Heart rate variability for medical decision support systems: A review

O Faust, W Hong, HW Loh, S Xu, RS Tan… - Computers in biology …, 2022 - Elsevier
Abstract Heart Rate Variability (HRV) is a good predictor of human health because the heart
rhythm is modulated by a wide range of physiological processes. This statement embodies …

An insight into diagnosis of depression using machine learning techniques: a systematic review

S Bhadra, CJ Kumar - Current medical research and opinion, 2022 - Taylor & Francis
Background In this modern era, depression is one of the most prevalent mental disorders
from which millions of individuals are affected today. The symptoms of depression are …

[HTML][HTML] Automatic depression detection using smartphone-based text-dependent speech signals: deep convolutional neural network approach

AY Kim, EH Jang, SH Lee, KY Choi, JG Park… - Journal of medical …, 2023 - jmir.org
Background Automatic diagnosis of depression based on speech can complement mental
health treatment methods in the future. Previous studies have reported that acoustic …

End-to-end depression recognition based on a one-dimensional convolution neural network model using two-lead ECG signal

X Zang, B Li, L Zhao, D Yan, L Yang - Journal of Medical and Biological …, 2022 - Springer
Purpose Depression is a common mental illness worldwide and has become an important
public health problem. The current clinical diagnosis of depression mainly relies on the …

Heart Rate Variability in Psychiatric Disorders: A Systematic Review

A Ramesh, T Nayak, M Beestrum, G Quer… - Neuropsychiatric …, 2023 - Taylor & Francis
Introduction Heart rate variability (HRV) is a measure of the fluctuation in time interval
between consecutive heart beats. Decreased heart rate variability has been shown to have …

Approximate entropy of brain network in the study of hemispheric differences

F Alù, F Miraglia, A Orticoni, E Judica, M Cotelli… - Entropy, 2020 - mdpi.com
Human brain, a dynamic complex system, can be studied with different approaches,
including linear and nonlinear ones. One of the nonlinear approaches widely used in …

Digital phenotype of mood disorders: A conceptual and critical review

R Maatoug, A Oudin, V Adrien, B Saudreau… - Frontiers in …, 2022 - frontiersin.org
Background Mood disorders are commonly diagnosed and staged using clinical features
that rely merely on subjective data. The concept of digital phenotyping is based on the idea …

[HTML][HTML] When heart beats differently in depression: review of nonlinear heart rate variability measures

M Čukić, D Savić, J Sidorova - JMIR Mental Health, 2023 - mental.jmir.org
Background: Disturbed heart dynamics in depression seriously increases mortality risk.
Heart rate variability (HRV) is a rich source of information for studying this dynamics. This …

Age-based analysis of heart rate variability (HRV) for patients with congestive heart failure

H Namazi, D Baleanu, O Krejcar - Fractals, 2021 - World Scientific
It is known that heart activity changes during aging. In this paper, we evaluated alterations of
heart activity from the complexity point of view. We analyzed the variations of heart rate of …

Information-based classification of electroencephalography (EEG) signals for healthy adolescents and adolescents with symptoms of Schizophrenia

H Namazi - Fluctuation and Noise Letters, 2020 - World Scientific
Analysis of the brain activity is the major research area in human neuroscience. Besides
many works that have been conducted on analysis of brain activity in case of healthy …