Detecting emotions in a learning environment can make the student-learning process more efficient, avoiding stressful situations that might eventually lead to failure, frustation and demotivation. The work presented here describes a perceptive desktop devised to capture the sensations of any person facing learning activities. To this end, we propose a perceptive environment enhanced with capabilities to perform an analysis of electroencephalography, facial expression, eye tracking and particularly a very distinctive indicator of stress as it is the galvanic response of the skin. This work focuses on the galvanic response of the skin, comparing the performance of two devices in the context of the perceptive desktop. One of the devices was very attractive to our environment as it was a mouse that fit very well to our computer-based desktop, equipped with low-cost sensors to detect the galvanic response. The other device is more tedious to place and more expensive but we use it as a ref erence to know if the mouse is accurate. Four people were exposed to an experiment with the two devices connected, and observing the results it can be concluded that there is no correlation between the captures of both devices. Therefore, we could not select the mouse for our environment even though at first it looks like a very promising device.