Anxiety & Stress

Future perspectives of robot psychiatry: can communication robots assist psychiatric evaluation in the COVID-19 pandemic era?

PURPOSE OF REVIEW: Direct face-to-face interview between a psychiatrist and a patient is crucial in psychiatric evaluation, however, such traditional interviews are becoming difficult to conduct because of the infection risk in the COVID-19 era. As telepsychiatry, video interviews using internet are suggested to be useful to evaluate and assist individuals with mental disorders. However, some pati...

Rapid prediction of drug inhibition under heat stress: single-photon imaging combined with a convolutional neural network.

A method of predicting cellular drug inhibition due to heat stress is presented. Black phosphorus nanosheets are used as photothermal agents to induce stress granule formation in tumor cells. The addition of different drugs induces different thermal stress responses. The features of single-photon images are automatically extracted and analyzed by a convolutional neural network algorithm for classi...

Phonetic variability constrained bottleneck features for joint speaker recognition and physical task stress detection.

Normalizing intrinsic variabilities (e.g., variability in speech production brought on by aging, physical or cognitive task stress, Lombard effect, et...

[A comparative study on treatment of lumbar degenerative disease with osteoporosis by manual and robot-assisted cortical bone trajectory screws fixation].

OBJECTIVE: To compare the safety and accuracy of manual and robot-assisted cortical bone trajectory (CBT) screws fixation in the treatment of lumbar d...

Anxiety and Depression Diagnosis Method Based on Brain Networks and Convolutional Neural Networks.

At present, only professional doctors can use the professional scales to diagnose depression and anxiety in clinical practice. In recent years, the pr...

Multi-level Stress Assessment Using Multi-domain Fusion of ECG Signal.

Stress analysis and assessment of affective states of mind using ECG as a physiological signal is a burning research topic in biomedical signal proces...

Passive Sensor Data Based Future Mood, Health, and Stress Prediction: User Adaptation Using Deep Learning.

Predicting one's mood, health, and stress in the future may provide useful feedback before wellbeing related problems become severe. Previously, resea...

Outcomes of a Robot-Assisted Social-Emotional Understanding Intervention for Young Children with Autism Spectrum Disorders.

This study is a randomized control trial aimed at testing the role of a human-assisted social robot as an intervention mediator in a socio-emotional u...

Spoken words as biomarkers: using machine learning to gain insight into communication as a predictor of anxiety.

OBJECTIVE: The goal of this study was to explore whether features of recorded and transcribed audio communication data extracted by machine learning a...

Targeted prescription of cognitive-behavioral therapy versus person-centered counseling for depression using a machine learning approach.

OBJECTIVE: Depression is a highly common mental disorder and a major cause of disability worldwide. Several psychological interventions are available,...

[Theoretical Review of Robot Anxiety].

The aim of the study is to describe the effect of robot anxiety. The forming of the concept and the description of similar constructs, like technologi...

Predicting post-experiment fatigue among healthy young adults: Random forest regression analysis.

The current study utilized a random forest regression analysis to predict post-experiment fatigue in a sample of 212 healthy participants (mean age = ...

The Language of LGBTQ+ Minority Stress Experiences on Social Media.

LGBTQ+ (lesbian, gay, bisexual, transgender, queer) individuals are at significantly higher risk for mental health challenges than the general populat...

Classification of Perceived Human Stress using Physiological Signals.

In this paper, we present an experimental study for the classification of perceived human stress using non-invasive physiological signals. These inclu...

Detection of Stressful Situations Using GSR While Driving a BCI-controlled Wheelchair.

This paper analyzes the galvanic skin response (GSR) recorded from healthy and motor disabled people while steering a robotic wheelchair (RobChair ISR...

Daytime Data and LSTM can Forecast Tomorrow's Stress, Health, and Happiness.

Accurately forecasting well-being may enable people to make desirable behavioral changes that could improve their future well-being. In this paper, we...

Multi-Modal Acute Stress Recognition Using Off-the-Shelf Wearable Devices.

Monitoring stress and, in general, emotions has attracted a lot of attention over the past few decades. Stress monitoring has many applications, inclu...

Optimizing Probability Threshold of Convolution Neural Network to Improve HRV-based Acute Stress Detection Performance.

As stress is linked to numerous emotional and physical conditions, its timely detection and proper management is important for our health. Convolution...

Combined multivariate analysis and machine learning reveals a predictive module of metabolic stress response in Arabidopsis thaliana.

Abiotic stress exposure of plants induces metabolic reprogramming which is tightly regulated by signalling cascades connecting transcriptional with tr...

Neural mechanisms supporting the relationship between dispositional mindfulness and pain.

Interindividual differences in pain sensitivity vary as a function of interactions between sensory, cognitive-affective, and dispositional factors. Tr...