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Cognitive Load Monitoring with Wearables — Lessons Learned from a Machine Learning Challenge

Martin Gjoreski, Bhargavi Mahesh, Tine Kolenik, Jens Uwe-Garbas, Dominik Seuss, Hristijan Gjoreski, Mitja Lustrek, Matjaz Gams, Veljko Pejovic
2021 IEEE Access  
A systematic comparison of preprocessing techniques, classification algorithms, and implementation techniques is presented.  ...  To bring consensus on methods for cognitive load monitoring, a machine learning challenge is organized.  ...  Her research interests include applications of machine learning algorithms in areas, including multimodal human stress detection and digital sensory perception.  ... 
doi:10.1109/access.2021.3093216 fatcat:wu3ssydwibforpeeuuasw4h3fa

Identifying the Optimal Features in Multimodal Deception Detection

Amin Derakhshan, Mohammad Mikaeili, Tom Gedeon, Ali Motie Nasrabadi
2020 Multimodal Technologies and Interaction  
By employing six statistical features, four feature reduction techniques and three classifiers, we attempted to identify the ROIs which are mostly associated with activation of the sympathetic nervous  ...  Our experimental results show that perinasal and cheek areas have greater discriminatory power in comparison with other ROIs on the face.  ...  Acknowledgments: I would like to acknowledge the valuable help of Ying-Hsang Liu, Research Fellow at the ANU Research School of Computer Science for constructive comments on my paper.  ... 
doi:10.3390/mti4020025 fatcat:dis4qbczczdoxijizlsxrkrhcm

Revealing Psychophysiology and Emotions through Thermal Infrared Imaging

Arcangelo Merla
2014 Proceedings of the International Conference on Physiological Computing Systems  
Thermal infrared imaging has been proposed as a tool for the non-invasive and contact-less evaluation of vital signs, psychophysiological responses and states.  ...  Therefore, the state of the art of thermal infrared imaging in computational physiology and psychophysiology is discussed in order to provide insights about its potentialities and limits for human-robot  ...  ACKNOWLEDGEMENTS Figures 2, 3 , 4, 6 have been adapted from previous papers of the author respecting the copyright rights for their publication in the present form.  ... 
doi:10.5220/0004900803680377 dblp:conf/phycs/Merla14 fatcat:jf5pbtgbinepdmgszdp2v7c3ku

Computational Psychometrics Using Psychophysiological Measures for the Assessment of Acute Mental Stress

Pietro Cipresso, Desirée Colombo, Giuseppe Riva
2019 Sensors  
They could represent the first step in developing complex platforms for the automatic detection of mental stress, which could improve the treatment.  ...  The goal of this study was to provide reliable quantitative analyses of psycho-physiological measures during acute mental stress.  ...  This aspect poses new challenges for the automatic recognition of stress using machine learning algorithms, which can be implemented in advanced platforms for the recognition of mental stress.  ... 
doi:10.3390/s19040781 fatcat:kxwj3n2zd5ekrhyspd46z6cg7y

Psychophysiological Indicators for Modeling User Experience in Interactive Digital Entertainment

Martin Čertický, Michal Čertický, Peter Sinčák, Gergely Magyar, Ján Vaščák, Filippo Cavallo
2019 Sensors  
Multiple psychophysiological measures, such as heart rate, electrodermal activity, and respiratory activity, have been used in combination with self-reporting to prepare training sets for machine learning  ...  Afterwards, we trained and compared the results of four different machine learning models, out of which the best one produced ∼96% accuracy.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s19050989 fatcat:ktsgksbsivbovpo7kno64oftjy

A short review and primer on the use of human voice in human computer interaction applications [article]

Kristian Lukander
2016 arXiv   pre-print
Working in this emerging field requires comprehension of an array of physiological signals and analysis techniques.  ...  Several types of factors affect speech, ranging from emotions to cognitive load and pathological conditions, providing a promising non-intrusive source for online understanding of context and psychophysiological  ...  Instead of direct comparisons involving individual features or combinations of them, modern approaches tend to use machine learning methods to improve detection rates [Zhou et al., 2001] .  ... 
arXiv:1609.07343v1 fatcat:eiksr6jfsrgq7lgoues4xecme4


Miroslav KELEMEN, Matej ANTOŠKO, Stanislav SZABO, Luboš SOCHA, Jaroslav JEVČÁK, Ladislav CHOMA, Alica TOBISOVÁ
2019 Transport Problems  
The main aim of the experiment, the presurvey, is to verify and prepare a final version of sets of test tasks in the field of measuring the psychophysiological performance of the candidates for aviation  ...  personnel and to complete the creation of a technical device and the software tool for these processes.  ...  APVV-17-0167 "Application of the Self-regulatory techniques for the Flight Crew Preparation".  ... 
doi:10.20858/tp.2019.14.3.13 fatcat:ohs22ubq75co5aswqqygoi3zga

Thermal Infrared Imaging-Based Computational Psychophysiology for Psychometrics

Daniela Cardone, Paola Pinti, Arcangelo Merla
2015 Computational and Mathematical Methods in Medicine  
Thermal infrared imaging has been proposed as a potential system for the computational assessment of human autonomic nervous activity and psychophysiological states in a contactless and noninvasive way  ...  The obtained physiological information could then be used to draw inferences about a variety of psychophysiological or affective states, as proved by the increasing number of psychophysiological studies  ...  Conflict of Interests The authors declare that there is no conflict of interests regarding the publication of this paper. Computational and Mathematical Methods in Medicine  ... 
doi:10.1155/2015/984353 pmid:26339284 pmcid:PMC4538766 fatcat:d3bnqwnu4vg3ji46sg6r3pxxhm

Towards a Resilience to Stress Index Based on Physiological Response: A Machine Learning Approach

Ramon E. Diaz-Ramos, Daniela A. Gomez-Cravioto, Luis A. Trejo, Carlos Figueroa López, Miguel Angel Medina-Pérez
2021 Sensors  
To compute the index, we used non-supervised machine learning methods to calculate the inter-cluster distances, specifically using the following four methods: Euclidean Distance of PCA, Mahalanobis Distance  ...  The benefits of having a metric that measures resilience to stress are multiple; for instance, to the extent that individuals can track their resilience to stress, they can improve their everyday life.  ...  Acknowledgments: The authors acknowledge the support of the Department of Psychology of Tecnológico de Monterrey for developing the psychophysiological mental stress test, especially to Fresia Hernández  ... 
doi:10.3390/s21248293 pmid:34960385 pmcid:PMC8705801 fatcat:p5riv2etfncnjd46lhbaiytpw4

Towards Classifying Cognitive Performance by Sensing Electrodermal Activity in Children with Specific Learning Disorders

Carolina Rico-Olarte, Diego M. Lspez, Linda Becker, Bjoern Eskofier
2020 IEEE Access  
Electrodermal activity (EDA) signals were collected, processed, and analyzed through a machine learning approach.  ...  The presented results evidence that psychophysiological measures could allow for a highly objective follow-up for patients.  ...  To the Ministry of Science, Technology, and Innovation (MinCiencias) and the call 785 from 2017 for funding the doctoral studies of Carolina Rico-Olarte.  ... 
doi:10.1109/access.2020.3033769 fatcat:h3pty6ocyjddpgpfugys6wkb5a

Psychophysiological methods for the diagnostics of human functional states: New approaches and perspectives

Alexsander M. Chernorizov, Sergey A. Isaychev, Yury P. Zinchenko, Vladimir V. Galatenko, Irina A. Znamenskaya, Petr N. Zakharov, Andrej V. Khakhalin, Olga N. Gradoboeva
2016 Psychology in Russia: State of Art  
Mathematical algorithms that provide a partition of FS indicators into different FS types are based on various methods of machine learning.  ...  We propose the vector approach for construction of complex estimations of the human FSes.  ...  This method is the most promising and rapidly developing technique for the distant detection of emotions.  ... 
doi:10.11621/pir.2016.0403 fatcat:iprbdoz72vgtfgcw2jgfgifzsq

A Review on Mental Stress Detection using Wearable Sensors and Machine Learning Techniques

Shruti Gedam, Sanchita Paul
2021 IEEE Access  
In this paper, a comprehensive review has been presented, which focuses on stress detection using wearable sensors and applied machine learning techniques.  ...  Also, a multimodal stress detection system using a wearable sensor-based deep learning technique has been proposed at the end.  ...  Brief description of several existing machine learning techniques Machine Learning Technique Advantages Disadvantages Applications SVM TABLE 8 . 8 Overview of stress detection using wearable  ... 
doi:10.1109/access.2021.3085502 fatcat:m5spbtol5ve5rkf4jjdincn6nq

Semi-supervised Deep Learning for Stress Prediction: A Review and Novel Solutions

Mazin Alshamrani
2021 International Journal of Advanced Computer Science and Applications  
This research introduces a novel self-supervised deep learning model for stress detection using an intelligent solution that detects the stress state using the physiological parameters.  ...  It is the first attempt of using contrastive learning for the stress prediction tasks.  ...  In [23] deep learning techniques for real-time stress and affect detection was examined.  ... 
doi:10.14569/ijacsa.2021.0120949 fatcat:epl27mblzzfgtpvq3na53ph3y4

A Survey on Psycho-Physiological Analysis & Measurement Methods in Multimodal Systems

Muhammad Zeeshan Baig, Manolya Kavakli
2019 Multimodal Technologies and Interaction  
Researchers use psychophysiological feedback devices such as skin conductance (SC), Electroencephalography (EEG) and Electrocardiography (ECG) to detect the affective states of the users during task performance  ...  Psycho-physiological feedback has been successful in detection of the cognitive states of users in human-computer interaction (HCI).  ...  Acknowledgments: We thank Charles Liu for his valued comments on the manuscript. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/mti3020037 fatcat:ljpz7qpnpndkrm5bgo7g7qacay

Predicting Navigation Performance with Psychophysiological Responses to Threat in a Virtual Environment [chapter]

Christopher G. Courtney, Michael E. Dawson, Albert A. Rizzo, Brian J. Arizmendi, Thomas D. Parsons
2013 Lecture Notes in Computer Science  
Comparisons of predictive abilities between the developed models were performed to determine optimal model parameters.  ...  Additionally, participants were subjected to varying levels of environmental threat during the route-learning phase of the experiment to assess the impact of threat on consolidating route and survey knowledge  ...  These techniques are often used for assessment and classification of nonlinear data (see [19] ).  ... 
doi:10.1007/978-3-642-39405-8_16 fatcat:wxs5yzlyufhkpb7wmtco37xx74
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