An Objective Screening Method for Major Depressive Disorder Using Logistic Regression Analysis of Heart Rate Variability Data Obtained in a Mental Task Paradigm

Abstract

Background and objectivesHeart rate variability (HRV) has been intensively studied as a promising biological marker of major depressive disorder (MDD). Our previous study confirmed that autonomic activity and reactivity in depression revealed by HRV during rest and mental task (MT) conditions can be used as diagnostic measures and in clinical evaluation. In this study, logistic regression analysis (LRA) was utilized for the classification and prediction of MDD based on HRV data obtained in an MT paradigm.MethodsPower spectral analysis of HRV on R–R intervals before, during, and after an MT (random number generation) was performed in 44 drug-naïve patients with MDD and 47 healthy control subjects at Department of Psychiatry in Shizuoka Saiseikai General Hospital. Logit scores of LRA determined by HRV indices and heart rates discriminated patients with MDD from healthy subjects. The high frequency (HF) component of HRV and the ratio of the low frequency (LF) component to the HF component (LF/HF) correspond to parasympathetic and sympathovagal balance, respectively.ResultsThe LRA achieved a sensitivity and specificity of 80.0 and 79.0%, respectively, at an optimum cutoff logit score (0.28). Misclassifications occurred only when the logit score was close to the cutoff score. Logit scores also correlated significantly with subjective self-rating depression scale scores (p < 0.05).ConclusionHRV indices recorded during a MT may be an objective tool for screening patients with MDD in psychiatric practice. The proposed method appears promising for not only objective and rapid MDD screening but also evaluation of its severity.

Development and Clinical Application of a Novel Autonomic Transient Response-Based Screening System for Major Depressive Disorder Using a Fingertip Photoplethysmographic Sensor

“…The HF band (0.15–0.4 Hz) is associated with parasympathetic activity and the LF band (0.04–0.15 Hz) is modulated by baroreflex-induced cardiac autonomic outflow (Goldstein et al, 2011 ). Based on these properties, our previous study confirmed that variance in HRV variables could be used as an MDD screening tool (Sun et al, 2016 ).…”

“…Conventionally, MDD is diagnosed by subjective methods such as self-report screening questionnaires or psychiatrist interviews based on Diagnostic and Statistical Manual of Mental Disorders V (DSM-V) published by American Psychiatric Association. Our previous study (Sun et al, 2016 ) adopted mental task induced autonomic response determined by ECG-derived HRV for MDD screening. The ECG-derived HRV based method achieved 80% sensitivity and 79% specificity via 91 subjects' (44 patients with MDD and 47 normal volunteers) HRV dataset.…”

“…Therefore, comfort enhanced and user-friendly self-monitoring system for MDD screening is proposed in this paper. The system described here adopts a fingertip PPG sensor, which has several advantages over the initial ECG system that we previously described (Sun et al, 2016 ).…”

Development and Clinical Application of a Novel Non-contact Early Airflow Limitation Screening System Using an Infrared Time-of-Flight Depth Image Sensor

“…We have previously developed various medical screening systems, including respiratory measurement devices, such as a household-use Major Depressive Disorder screening system and infection screening systems, including a pediatric pneumonia monitor using a Doppler radar that determines a respiratory curve and estimates the respiration rate ( Matsui et al, 2010 ; Sun et al, 2014 , 2015 , 2016 ; Dagdanpurev et al, 2018 , 2019 ). A non-contact respiratory monitoring method using a fiber-grating vision sensor has been developed to evaluate the pulmonary functions of patients with airflow limitation ( Tsujimura et al, 2011 ).…”

Noncontact Monitoring of Vital Signs with RGB and Infrared Camera and Its Application to Screening of Potential Infection

“…There have also been reports regarding methods for measuring respiration or heartbeat using pressure sensors [1], microwave radar [2], air mattresses, or high-polymer piezoelectric film. The methods have wide-ranging applications, including systems for monitoring elderly people [3], identification of sleep apnea [4], detection of patients suspected to have an infectious disease [5,6], and noncontact measurement of stress levels [7]. In this chapter, the principles behind noncontact measurement of respiration and heartbeat using infrared/RGB facial-image analysis are discussed, along with the applications for such measurement in the detection of patients suspected to be suffering from an infectious disease.…”