AIMC Topic: Galvanic Skin Response
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Continuous Short-Term Pain Assessment in Temporomandibular Joint Therapy Using LSTM Models Supported by Heat-Induced Pain Data Patterns.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sep 25, 2024
This study aims to design a time-continuous pain level assessment system for temporomandibular joint therapy. Our objectives cover verifying literature suggestions on pain stimulus, protocols for collecting reference data, and continuous pain recogni...
Machine learning based classification of presence utilizing psychophysiological signals in immersive virtual environments.
Scientific reports
Sep 17, 2024
In Virtual Reality (VR), a higher level of presence positively influences the experience and engagement of a user. There are several parameters that are responsible for generating different levels of presence in VR, including but not limited to, grap...
Infants' psychophysiological responses to eye contact with a human and with a humanoid robot.
Biological psychology
Aug 17, 2024
Eye contact with a human and with a humanoid robot elicits attention- and affect-related psychophysiological responses. However, these responses have mostly been studied in adults, leaving their developmental origin poorly understood. In this study, ...
Machine learning-enabled detection of attention-deficit/hyperactivity disorder with multimodal physiological data: a case-control study.
BMC psychiatry
Aug 5, 2024
BACKGROUND: Attention-Deficit/Hyperactivity Disorder (ADHD) is a multifaceted neurodevelopmental psychiatric condition that typically emerges during childhood but often persists into adulthood, significantly impacting individuals' functioning, relati...
A machine-learning approach for stress detection using wearable sensors in free-living environments.
Computers in biology and medicine
Jul 18, 2024
Stress is a psychological condition resulting from the body's response to challenging situations, which can negatively impact physical and mental health if experienced over prolonged periods. Early detection of stress is crucial to prevent chronic he...
Deep learning-based stress detection for daily life use using single-channel EEG and GSR in a virtual reality interview paradigm.
PloS one
Jul 3, 2024
This research aims to establish a practical stress detection framework by integrating physiological indicators and deep learning techniques. Utilizing a virtual reality (VR) interview paradigm mirroring real-world scenarios, our focus is on classifyi...
Applying artificial intelligence on EDA sensor data to predict stress on minimally invasive robotic-assisted surgery.
International journal of computer assisted radiology and surgery
Jul 2, 2024
PURPOSE: This study aims predicting the stress level based on the ergonomic (kinematic) and physiological (electrodermal activity-EDA, blood pressure and body temperature) parameters of the surgeon from their records collected in the previously immed...
Robots as Mental Health Coaches: A Study of Emotional Responses to Technology-Assisted Stress Management Tasks Using Physiological Signals.
Sensors (Basel, Switzerland)
Jun 21, 2024
The current study investigated the effectiveness of social robots in facilitating stress management interventions for university students by evaluating their physiological responses. We collected electroencephalogram (EEG) brain activity and Galvanic...
Cognitive workload classification of law enforcement officers using physiological responses.
Applied ergonomics
May 10, 2024
Motor vehicle crashes (MVCs) are a leading cause of death for law enforcement officers (LEOs) in the U.S. LEOs and more specifically novice LEOs (nLEOs) are susceptible to high cognitive workload while driving which can lead to fatal MVCs. The object...
Human Activity Recognition Algorithm with Physiological and Inertial Signals Fusion: Photoplethysmography, Electrodermal Activity, and Accelerometry.
Sensors (Basel, Switzerland)
May 9, 2024
Inertial signals are the most widely used signals in human activity recognition (HAR) applications, and extensive research has been performed on developing HAR classifiers using accelerometer and gyroscope data. This study aimed to investigate the po...
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