Suchergebnisse - "physiological data"

Predicting high anger intensity using ecological momentary assessment and wearable-derived physiological data in a trauma-affected sample

Autoren: Metcalf, Olivia Lamb, Karen E Forbes, David et al.

Quelle: European Journal of Psychotraumatology. 16(1)

Schlagwörter: 32 Biomedical and Clinical Sciences (for-2020), 5201 Applied and Developmental Psychology (for-2020), 5203 Clinical and Health Psychology (for-2020), 3202 Clinical Sciences (for-2020), 52 Psychology (for-2020), Social Determinants of Health (rcdc), Behavioral and Social Science (rcdc), Bioengineering (rcdc), Clinical Research (rcdc), Mental Health (rcdc), 4.1 Discovery and preclinical testing of markers and technologies (hrcs-rac), 3 Good Health and Well Being (sdg), Humans (mesh), Anger (mesh), Ecological Momentary Assessment (mesh), Male (mesh), Female (mesh), Wearable Electronic Devices (mesh), Adult (mesh), Heart Rate (mesh), Middle Aged (mesh), Young Adult (mesh), Anger, trauma, HRV, physiological data, digital phenotyping, machine learning, prediction modeling, Ira, Humans (mesh), Anger (mesh), Heart Rate (mesh), Adult (mesh), Middle Aged (mesh), Female (mesh), Male (mesh), Young Adult (mesh), Ecological Momentary Assessment (mesh), Wearable Electronic Devices (mesh), Anger, HRV, Ira, datos fisiológicos, digital phenotyping, fenotipado digital, machine learning, physiological data, predicción, prediction modeling, trauma, Humans (mesh), Anger (mesh), Ecological Momentary Assessment (mesh), Male (mesh), Female (mesh), Wearable Electronic Devices (mesh), Adult (mesh), Heart Rate (mesh), Middle Aged (mesh), Young Adult (mesh)

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/11t2k02h
https://escholarship.org/content/qt11t2k02h/qt11t2k02h.pdf

Physiological Responses to Affective Virtual Coach Design in a VR Fear of Heights Consultation

Autoren: Shu Wei Abdallah El Ali Pablo Cesar et al.

Quelle: Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems. :1-8

Schlagwörter: Psychotherapy, Mental Health, SDG 3 - Good Health and Well-being, Physiological Data, Virtual Coach, Virtual Reality (VR), Agent

Key Principles Involving Ethical and Deontological Issues in Military Stress Management Training in Virtual Reality Environments

Autoren: Veloso Gomes, Paulo Vianez, Ana Curado, Henrique et al.

Quelle: RUC. Repositorio da Universidade da Coruña
Universidade da Coruña (UDC)

Schlagwörter: Resilience, Physiological data, Mental and physical state, Training, VR programs, Military stress

Zugangs-URL: http://hdl.handle.net/2183/41134

Association of daily lung condition in COPD patients with wearable speech and physiological data

Autoren: Sejal Bhalla Deshang Kong Salaar Liaqat et al.

Quelle: Scientific Reports, Vol 15, Iss 1, Pp 1-12 (2025)

Schlagwörter: COPD, Physiological data, Continuous health sensing, Medicine, Science

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2045-2322

Zugangs-URL: https://doaj.org/article/f10fa17afd9b472d8409fbb952d625c1

A deep learning approach to stress recognition through multimodal physiological signal image transformation

Autoren: Shiqi Yang Yuan Gao Yao Zhu et al.

Quelle: Scientific Reports, Vol 15, Iss 1, Pp 1-11 (2025)

Schlagwörter: Stress recognition, Multimodal physiological data, Deep neural network, WESAD dataset, Image encoding, Medicine, Science

Dateibeschreibung: electronic resource

Relation: https://doaj.org/toc/2045-2322

Zugangs-URL: https://doaj.org/article/c6f350d7f5cb4c878ba584f35eed1251

SiamQuality: a ConvNet-based foundation model for photoplethysmography signals.

Autoren: Ding, Cheng Guo, Zhicheng Chen, Zhaoliang et al.

Quelle: Physiological Measurement. 45(8)

Schlagwörter: PPG signal quality, foundation model, physiological data, Photoplethysmography, Humans, Signal Processing, Computer-Assisted, Neural Networks, Computer

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/29g3g594
https://escholarship.org/content/qt29g3g594/qt29g3g594.pdf

Automated assessment of non-technical skills by heart-rate data

Autoren: Huaulmé, Arnaud Tronchot, Alexandre Thomazeau, Herve et al.

Weitere Verfasser: Huaulmé, Arnaud Tronchot, Alexandre Thomazeau, Herve et al.

Quelle: International Journal of Computer Assisted Radiology and Surgery. 20:561-568

Schlagwörter: [SDV.IB] Life Sciences [q-bio]/Bioengineering, physiological data, Non-technical skill, Heart-rate, Surgical assessment

Dateibeschreibung: application/pdf

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/39495359

Multiscale computational analysis of the steady fluid flow through a lymph node

Autoren: Girelli A. Giantesio G. Musesti A. et al.

Quelle: Biomech Model Mechanobiol

Schlagwörter: Multiscale modelling, Original Paper, Numerical simulations, Physiological data, Hydrodynamics, Humans, Lymph flow, Computer Simulation, Lymph Nodes, Lymph, Models, Biological

Dateibeschreibung: application/pdf

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/39320689
https://hdl.handle.net/10281/528603
https://doi.org/10.1007/s10237-024-01879-7
https://hdl.handle.net/10807/299997
https://doi.org/10.1007/s10237-024-01879-7

A quasilinear hyperbolic one-dimensional model of the lymph flow through a lymphangion with valve dynamics and a contractile wall

Autoren: Girelli, Alberto

Quelle: Computer Methods in Biomechanics and Biomedical Engineering. :1-16

Schlagwörter: numerical simulations, valves, physiological data, quasilinear hyperbolic systems, Lymphangion

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/39262168
https://hdl.handle.net/10281/528602
https://doi.org/10.1080/10255842.2024.2399769
https://hdl.handle.net/10807/314460
https://doi.org/10.1080/10255842.2024.2399769

Methodology of collection, recording and markup of biophysical multimodal data in the study of human psychoemotional states

Autoren: Shusharina, Natalia Nikolaevna

Quelle: Известия Саратовского университета. Новая серия Серия: Физика, Vol 24, Iss 3, Pp 239-249 (2024)

Schlagwörter: multimodal data, synchronization of multichannel physiological data, depression diagnosis, non-invasive electroencephalogram, biophysics, biomedical signals, Physics, QC1-999

Zugangs-URL: https://doaj.org/article/8704459c40834046bc046e579716bea4

Kinaesthetic empathy through the lens of the cinematographer: physiological and phenomenological alignments in the act of creation

Autoren: William Primett Ksenia Mukhina Mehmet Burak Yilmaz et al.

Quelle: Frontiers in Neuroscience, Vol 19 (2025)

Schlagwörter: affective computing, enactive simulation, physiological data, camera movements, cinematographer's embodiment, kinaesthetic empathy, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571

Dateibeschreibung: electronic resource

Relation: https://www.frontiersin.org/articles/10.3389/fnins.2025.1613485/full; https://doaj.org/toc/1662-453X

Zugangs-URL: https://doaj.org/article/fecb420614314e3dac1f16d0df3975c0

Breaking the bias: integrating physiological and self-reported data to improve UX researchers' accuracy and empathy

Autoren: Pascal Snow Alejandra Ruiz-Segura Pierre-Majorique Léger et al.

Quelle: Computers in Human Behavior Reports, Vol 19, Iss , Pp 100723- (2025)

Schlagwörter: Usability testing, Physiological data, Self-reported measures, Empathy in design, UX researche, Multimethod approaches, Electronic computers. Computer science, QA75.5-76.95, Psychology, BF1-990

Dateibeschreibung: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S2451958825001381; https://doaj.org/toc/2451-9588

Zugangs-URL: https://doaj.org/article/8062d6ab26344c16a5b4577ac17952ee

Building Digital Twins for Elderly Care: An End-to-End Framework From Data Acquisition to Modeling

Autoren: Ziaullah Momand Pornchai Mongkolnam Jonathan H. Chan et al.

Quelle: IEEE Access, Vol 13, Pp 169415-169445 (2025)

Schlagwörter: Elderly digital twin, human digital twins, personalized healthcare, physiological data integration, predictive models, Electrical engineering. Electronics. Nuclear engineering, TK1-9971

Dateibeschreibung: electronic resource

Relation: https://ieeexplore.ieee.org/document/11153809/; https://doaj.org/toc/2169-3536

Zugangs-URL: https://doaj.org/article/5ca5851b2b1e48f88a498beb7dd37dc1

Applications of Machine Learning in Assessing Cognitive Load of Uncrewed Aerial System Operators and in Enhancing Training: A Systematic Review

Autoren: Qianchu Li Oleksandra Molloy Heba El-Fiqi et al.

Quelle: Drones, Vol 9, Iss 11, p 760 (2025)

Schlagwörter: cognitive load, uncrewed aerial systems, machine learning, artificial intelligence, adaptive training, physiological data, Motor vehicles. Aeronautics. Astronautics, TL1-4050

Dateibeschreibung: electronic resource

Relation: https://www.mdpi.com/2504-446X/9/11/760; https://doaj.org/toc/2504-446X

Zugangs-URL: https://doaj.org/article/12d26a639f8b4b488d3eb5047c9da686

Enhancing Workplace Well-being: Integrating Physiological Data into Aromatherapy through Calm Technology: Integrating Physiological Data into Aromatherapy through Calm Technology

Autoren: Qiurui Wang Caihong He Jun Hu

Quelle: Proceedings of the Eleventh International Symposium of Chinese CHI. :455-460

Schlagwörter: Aromatherapy, Physiological data, Calm technology, Stress

Zugangs-URL: https://research.tue.nl/en/publications/76e8303e-f30e-4bc0-b0ac-1e3efabc14c7
https://doi.org/10.1145/3629606.3629653

Editorial: Exploring the emotional landscape: cutting-edge technologies for emotion assessment and elicitation

Autoren: Castiblanco Jimenez, Ivonne Angelica Marcolin, Federica Vezzetti, Enrico et al.

Quelle: Front Psychol
Frontiers in Psychology, Vol 15 (2025)

Schlagwörter: neuroscience, biometrics, physiological data, affective computing, affective elicitation, augmented/virtual reality, emotion assessment, human-computer interaction, Psychology, BF1-990

Dateibeschreibung: application/pdf

Zugangs-URL: https://doaj.org/article/f1633c2e175542d5b214df41c1fdf2c9

Reshaping the healthcare world by AI-integrated wearable sensors following COVID-19

Autoren: Khan, B. Talha Khalid, R. Ul Wara, K. et al.

Quelle: Chemical Engineering Journal. 505

Schlagwörter: Advancements, Artificial Intelligence, COVID-19, Healthcare, Wearable sensors, Electronic health record, Risk analysis, Advancement, Early warning, Health issues, Health parameters, Physiological data, Prospectives, Risk factors, Technological breakthroughs, Wearable devices

Dateibeschreibung: print

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-69837

A novel framework for the assessment of public-transport drivers' well-being and satisfaction based on physiological data

Autoren: Guy Wachtel Yuval Hadas

Quelle: Journal of Public Transportation, Vol 27, Iss, Pp 100129-(2025)

Schlagwörter: Transportation engineering, Discrete choice, TA1001-1280, Machine learning, Physiological data, Satisfaction, Bus driver, Transportation and communications, HE1-9990

Zugangs-URL: https://doaj.org/article/c87fc1f19b7b4a3f938bf13b5bcbe411

Physiological Data for User Experience and Quality of Experience: A Systematic Review (2018–2022)

Autoren: Aleph Campos da Silveira Mariane Lima de Souza Gheorghita Ghinea et al.

Quelle: International Journal of Human–Computer Interaction. 41:664-693

Schlagwörter: physiological data, user experience, 05 social sciences, 0202 electrical engineering, electronic engineering, information engineering, biosignals, 0501 psychology and cognitive sciences, quality of experience, 02 engineering and technology

Dateibeschreibung: Print-Electronic

Zugangs-URL: https://bura.brunel.ac.uk/handle/2438/28555

Predicting stress levels using physiological data: Real-time stress prediction models utilizing wearable devices

Autoren: Evgenia Lazarou Themis P. Exarchos

Quelle: AIMS Neurosci
AIMS Neuroscience, Vol 11, Iss 2, Pp 76-102 (2024)

Schlagwörter: physiological data, Neurosciences. Biological psychiatry. Neuropsychiatry, Review, 02 engineering and technology, 01 natural sciences, sensor review, 0104 chemical sciences, 3. Good health, wearables, wearable devices, health monitoring, 0202 electrical engineering, electronic engineering, information engineering, physical health, mental health, stress detection, RC321-571

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/38988886
https://doaj.org/article/ddea1745a3ce416cbbdfc2fdc7422b1b