Journal Article

Screening for Major Depressive Disorder Using a Wearable Ultra-Short-Term HRV Monitor and Signal Quality Indices

Toshikazu Shinba, Takemi Matsui, Yusuke Obara, Shohei Sato, Takuma Hiratsuka, Kenya Hasegawa, Nobutoshi Kariya, Keisuke Watanabe

2023

Overview

To encourage potential major depressive disorder (MDD) patients to attend diagnostic sessions, we developed a novel MDD screening system based on sleep-induced autonomic nervous responses. The proposed method only requires a wristwatch device to be worn for 24 h. We evaluated heart rate variability (HRV) via wrist photoplethysmography (PPG). However, previous studies have indicated that HRV measurements obtained using wearable devices are susceptible to motion artifacts. We propose a novel method to improve screening accuracy by removing unreliable HRV data (identified on the basis of signal quality indices (SQIs) obtained by PPG sensors). The proposed algorithm enables real-time calculation of signal quality indices in the frequency domain (SQI-FD). A clinical study conducted at Maynds Tower Mental Clinic enrolled 40 MDD patients (mean age, 37.5 ± 8.8 years) diagnosed on the basis of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, and 29 healthy volunteers (mean age, 31.9 ± 13.0 years). Acceleration data were used to identify sleep states, and a linear classification model was trained and tested using HRV and pulse rate data. Ten-fold cross-validation showed a sensitivity of 87.3% (80.3% without SQI-FD data) and specificity of 84.0% (73.3% without SQI-FD data). Thus, SQI-FD drastically improved sensitivity and specificity.

• Publisher: MDPI AG,MDPI
• Subject: Accuracy / Adolescent / Adult / Algorithms / autonomic nervous response / Biomarkers / Chemical technology / Classification / Depressive Disorder, Major / Depressive Disorder, Major - diagnosis / Electrocardiography / Heart beat / Heart Rate / Heart Rate - physiology / Humans / machine learning / Major depressive disorder / major depressive disorder; ultra-short-term heart rate variability; autonomic nervous response; photoplethysmography; signal quality index; machine learning / Mental depression / Mental disorders / Mental illness / Middle Aged / Motion / Photoplethysmography / Physiology / Regression analysis / Sensors / signal quality index / Skin / Sleep / Smartphones / Stress / TP1-1185 / ultra-short-term heart rate variability / Wavelet transforms / Wearable computers / Wearable Electronic Devices / Wrist / Young Adult