## 3 Materials and Methods
The FaceReader index of agreement is 0.69 for FACS accuracy [45]. Similar findings have been described in other studies on the reliability and accuracy of FaceReader, as well as their opinions of the device's maker, Noldus Information Technology. The FLIR A35 SC infrared camera has a thermal sensitivity of 0.05 \({}^{\circ}\)C and an accuracy of 2% (FLIR). The manufacturer calibrated and checked the camera, and the calibration certificate attested to the accuracy of the measurements. The metrological verification of thermographic cameras is performed once a year to make sure the error rate stays within the limits given by the manufacturer. Self-reports were also collected from the participants to compare them with those elicited by viewing the sample data. The basis for this software is AI tools that make it possible to detect human reactions and subjective emotions based on input videos or even images. The outputs of the software are usually a series of quantitative data and charts that can be used to interpret underlying emotional states. These data were collected every second during the experiment. The study used these techniques, as well as XeThru technology [64] and a model-based face modelling method--the Active Appearance Model. This model describes the location of 500 facial key points and the facial texture of the specific area entangled by these points to synthesise an artificial face model. The Facial Action Coding System, the Method of Automatic Facial Expression Recognition, and the Continuous Calibration and Participant methods found in the FaceReader manual [65] were also used. Certain requirements are applicable to each set of the equipment:  
* Internet speed should be at least 600 MB/s. The download speed should be 50 GB/s. A static external IP address is also required. * Enabled network connection is required. * All optimal sites being analysed should be identified. Depasonalised physiological and emotional states of the participants should be taken from a distance of 50 cm. The emotion model for the renovation project based on the [PERSON]'s circumplex model is presented in Figure 2. Emotions are triggered by many factors, such as judging an unexpected situation, making a decision, talking about past emotional experiences or observing another person's emotional reactions. [PERSON] and [PERSON] [66] proposed the main emotions that are common to all people: happy, sad, angry, fear, surprise and disgust. Physiological arousal and the accompanying cognitions related to cues or situational determinants interact to create emotional experience. Facial expression plays an important role in reflecting the way emotional states change. When a unique facial expression is recognised as a certain emotion, this expression reveals that person's feelings and provides social information. In addition to the \"neutral\" state, used as a reference, the software in its classification also includes the baseline definitions of each individual state (total N = 6) targeting \"sad\", \"happy\", \"disgusted\", \"fearful\", \"surprised\" and \"angry\". From a practical point of view, the software offers an instant rating of action units (from 0 to 1) related to all emotions that are detected. By quantifying baseline parameters such as arousal, valence, orientation of head, gaze direction, heart rate variability (skin conductance is analysed remotely for that purpose) and a few more personal details of the participants (such as age, sex, beard, whether the person wears glasses) can also provide useful feedback. In addition to the analysis of facial emotions, heart rate variability (HRV) was measured. HRV is a method where the emotional state is assessed by looking at the measurement of how the interval between successive heartbeats changes, known as variability). This interval is called the \"R-R interval\" or \"interbeat interval\" and is measured in milliseconds (see Figure 3). The parasympathetic and sympathetic nervous systems, the two branches of the autonomic nervous system, work in synergy to regulate HRV.