patients with MDD compared to healthy subjects during the mental task, which enabled us to identify the patients at risk for depression. In this study, the reactivity of HRV was measured not only in the mental task but also during paced respiration (i.e., 5-s inhalation and 5-s exhalation) conditions, thereby assessing more detailed autonomic nervous system (ANS) activity via HRV indices. To investigate the effect of paced respiration on MDD screening, we compared the ANS activity via HRV indices in with/without paced respiration conditions in 28 drug-naïve patients with MDD and 27 healthy control subjects. The result showed that ANS significantly activated during the paced respiration condition (p;0.05). The sensitivity in detecting patients with MDD was 86% under paced respiration and mental task conditions, which was higher than the sensitivity (68%) under mental task condition alone.