## 2 The Biofeedback Device and Application  
Taking into account the dynamics of the anxiety provided by biofeedback during academic examinations, the present study attempted to initially investigate the deployment of a cost-effective biofeedback system that provides anxiety awareness during online examination activities. This section briefly presents this device. The design of the biofeedback device was based on an analysis and modeling of the users, and on the relevant activities and suitable usage scenarios as well. Next, we proceeded with an application of the biofeedback tool by creating a prototype version and evaluating it. The biofeedback device (Figure 1a) was used to collect, identify, and utilize biosignals, which were the result of physiological reactions to stressful situations, such as skin sweating (GSR), heart rate (HR), and skin temperature (SKT). In our effort to construct a convenient device, we embedded the skin temperature (Figure 1b) and GSR (Figure 1c) sensors on the surface of a bracelet. We also used a heart rate sensor in the form of a clip, which we attached to the individual's ear lobe (Figure 1d). The clip was part of the Grove ear clip kit, which collects photoplethysmographic (PPG) signals and calculates the values of the interbeat interval (IBI) time series, which result in heart rate values. Figure 1e depicts the user wearing the heart rate sensor. Figure 1f depicts the user wearing the bracelet with the skin temperature and GSR sensor. During this study, the collected raw biosignals are first normalized and then filtered. A low pass filter is applied to the PPG signal. In addition, low pass and moving average filters are applied to the GSR and skin temperature signals in order to remove the high frequency components. The resulting values of the GSR and SKT signals and the calculated heart rate (HR) are added to the biosignal vectors, which are transferred to the biofeedback application (Figure 2). Figure 1: The biofeedback device. (**a**) Device, (**b**) Skin temperature, (**c**) GSR, (**d**) Heart rate ear clip, (**e**) User connected to heart rate ear clip, (**f**) user wearing bracelet with skin temperature and GSR sensor, (**g**) USB cable. The heart rate sensor has a range of measures \(\geq\) 30/min. A TMP36 (analog system) is used as a skin temperature sensor which is sufficiently accurate, affordable, easy to use, and also operates under a broad range of environmental conditions (\(-\)40 to 150 \({}^{\circ}\)C). As the temperature increases, the voltage across a diode also increases at a known rate. This sensor has \(\pm\)2 \({}^{\circ}\)C accuracy over temperature and a scale factor of 10 mV/\({}^{\circ}\)C. The resolution of the Arduino board is 4.9 mv. The measurement sampling rate is 10 Hz. Both the bracelet and the ear clip are connected to the main body of the system, which consists of an Arduino board and a separate processing board for the heart rate sensor. The whole system costs approximately 100 Euros, which is quite low compared to other similar, well-known systems. All measurements took place at a normal environmental temperature, ranging from 20 \({}^{\circ}\)C to 25 \({}^{\circ}\)C. The biofeedback tool (Figure 1) uses the Arduino platform as an analogue to digital converter; it is connected to a computer through a USB cable (Figure 1g) or via a Bluetooth connection. This device collaborates with dedicated software (biofeedback application). This application classifies real-time biosignals, using the Gaussian regression algorithm [34], to human anxiety levels. The real-time raw biosignals and the resulting anxiety level are displayed on the screen. Biosignal values and anxiety levels are stored in an online database for record-keeping purposes (Figure 2). Before the case study activities take place, the regression algorithm is trained for every user. Then every derived model is used to determine the specific participant's anxiety level during the activities, on the fly.