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Identifying physiological and behavioral markers for mental health conditions is a longstanding challenge in psychiatry. Depression and suicidal ideation, in particular, lack objective biomarkers, with screening and diagnosis primarily…

In behavioral health informatics, inferring an individual's psychological state from physiological and behavioral data is fundamental. A key physiological signal in this endeavor is electrodermal activity (EDA), often quantified as skin…

Systems and Control · Electrical Eng. & Systems 2023-11-07 Hui Sophie Wang , Stacy Marsella , Misha Pavel

The quantitative analysis of non-invasive electrophysiology signals from electroencephalography (EEG) and magnetoencephalography (MEG) boils down to the identification of temporal patterns such as evoked responses, transient bursts of…

Signal Processing · Electrical Eng. & Systems 2022-07-12 Cédric Allain , Alexandre Gramfort , Thomas Moreau

Major Depressive Disorder (MDD) is a highly prevalent mental health condition, and a deeper understanding of its neurocognitive foundations is essential for identifying how core functions such as emotional and self-referential processing…

While depression has been studied via multimodal non-verbal behavioural cues, head motion behaviour has not received much attention as a biomarker. This study demonstrates the utility of fundamental head-motion units, termed \emph{kinemes},…

Computer Vision and Pattern Recognition · Computer Science 2023-07-25 Monika Gahalawat , Raul Fernandez Rojas , Tanaya Guha , Ramanathan Subramanian , Roland Goecke

Depression is a complex mental disorder characterized by a diverse range of observable and measurable indicators that go beyond traditional subjective assessments. Recent research has increasingly focused on objective, passive, and…

Machine Learning · Computer Science 2025-04-21 Yassine Ouzar , Clémence Nineuil , Fouad Boutaleb , Emery Pierson , Ali Amad , Mohamed Daoudi

In high-pressure environments where human individuals must simultaneously monitor multiple entities, communicate effectively, and maintain intense focus, the perception of time becomes a critical factor influencing performance and…

Human-Computer Interaction · Computer Science 2024-10-27 Till Aust , Eirini Balta , Argiro Vatakis , Heiko Hamann

Depression manifests through a diverse set of symptoms such as sleep disturbance, loss of interest, and concentration difficulties. However, most existing works treat depression prediction either as a binary label or an overall severity…

Computation and Language · Computer Science 2026-02-18 Chaithra Nerella , Chiranjeevi Yarra

We describe the development of a model to detect user-level clinical depression based on a user's temporal social media posts. Our model uses a Depression Symptoms Detection (DSD) classifier, which is trained on the largest existing samples…

Computation and Language · Computer Science 2023-03-31 Nawshad Farruque , Randy Goebel , Sudhakar Sivapalan , Osmar R. Zaïane

Current management of bipolar disorder relies on self-reported questionnaires and interviews with clinicians. The development of objective measures of deteriorating mood may also allow for early interventions to take place to avoid…

Signal Processing · Electrical Eng. & Systems 2020-07-08 Oliver Carr , Fernando Andreotti , Kate E. A. Saunders , Niclas Palmius , Guy M. Goodwin , Maarten De Vos

Depression is a common mental disorder that causes people to experience depressed mood, loss of interest or pleasure, feelings of guilt or low self-worth. Traditional clinical depression diagnosis methods are subjective and time consuming.…

Human-Computer Interaction · Computer Science 2022-11-22 Chuang Yu

Current automatic depression detection systems provide predictions directly without relying on the individual symptoms/items of depression as denoted in the clinical depression rating scales. In contrast, clinicians assess each item in the…

Objective: A person's affective state has known relationships to physiological processes which can be measured by wearable sensors. However, while there are general trends those relationships can be person-specific. This work proposes using…

Applications · Statistics 2020-02-12 Callum L. Stewart , Amos Folarin , Richard Dobson

Early detection of psychological distress is key to effective treatment. Automatic detection of distress, such as depression, is an active area of research. Current approaches utilise vocal, facial, and bodily modalities. Of these, the…

Computer Vision and Pattern Recognition · Computer Science 2020-03-03 Indigo J. D. Orton

Recurrent major mood episodes and subsyndromal mood instability cause substantial disability in patients with bipolar disorder. Early identification of mood episodes enabling timely mood stabilisation is an important clinical goal. Recent…

Machine Learning · Statistics 2017-08-04 Andrey Kormilitzin , Kate E. A. Saunders , Paul J. Harrison , John R. Geddes , Terry Lyons

Depression and suicidality affect cognitive and emotional processes, yet objective, task-evoked neural readouts of mental health remain limited. We investigated the spatiotemporal dynamics of affective semantic processing using multivariate…

Stress can be seen as a physiological response to everyday emotional, mental and physical challenges. A long-term exposure to stressful situations can have negative health consequences, such as increased risk of cardiovascular diseases and…

Machine Learning · Computer Science 2017-11-20 Aaqib Saeed , Stojan Trajanovski

Depression is characterized by persistent sadness and loss of interest, significantly impairing daily functioning and now a widespread mental disorder. Traditional diagnostic methods rely on subjective assessments, necessitating objective…

Depression is a debilitating mood disorder negatively impacting millions worldwide. While researchers have explored multiple verbal and non-verbal behavioural cues for automated depression assessment, head motion has received little…

A person's passage of time perception (POTP) is strongly linked to their mental state and stress response, and can therefore provide an easily quantifiable means of continuous mental health monitoring. In this work, we develop a custom…

Signal Processing · Electrical Eng. & Systems 2021-07-15 Lara Orlandic , Adriana Arza Valdes , David Atienza
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