  This paper considers the adaptation of the e-coaching concept at times of
emergencies and disasters, through aiding the e-coaching with intelligent tools
for monitoring humans' affective state. The states such as anxiety, panic,
avoidance, and stress, if properly detected, can be mitigated using the
e-coaching tactic and strategy. In this work, we focus on a stress monitoring
assistant tool developed on machine learning techniques. We provide the results
of an experimental study using the proposed method.
