Results 31 to 40 of about 7,125 (175)

Subjective Listening Effort and Electrodermal Activity in Listening Situations with Reverberation and Noise

Trends in Hearing, 2016
Disturbing factors like reverberation or ambient noise can impair speech recognition and raise the listening effort needed for successful communication in daily life. Situations with high listening effort are thought to result in increased stress for the
Inga Holube, Kristina Haeder, Christina Imbery, Reinhard Weber   +3 more
doaj   +1 more source

Psychological mechanisms of offset analgesia: The effect of expectancy manipulation.

PLoS ONE, 2023
A frequently used paradigm to quantify endogenous pain modulation is offset analgesia, which is defined as a disproportionate large reduction in pain following a small decrease in a heat stimulus. The aim of this study was to determine whether suggestion
Tibor M Szikszay, Waclaw M Adamczyk, Janina Panskus, Lotte Heimes, Carolin David, Philip Gouverneur, Kerstin Luedtke   +6 more
doaj   +1 more source

Personality and Reactions to Sudden Events: Effects of Different Approaches to Modelling Physiological Reactions

Psychological Topics, 2020
This study aimed to examine interindividual differences in electrodermal responses to a sudden stimulus by using different methods of electrodermal reaction assessment.
Marko Tončić
doaj  

Wearable Technologies for Electrodermal and Cardiac Activity Measurements: A Comparison between Fitbit Sense, Empatica E4 and Shimmer GSR3+

Sensors, 2023
The capability of measuring specific neurophysiological and autonomic parameters plays a crucial role in the objective evaluation of a human’s mental and emotional states. These human aspects are commonly known in the scientific literature to be involved
Vincenzo Ronca, Ana C. Martinez-Levy, Alessia Vozzi, Andrea Giorgi, Pietro Aricò, Rossella Capotorto, Gianluca Borghini, Fabio Babiloni, Gianluca Di Flumeri   +8 more
doaj   +1 more source

Active learning for electrodermal activity classification [PDF]

2015 IEEE Signal Processing in Medicine and Biology Symposium (SPMB), 2015
To filter noise or detect features within physiological signals, it is often effective to encode expert knowledge into a model such as a machine learning classifier. However, training such a model can require much effort on the part of the researcher; this often takes the form of manually labeling portions of signal needed to represent the concept ...
Xia, Victoria F., Jaques, Natasha Mary, Taylor, Sara Ann, Fedor, Szymon, Picard, Rosalind W.   +4 more
openaire   +3 more sources

Machine Learning‐Driven Digital Twin of a Field‐Effect Transistor‐Based Hormone Biosensor for Real‐Time Estradiol Monitoring

Advanced Intelligent Systems, EarlyView.
A machine learning‐driven digital twin simulates an aptamer‐functionalized BioFET measuring 17β‐estradiol. Real‐time Isd signals are processed, features are extracted, and trained models estimate hormone concentration. In parallel, a one‐step‐ahead forward model learns biosensor dynamics and generates realistic synthetic signals, enabling in silico ...
Anastasiia Gorelova, Alexandra Parichenko, Shirong Huang, Santiago Melia, Gianaurelio Cuniberti   +4 more
wiley   +1 more source

Advances in vital‐sign prediction and early‐warning models for underground coal mine workers integrating environmental factors

Deep Underground Science and Engineering, EarlyView.
This review synthesizes advances in predicting miners' vital signs by integrating environmental monitoring (dust, temperature, and gas) with physiological data. It highlights multi‐source data fusion techniques and early‐warning models for enhanced occupational safety in underground coal mines.
Junji Zhu, Dawei Cui, Yingjie Liu, Yuntao Liang, Yue Zhang   +4 more
wiley   +1 more source

Video‐based diagnostics supported by artificial intelligence as an opportunity to address the epilepsy diagnostic gap: A narrative review

Epilepsia, EarlyView.
Abstract Despite advancements in epilepsy care, a substantial diagnostic gap persists, particularly in resource‐limited settings. This narrative review explores the potential of video‐based diagnostics augmented by artificial intelligence (AI) to address this gap by enabling earlier and more accessible seizure detection and classification.
Gadi Miron, Robert Terziev, Maximilian Schöls, John McLaren, Tobias Loddenkemper, Jörg Wellmer, Sigrid Mues, Christian Meisel   +7 more
wiley   +1 more source

Electrodermal activity - a review

Ingeniería e Investigación, 2011
The electricity in living tissue was widely studied around the 19th century. Such study was suspended for many years but has then been started again during recent decades. New research into bioelectricity is creating alternatives in the health field; one of them is an electrodermal response associated with the wound healing, cell stimulation and ...
María Elena Moncada, Juan Pablo Cruz
openaire   +1 more source

Rhythms in longitudinal thalamic recordings are linked to seizure risk

Epilepsia, EarlyView.
Abstract Objective Seizure unpredictability remains a major clinical challenge for people with epilepsy. Previous works have shown that seizure risk is associated with circadian and multi‐day cycles in both brain and physiological signals. However, it remains unclear whether neural activity from deep brain structures such as the anterior nucleus of the
Xinbing Zhang, Zachary T. Sanger, Thomas Lisko, Steffen Ventz, Robert A. McGovern, Theoden I. Netoff   +5 more
wiley   +1 more source