Predicting depressed patients with suicidal ideation from ECG recordings

AH Khandoker, V Luthra, Y Abouallaban… - Medical & biological …, 2017 - Springer
Globally suicidal behavior is the third most common cause of death among patients with
major depressive disorder (MDD). This study presents multi-lag tone–entropy (T–E) analysis …

Entropy analysis of heart rate variability and its application to recognize major depressive disorder: A pilot study

S Byun, AY Kim, EH Jang, S Kim… - … and Health Care, 2019 - content.iospress.com
BACKGROUND: The current method to evaluate major depressive disorder (MDD) relies on
subjective clinical interviews and self-questionnaires. OBJECTIVE: Autonomic imbalance in …

Suicidal ideation is associated with altered variability of fingertip photo-plethysmogram signal in depressed patients

AH Khandoker, V Luthra, Y Abouallaban… - Frontiers in …, 2017 - frontiersin.org
Physiological and psychological underpinnings of suicidal behavior remain ill-defined and
lessen timely diagnostic identification of this subgroup of patients. Arterial stiffness is …

Automated recognition of major depressive disorder from cardiovascular and respiratory physiological signals

MS Zitouni, S Lih Oh, J Vicnesh, A Khandoker… - Frontiers in …, 2022 - frontiersin.org
Major Depressive Disorder (MDD) is a neurohormonal disorder that causes persistent
negative thoughts, mood and feelings, often accompanied with suicidal ideation (SI). Current …

[PDF][PDF] A multimodal prediction model for suicidal attempter in major depressive disorder

Q Li, K Liao - PeerJ, 2023 - peerj.com
Background. Suicidal attempts in patients with major depressive disorder (MDD) have
become an important challenge in global mental health affairs. To correctly distinguish MDD …

The relationships of current suicidal ideation with inflammatory markers and heart rate variability in unmedicated patients with major depressive disorder

CC Chang, NS Tzeng, YC Kao, CB Yeh, HA Chang - Psychiatry Research, 2017 - Elsevier
Studies investigating inflammatory status and autonomic functioning simultaneously in
depressed patients with current suicidal ideation (SI) are lacking. We recruited 58 …

Identification of major depression patients using machine learning models based on heart rate variability during sleep stages for pre-hospital screening

D Geng, Q An, Z Fu, C Wang, H An - Computers in Biology and Medicine, 2023 - Elsevier
With the COVID-19 pandemic causing challenges in hospital admissions globally, the role of
home health monitoring in aiding the diagnosis of mental health disorders has become …

Cardiorespiratory coupling analysis based on entropy and cross-entropy in distinguishing different depression stages

L Zhao, L Yang, Z Su, C Liu - Frontiers in physiology, 2019 - frontiersin.org
Aims This study used entropy-and cross entropy-based methods to explore the
cardiorespiratory coupling of depressive patients, and thus to assess the values of those …

An objective screening method for major depressive disorder using logistic regression analysis of heart rate variability data obtained in a mental task paradigm

G Sun, T Shinba, T Kirimoto, T Matsui - Frontiers in Psychiatry, 2016 - frontiersin.org
Background and objectives Heart rate variability (HRV) has been intensively studied as a
promising biological marker of major depressive disorder (MDD). Our previous study …

Prediction of suicide-related events by analyzing electronic medical records from PTSD patients with bipolar disorder

P Fan, X Guo, X Qi, M Matharu, R Patel, D Sakolsky… - Brain sciences, 2020 - mdpi.com
Around 800,000 people worldwide die from suicide every year and it's the 10th leading
cause of death in the US. It is of great value to build a mathematic model that can accurately …