# Effect of Exposure Time on Thermal Behaviour: A Psychophysiological Approach
## 4 Data Analysis and Findings
### Physiological Response  
This study focuses on the investigation of EDA activity in different ambient temperature environments. The raw EDA signals had a sampling frequency of 4 Hz and were analysed using the Neurokit2 library for Python [49], i.e., filtered, cleaned, and then divided into phasic (SCR) and tonic (SCL) activities, while the SCR peaks were identified. Below (Figure 6) are the graphs illustrating The EDA levels of each test subject from different days, against the temperature that the subjects were exposed to at the respective time. As mentioned previously, the main part of the data analyses focused on tonic component. The 25 \({}^{\circ}\)C day was accepted as the baseline for all participants. As expected, generally the EDA activity is at its minimum for all--however a comparison between Participant 3 and others clearly show the difficulty in making inter-person analysis with absolute numbers. As a clear example, while Participant 3 had a tonic range of 0-7.5 \(\upmu\)S during the 25 \({}^{\circ}\)C day, this is the maximum range ever observed for Participant 1, including the  
Figure 5: Clo values of the participants in respective days. 30 \({}^{\circ}\)C day (see Figure 7). This has been found previously in literature as \"within-subjects correlations being much higher than those between-subjects\" [36, 37, 48]. The tonic EDA is a slow varying signal over time, thus for each participant/session, a sliding temporal window of \(\Delta\)t = 1 min and step of 1 min was used after carefully checking that does not affect the information and the signals' variability. As EDA presents inter-subject variability, it is appropriate to take into account each participant's personalized EDA tonic baseline (grand average of 25 \({}^{\circ}\)C). The differential to baseline EDA tonic values were extracted generating a common reference for EDA across subjects providing data normalization. The normalized data elicited statistically significant changes in normalized tonic EDA over temperature (Kruskal-Wallis H test, H(4) = 5335.45, \(p\) < 0.001). Pairwise post-hoc analysis with Bonferroni correction on multiple comparisons revealed statistically significant differences in median tonic EDA values between 25 \({}^{\circ}\)C and 28 \({}^{\circ}\)C (\(p\) < 0.001), 25 \({}^{\circ}\)C and 29 \({}^{\circ}\)C (\(p\) < 0.001) and 25 \({}^{\circ}\)C and 30 \({}^{\circ}\)C (\(p\) < 0.001). The results are presented in Figure 8.  
Figure 6: EDA tonic and phasic levels of each participant throughout the day. Each column represents different days (from top to bottom, 25 \({}^{\circ}\)C, 27 \({}^{\circ}\)C, 28 \({}^{\circ}\)C, 29 \({}^{\circ}\)C and 30 \({}^{\circ}\)C) for each Participant, respectively. The black lines show the temperature that the participant was exposed at the given time; i.e., one can assume that the higher temperatures are when they are in the Sense Lab, the lower ones are when they take a break in the cold room (Clima Lab) and the lowest ones are when they step outside. This also gives information about their break habits. It can be observed from Figure 8, that tonic EDA presents a statistically significant increase after the 28 \({}^{\circ}\)C and above this temperature (i.e., 29 \({}^{\circ}\)C and 30 \({}^{\circ}\)C). Although there are several studies that compare EDA levels under different temperature settings, to the authors' best knowledge, there are no comparable datasets that collected EDA data under the same temperatures and temperature steps. In the occupational health, psychophysiology or biomedical studies where the use of EDA has been traditionally more common, either the ambient temperature was kept to the thermoneutral ranges (22-26 \({}^{\circ}\)C depending on the study [37]) or where the impact of ambient temperature was studied, bigger steps of temperature changes were tested [50,51]. Therefore, the observed finding could not be compared to the existing literature.