Prior research suggests and reveals that there is a correlation between human emotional responses and the subjective qualities of digital interactive experiences, using facial analysis done by deep neural networks propose a true non-intrusive way of measuring emotional responses and continuation desire of a player. This thesis proposes a tool to measure emotional responses across eight different emotions and continuation desire in real time of any game. The emotional recognition system achieves an accuracy of 98\% and the continuation desire system achieves 93.3\% accuracy. This forms a strong tool that shows a correlation between emotions and continuation desire, which can be used to evaluate digital interactive experiences, in critical stages of development of said content.