Meditation Detection Using Sensors from Wearable Devices
Meditation is a practice that aims at self-inducing a state of calmed rest. In this work, we analyze physiological signals collected with wearable sensors to observe if meditation has a noticeable effect on the human body response and if this effect is inversely related to stress and can be detected using the same biosignals and similar features and methods. Our work is based on the extraction of statistical and physiological features and extends the models found in the literature by extracting 30 additional features related to heart rate variability. The results show that using wrist wearable devices, meditation periods can be distinguished from spontaneous rest with an accuracy of up to 86% accuracy.