Problem Statement

The e-Health Sensor Platform is presented as a very good option for research and study of human emotions but early tests have shown that the platform sometimes is unstable and not very reliable.

The objective of this thesis is to test the platform, modify and develop the necessary software to make it more stable and reliable for future studies related to Affective Computing specially oriented in the field of learning but not restricted only to this area.

The work includes testing the e-Health Sensor Platform with different hardware architectures to define which presents the best performance and obtaining more than 2 or more biomedical signals simultaneously.