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This literature review involves the use of AI communication facilitators to detect mood disorders such as bipolar disorder, a psychiatric condition in which patients experience drastic mood shifts. Due to the ill-defined nature of the…
Multimodal sentiment analysis aims to identify the emotions expressed by individuals through visual, language, and acoustic cues. However, most existing research assume that all modalities are available during both training and testing,…
Multimodal sentiment analysis relies on textual, acoustic, and visual signals, yet real-world data often suffer from modality missing and quality imbalance. Existing methods generate features for modality missing from available ones, but…
MoodCam introduces a novel method for assessing mood by utilizing facial affect analysis through the front-facing camera of smartphones during everyday activities. We collected facial behavior primitives during 15,995 real-world phone…
Despite the importance of emphasizing the right psychotherapy treatment for an individual patient, assessing the outcome of the therapy session is equally crucial. Evidence showed that continuous monitoring patient's progress can…
The ability to estimate the current affective statuses of web users has considerable potential for the realization of user-centric services in the society. However, in real-world web services, it is difficult to determine the type of data…
Background: Mobile phone sensor technology has great potential in providing behavioral markers of mental health. However, this promise has not yet been brought to fruition. Objective: The objective of our study was to examine challenges…
Key features of mental illnesses are reflected in speech. Our research focuses on designing a multimodal deep learning structure that automatically extracts salient features from recorded speech samples for predicting various mental…
Predicting mental health from smartphone and social media data on a longitudinal basis has recently attracted great interest, with very promising results being reported across many studies. Such approaches have the potential to…
This tutorial aims to provide signal processing (SP) and machine learning (ML) practitioners with vital tools, in an accessible way, to answer the question: How to deal with missing data? There are many strategies to handle incomplete…
During psychiatric assessment, clinicians observe not only what patients report, but important nonverbal signs such as tone, speech rate, fluency, responsiveness, and body language. Weighing and integrating these different information…
Notifications are one of the most prevailing mechanisms on smartphones and personal computers to convey timely and important information. Despite these benefits, smartphone notifications demand individuals' attention and can cause stress…
Inferring human mental state (e.g., emotion, depression, engagement) with sensing technology is one of the most valuable challenges in the affective computing area, which has a profound impact in all industries interacting with humans. The…
Failure to timely diagnose and effectively treat depression leads to over 280 million people suffering from this psychological disorder worldwide. The information cues of depression can be harvested from diverse heterogeneous resources,…
According to the World Health Organization (WHO), one in four people will be affected by mental disorders at some point in their lives. However, in many parts of the world, patients do not actively seek professional diagnosis because of…
Mobile technology enables unprecedented continuous monitoring of an individual's behavior, social interactions, symptoms, and other health conditions, presenting an enormous opportunity for therapeutic advancements and scientific…
Depression is a widespread mental disorder that affects millions worldwide. While automated depression assessment shows promise, most studies rely on limited or non-clinically validated data, and often prioritize complex model design over…
Clinical practice in psychiatry is burdened with the increased demand for healthcare services and the scarce resources available. New paradigms of health data powered with machine learning techniques could open the possibility to improve…
Mental disorders such as depression and suicidal ideation are hazardous, affecting more than 300 million people over the world. However, on social media, mental disorder symptoms can be observed, and automated approaches are increasingly…
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…