Cognitive stress, also known as mental workload, constitutes a central topic within the field of psychophysiology due to its role in modulating attention, autonomic regulation, and stress reactivity. Furthermore, it bears direct relevance to practical monitoring systems that employ non-invasive sensing techniques. This study investigates whether a multimodal, non-invasive measurement setup can detect systematic physiological differences between Resting periods and short episodes of cognitive load within the same individuals. Additionally, it explores the capacity of such a system to differentiate tasks characterized by varying cognitive demands. A sequential, within-subject protocol was employed, comprising five consecutive phases (rest 1, Stroop, rest 12, subtraction, rest 3), during which five modalities were recorded concurrently: EEG, heart rate (HR), galvanic skin response (GSR), facial surface temperature, and oxygen saturation (SpO₂). Beyond phase-wise inspection of time-series data, an exploratory assessment of similarity across participants was conducted using correlation coefficients. The maximum cross-participant correlations observed were 0.88 (HR), 0.90 (GSR), 0.83 (facial temperature), and 0.77 (SpO₂); however, these correlations were used only as exploratory descriptors of inter-individual similarity and did not imply a significant phase effect. For inferential analysis, phase-wise epoch means were evaluated through one-factor repeated-measures ANOVA. The heart rate exhibited a robust main effect of phase (F(4, 32) = 10.5862, p_GG = 0.01044, ηp² = 0.5696), with higher HR observed during cognitive load epochs (e.g., 77.841 ± 11.777 bpm at rest 1 versus 83.926 ± 14.532 bpm during subtraction). The relatively large standard deviation reflects variability between subjects rather than variability within epochs. Regarding processed baseline-referenced GSR, the omnibus phase effect was not statistically significant under the conservative Greenhouse–Geisser correction; therefore, GSR was interpreted as exploratory in this dataset. Facial temperature and SpO₂ likewise did not show statistically significant omnibus phase effects under Greenhouse–Geisser correction (e.g., SpO₂: p_GG = 0.1209). EEG-derived measures provide supplementary central evidence of task engagement; entropy variations within an approximate dynamic range of 0.2 to 0.8 were observed, and the α/θ ratios demonstrated nearly a twofold distinction between rest and cognitive load epochs across different leads.

The aim of this study was to evaluate the influence of factors determining the state of danger heat stress on the udder and thigh temperature of dairy cows. Heat stress was classified by measuring the temperature–humidity index (THI). Surface temperatures in the areas of interest were measured using infrared thermography (IRT). The correlation coefficient between THI and thigh surface temperatures ranged from 0.67 to 0.87. The correlation coefficient between udder surface temperature and THI was 0.81. The rate of increase in thigh surface temperature ranged from 0.33 to 0.45. The rate of increase in udder surface temperature was 0.64. The results showed that under danger heat stress, the surface temperature of the udder and thigh was strongly affected and the cows’ body showed a strong tendency to cool down.

The main objective of this study is to investigate the influence of cognitive stress (mental workload) on some physiological parameters and reactions of a set of experimental subjects. The aim is to check whether these indicators, observed simultaneously, can distinguish the state of rest from the state of mental tension and whether they can distinguish tasks of different difficulty. An assessment of the state of rest in the study protocol is also performed. The experiments implemented a multimodal, non-invasive BCI for tracking physiological responses during cognitive task performance. Five parallel measured parameters are used: electroencephalography (EEG), heart rate (HR), galvanic skin response (GSR), facial surface temperature, and oxygen saturation (SpO₂). The results show that HR is a fast and reliable marker for detecting psychological load, the normalized phase GSR is good for detecting higher loads, EEG α/θ can be used for central validation, facial temperature is shown to be a slowly changing but reliable context indicator and SpO₂ preservation can be used as a measure of stability.