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Speech production under stress for machine learning: multimodal dataset of 79 cases and 8 signals
(Springer Nature, 2024-11-12) Pešán, Jan; Juřík, Vojtěch; Růžičková, Alexandra; Svoboda, Vojtěch; Janoušek, Oto; Němcová, Andrea; Bojanovská, Hana; Aldabaghová, Jasmína; Kyslík, Filip; Vodičková, Kateřina; Sodomová, Adéla; Bartys, Patrik; Chudý, Peter; Černocký, Jan
Early identification of cognitive or physical overload is critical in fields where human decision making matters when preventing threats to safety and property. Pilots, drivers, surgeons, and operators of nuclear plants are among those affected by this challenge, as acute stress can impair their cognition. In this context, the significance of paralinguistic automatic speech processing increases for early stress detection. The intensity, intonation, and cadence of an utterance are examples of paralinguistic traits that determine the meaning of a sentence and are often lost in the verbatim transcript. To address this issue, tools are being developed to recognize paralinguistic traits effectively. However, a data bottleneck still exists in the training of paralinguistic speech traits, and the lack of high-quality reference data for the training of artificial systems persists. Regarding this, we present an original empirical dataset collected using the BESST experimental protocol for capturing speech signals under induced stress. With this data, our aim is to promote the development of pre-emptive intervention systems based on stress estimation from speech.
Subjective visual sensitivity in neurotypical adults: insights from a magnetic resonance spectroscopy study
(FRONTIERS MEDIA SA, 2024-09-25) Jurkovičová, Lenka; Palenik, Julie; Kudlička, Petr; Pezlar, Lenka; Růžičková, Alexandra; Juřík, Vojtěch; Marecek, Radek; Roman, Robert; Braithwaite, Jason J.; Sandberg, Kristian; Near, Jamie; Brázdil, Milan
Introduction Altered subjective visual sensitivity manifests as feelings of discomfort or overload elicited by intense and irritative visual stimuli. This can result in a host of visual aberrations including visual distortions, elementary visual hallucinations and visceral responses like dizziness and nausea, collectively referred to as "pattern glare." Current knowledge of the underlying neural mechanisms has focused on overall excitability of the visual cortex, but the individual contribution of excitatory and inhibitory systems has not yet been quantified.Methods In this study, we focus on the role of glutamate and gamma-aminobutyric acid (GABA) as potential mediators of individual differences in subjective visual sensitivity, measured by a computerized Pattern Glare Test-a series of monochromatic square-wave gratings with three different spatial frequencies, while controlling for psychological variables related to sensory sensitivity with multiple questionnaires. Resting neurotransmitter concentrations in primary visual cortex (V1) and right anterior insula were studied in 160 healthy participants using magnetic resonance spectroscopy.Results Data showed significant differences in the perception of visual distortions (VD) and comfort scores between men and women, with women generally reporting more VD, and therefore the modulatory effect of sex was considered in a further examination. A general linear model analysis showed a negative effect of occipital glutamate on a number of reported visual distortions, but also a significant role of several background psychological traits. When assessing comfort scores in women, an important intervening variable was the menstrual cycle.Discussion Our findings do not support that baseline neurotransmitter levels have a significant role in overreactivity to aversive stimuli in neurotypical population. However, we demonstrated that biological sex can have a significant impact on subjective responses. Based on this additional finding, we suggest that future studies investigate aversive visual stimuli while examining the role of biological sex.
Building Execution Plan as an effective document for Building Information Modelling
(Elsevier B.V, 2024-07-29) Sudakova, Katsiaryna; Remeš, Josef; Tichá, Alena
The use of Building Information Modelling (BIM) technology is recently becoming an increasingly influential factor in the successful completion of construction projects. Providing a wide range of technical enhancements to the design process (for example software for 3D modelling), BIM also offers a wide range of tools for managing construction projects. The goal of Building Information Modelling is to eliminate gaps in data transmission between different stages of the life cycle of a construction project. In this context, BEP, or BIM Execution Plan, is an essential document in the BIM concept. It functions as a tool for managing a project, both from the human resources perspective, such as meeting deadlines, and from the perspective of preserving and transferring graphical and non-graphical data of the project. Furthermore, it provides a detailed plan for building design, construction, and facility management, helping to ensure that all stakeholders are in line with the project’s goals. This article examines BEP as it evolves throughout various life cycle stages, from initial design and planning to construction and final delivery, exploring its potential in facility management.
Virtual reality exposure effect in acrophobia: psychological and physiological evidence from a single experimental session
(Springer Nature, 2024-07-15) Varšová, Kristína; Szitás, Dagmar; Janoušek, Oto; Jurkovičová, Lenka; Bartošová, Kateřina; Juřík, Vojtěch
In recent years, virtual reality (VR) has gained attention from researchers in diverse fields, particularly in therapy of phobias. Currently, virtual reality exposure therapy therapy (VRET) is considered a promising cognitive-behavioral therapy technique. However, specific psychological and physiological responses of VR users to virtual exposure in such a context are still only vaguely explored. In this experimental study, we mapped VR exposure in a height environment in people with a moderate fear of heights–acrophobia. Thirty-six participants were divided into experimental and control groups–with and without psychological guidance during exposure. Participants' subjective level of anxiety was examined, and objective physiological response was captured via heart rate variability (HRV) measurement. Psychological assessments recorded an anticipated rise in participant anxiety following exposure to height; nevertheless, no distinctions were observed in self-reported anxiety concerning psychological guidance. Notably, objective physiological measures revealed that VR exposure prompts physiological responses akin to real-world scenarios. Moreover, based on the analysis of heart rate variability, participants who received psychological guidance were identified as better at compensating for anxiety compared to those without such support. These findings support VRET as a promising tool for psychotherapy and advocate for psychological guidance as beneficial in reducing anxiety and managing stress during exposure. The results may help improve our understanding of anxiety during exposure to phobic stimuli.
Calibration of pedestrian ingress model based on CCTV surveillance data using machine learning methods
(Public Library of Science, 2024-01-18) Floriánová, Martina; Uhlík, Ondřej; Apeltauer, Tomáš
Machine learning methods and agent-based models enable the optimization of the operation of high capacity facilities. In this paper, we propose a method for automatically extracting and cleaning pedestrian traffic detector data for subsequent calibration of the ingress pedestrian model. The data was obtained from the waiting room traffic of a vaccination center. Walking speed distribution, the number of stops, the distribution of waiting times, and the locations of waiting points were extracted. Of the 9 machine learning algorithms, the random forest model achieved the highest accuracy in classifying valid data and noise. The proposed microscopic calibration allows for more accurate capacity assessment testing, procedural changes testing, and geometric modifications testing in parts of the facility adjacent to the calibrated parts. The results show that the proposed method achieves state-of-the-art performance on a violent-flows dataset. The proposed method has the potential to significantly improve the accuracy and efficiency of input model predictions and optimize the operation of high-capacity facilities.

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