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

Abstract

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.

The Use of Photoplethysmography in the Assessment of Mental Health: Scoping Review

“…After title screening and review of 114 abstracts against the inclusion and exclusion criteria, followed by full-text retrieval, 24 studies were included in the review [ 31 - 54 ]. It should be noted that the 2 sets of studies were sister papers [ 32 , 37 , 38 , 51 , 52 ]. The sister papers are those authored by the same author who published multiple articles using the same data set.…”

“…Most of these were proof-of-concept studies with a small number of participants. Three studies had a control group with sample sizes ranging from 61 to 308 [ 37 , 42 , 52 ]. The age range was broad across the studies, ranging from 16 to 85 years.…”

“…Only 3 studies compared patients with MDD with those who did not have clinical depression [ 42 , 52 , 54 ]. One study examined suicidal ideation in patients with MDD and in patients with MDD who did not have suicidal ideation [ 37 ]. There were no longitudinal studies.…”

“…HR was elevated when participants were stressed, and PPG could accurately capture these physiological changes, including HR reduction during relaxing exercises [ 10 , 42 , 43 , 64 , 65 ]. In addition to stress, PPG also accurately detects patients who are depressed [ 32 - 34 , 37 , 38 , 40 , 41 , 44 , 45 , 48 , 49 , 52 , 54 ], including those with MDD. In other words, depression was associated with a lower HR in contrast to stress.…”

Teaching Machines to Know Your Depressive State: On Physical Activity in Health and Major Depressive Disorder

“…Mumtaz et al proposed a method based on logistic regression to discriminate MDD patients and healthy controls via EEG data [8]. Among EEG signals, other physiological signals, e. g., arterial pulse signals [9], heart rate variability [10], images [11], and audio signals [12] were used for extracting representations for building MDD machine learning models. The experimental results of these limited studies are encouraging and promising.…”