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Mental Stress Detection using EEG and Recurrent Deep Learning

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Artificial Intelligence Models to Predict Disability for Mental Health Disorders

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Integration of Multi-Modal Biosensing Approaches for Depression: Current Status, Challenges, and Future Perspectives

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An Overview of Wearable Biosensor Systems for Real-Time Substance Use Detection

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IoT-enabled model for Digital Twin Of Mental Stress (DTMS)

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Understanding and Modeling Viewers’ First Impressions with Images in Online Medical Crowdfunding Campaigns

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A Systematic Review of Machine Learning Models in Mental Health Analysis Based on Multi-Channel Multi-Modal Biometric Signals

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EmotIoT: An IoT System to Improve Users’ Wellbeing

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Mental health benefits of traditional Chinese medicine – An umbrella review of meta-analyses

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Depression prediction based on LassoNet-RNN model: A longitudinal study

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Evaluation of the performance of supervised and unsupervised Machine learning techniques for intrusion detection

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New evidence on technological acceptance model in preschool education: Linking project-based learning (PBL), mental health, and semi-immersive virtual reality with learning performance

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Predicting and Monitoring Anxiety and Depression: Advanced Machine Learning Techniques for Mental Health Analysis

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An integrated approach for mental health assessment using emotion analysis and scales

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From Monitoring to Assisting: A Systematic Review towards Healthier Workplaces

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Healthcare Professionals' Views on the Use of Passive Sensing and Machine Learning Approaches in Secondary Mental Healthcare: A Qualitative Study

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Identification of Schizophrenic Individuals Using Activity Records Through Visualization of Recurrent Networks

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Semantic Mediation Model to Promote Improved Data Sharing Using Representation Learning in Heterogeneous Healthcare Service Environments

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Human centered design of AI-powered Digital Therapeutics for stress prevention: Perspectives from multi-stakeholders' workshops about the SHIVA solution

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Examining and Promoting Explainable Recommendations for Personal Sensing Technology Acceptance

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Objective Monitoring of Facioscapulohumeral Dystrophy During Clinical Trials Using a Smartphone App and Wearables: Observational Study

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Ensemble Learning Approach to Human Stress Detection Based on Behaviours During the Sleep

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Step by Step Towards Effective Human Activity Recognition: A Balance between Energy Consumption and Latency in Health and Wellbeing Applications

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Artificial Intelligence - Enabled IoT for Health and Wellbeing Monitoring

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Heart Rate Prediction from Head Movement during Virtual Reality Treatment for Social Anxiety

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Evaluating and mitigating unfairness in multimodal remote mental health assessments

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Cannabis use and suicidal ideation among youth: Can we democratize school policies using digital citizen science?

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Big Five Personality Traits Prediction Using Brain Signals

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Depression and Anxiety Screening for Pregnant Women via Free Conversational Speech in Naturalistic Condition

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Acoustic and Natural Language Markers for Bipolar Disorder: A Pilot, mHealth Cross-Sectional Study

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Enhancing mental well-being: An artificial intelligence model for predicting mental disorders

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Prediction of schizophrenia from activity data using hidden Markov model parameters

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Mental Health Tracker Using Machine Learning Approaches

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Responsible Artificial Intelligence for Mental Health Disorders: Current Applications and Future Challenges

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An Extended Review Concerning the Relevance of Deep Learning and Privacy Techniques for Data-Driven Soft Sensors

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Human Stress Detection Based on Sleeping Habits Using Machine Learning Algorithms

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SFF-DA: Spatiotemporal Feature Fusion for Nonintrusively Detecting Anxiety

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Wearable smart textiles—recent development and applications

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Neurophysiological Approach for Psychological Safety: Enhancing Mental Health in Human–Robot Collaboration in Smart Manufacturing Setups Using Neuroimaging

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Predictive Analytics in Mental Health: Machine Learning Models for Major Depressive Disorder Detection using Sensor Data

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Accurate Insights, Trustworthy Interactions: Designing a Collaborative AI-Human Multi-Agent System with Knowledge Graph for Diagnosis Prediction

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Diagnosing Schizophrenia from Activity Records using Hidden Markov Model Parameters

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Multimodal mental state analysis

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Things that help out: designing smart wearables as partners in stress management

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Artificial Intelligence in Biometrics: Uncovering Intricacies of Human Body and Mind

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Depression detection: approaches, challenges and future directions

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The design of a mental health service platform for college students based on multi-modal information

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AI based Dynamic Prediction Model for Mobile Health Application System

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“Sensing the Mind”: An Exploratory Study About Sensors Used in E-Health and M-Health Applications for Diagnosis of Mental Health Condition

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AI-Driven Tools for Detecting and Monitoring Mental Health Conditions Though Behaviour Patterns

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Data quality and privacy concerns in digital trace data

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Artificial Intelligence in Mental Health Care

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HTAD: A Home-Tasks Activities Dataset with Wrist-Accelerometer and Audio Features

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Supporting Anxiety Patients’ Self-Reflection through Visualization of Physiological Data.

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Real-time twitter data analytics of mental illness in COVID-19: sentiment analysis using deep neural network

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On Leveraging FemtoClouds for Federated Learning

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OBF-Psychiatric, a motor activity dataset of patients diagnosed with major depression, schizophrenia, and ADHD

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Developing personalized algorithms for sensing mental health symptoms in daily life

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Cross-sectional associations of self-perceived stress and hair cortisol with metabolic outcomes and microvascular complications in type 2 diabetes

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Automated ADHD detection using dual-modal sensory data and machine learning

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Development of intelligent system based on synthesis of affective signals and deep neural networks to foster mental health of the Indian virtual community

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Futures for Health Research Data Platforms From the Participants’ Perspectives

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Towards Clustering Human Behavioral Patterns based on Digital Phenotyping

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An Ensemble Technique to Analyse Mental Health of Workforce in the Corporate Sector

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Enhanced stacking ensemble Model: A statistical ensemble pruning framework to classify anxiety severity for responsive emergency preparedness

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