*3.3. Methods*

The analysis was performed on the basis of qualitative research and the descriptive statistics. Overall, we created a dataset consisting of 464 days of continuous measurements that included 50 days of self-isolation at home during the Covid-19 pandemic. We used Fitbit Versa (dimensions: 1.98 × 3.98 × 9.00 inches) as a source of biomarkers, which is an advanced smartwatch featuring built-in wrist-based heart rate sensor, sleep tracker, accelerometer, 4 days battery life and Bluetooth wireless interface for Fitbit cloud communication. Data were extracted and analyzed from the Fitbit cloud application using developed Python and Matlab scripts. A quantitative and comparative study analysis was carried out using Python and Matlab.

The research was planned in such a way as to simultaneously compare changes in the measured physiological parameters, because the seasons have a large impact on the variability of human activity, e.g., in summer, human activity increases because it is warmer and there are more opportunities to spend time actively outdoors.

We believe that the comparison of physiological activity during hard lockdown with the same period in the preceding year is very reliable and reflects the real impact of the pandemic on human activity. A similar methodology was published by fitness tracker companies comparing the same periods to avoid confounding variables such as the seasons or holidays [49].
