Stress is an escalated psycho-physiological state of the human body emerging in response to a challenging event or a demanding condition and since it is one of the major issues in modern society, there is a growing interest in developing methods that make automatic detection possible. To this end, the adoption of wearable technology coupled with the implementation of machine learning (ML) techniques are emerging as an interesting approach to develop non-invasive stress detection systems. The present work investigates the coupled use of Machine Learning and biosignals collected from wearables in a controlled environment to study the feasibility of non-invasive stress detection systems.