Anxiety & Stress

Affect and stress detection based on feature fusion of LSTM and 1DCNN.

The impact of emotions on health, especially stress, is receiving increasing attention. It is important to provide a non-invasive affect detection system that can be continuously monitored for a long period of time. Multi-sensor fusion strategies can better improve the performance of affect detection models, but there are also problems such as insufficient feature extraction and poor spatiotempora...

Advancements in Imaging Sensors and AI for Plant Stress Detection: A Systematic Literature Review.

Integrating imaging sensors and artificial intelligence (AI) have contributed to detecting plant stress symptoms, yet data analysis remains a key challenge. Data challenges include standardized data collection, analysis protocols, selection of imaging sensors and AI algorithms, and finally, data sharing. Here, we present a systematic literature review (SLR) scrutinizing plant imaging and AI for id...

Leveraging deep learning models to understand the daily experience of anxiety in teenagers over the course of a year.

INTRODUCTION: Anxiety disorders are a prevalent and severe problem that are often developed early in life and can disrupt the daily lives of affected ...

Cross Dataset Analysis for Generalizability of HRV-Based Stress Detection Models.

Stress is an increasingly prevalent mental health condition across the world. In Europe, for example, stress is considered one of the most common heal...

An interpretable machine learning approach to multimodal stress detection in a simulated office environment.

BACKGROUND AND OBJECTIVE: Work-related stress affects a large part of today's workforce and is known to have detrimental effects on physical and menta...

Hybridizing five neural-metaheuristic paradigms to predict the pillar stress in bord and pillar method.

Pillar stability is an important condition for safe work in room-and-pillar mines. The instability of pillars will lead to large-scale collapse hazard...

Low temperature decreased insecticidal protein contents of cotton and its physiological mechanism.

Low temperature delayed cotton growth, increased abscission of reproductive organs, and seriously reduced quality and yield. Moreover, failed or unsta...

Wearable Artificial Intelligence for Anxiety and Depression: Scoping Review.

BACKGROUND: Anxiety and depression are the most common mental disorders worldwide. Owing to the lack of psychiatrists around the world, the incorporat...

Acute Stress-Induced Changes in the Lipid Composition of Cow's Milk in Healthy and Pathological Animals.

Producers of milk and dairy products have been faced with the challenge of responding to European society's demand for guaranteed animal welfare produ...

Prediction of ethanol fermentation under stressed conditions using yeast morphological data.

A high sugar concentration is used as a starting condition in alcoholic fermentation by budding yeast, which shows changes in intracellular state and ...

Prediction of Tinnitus Treatment Outcomes Based on EEG Sensors and TFI Score Using Deep Learning.

Tinnitus is a hearing disorder that is characterized by the perception of sounds in the absence of an external source. Currently, there is no pharmace...

Enabling Remote Responder Bio-Signal Monitoring in a Cooperative Human-Robot Architecture for Search and Rescue.

The roles of emergency responders are challenging and often physically demanding, so it is essential that their duties are performed safely and effect...

An Efficient AP-ANN-Based Multimethod Fusion Model to Detect Stress through EEG Signal Analysis.

Stress is a universal emotion that every human experiences daily. Psychologists say stress may lead to heart attack, depression, hypertension, strokes...

Classification of Mental Stress from Wearable Physiological Sensors Using Image-Encoding-Based Deep Neural Network.

The human body is designed to experience stress and react to it, and experiencing challenges causes our body to produce physical and mental responses ...

The effect of an interactive robot on children's post-operative anxiety, mobilization, and parents' satisfaction; randomized controlled study.

PURPOSE: To evaluate the effect of an interactive robot on Turkish children's post-operative anxiety, mobilization, and parents' satisfaction related ...

The Ethics of Supernumerary Robotic Limbs. An Enactivist Approach.

Supernumerary robotic limbs are innovative devices in the field of wearable robotics which can provide humans with unprecedented sensorimotor abilitie...

Key factors selection on adolescents with non-suicidal self-injury: A support vector machine based approach.

Comparing a family structure to a company, one can often think of parents as leaders and adolescents as employees. Stressful family environments and a...

Intervention with a humanoid robot avatar for individuals with social anxiety disorders comorbid with autism spectrum disorders.

For some individuals with social anxiety disorders (SAD) comorbid with autism spectrum disorders (ASD), it is difficult to speak in front of others. H...

Predicting the evolution trajectory of population-driven connectional brain templates using recurrent multigraph neural networks.

The mapping of the time-dependent evolution of the human brain connectivity using longitudinal and multimodal neuroimaging datasets provides insights ...

Multimodal fusion diagnosis of depression and anxiety based on CNN-LSTM model.

BACKGROUND: In recent years, more and more people suffer from depression and anxiety. These symptoms are hard to be spotted and can be very dangerous....