Front-end Analog Pre-Processing for Real Time Psychophysiological Stress Measurements Frederic Angus Biomedical Engineering, Florida International University Miami, Florida 33174, USA and Jing Zhai Electrical and Computer Engineering, Florida International University Miami, Florida 33174, USA and Armando Barreto Biomedical and Electrical and Computer Engineering, Florida International University Miami, Florida 33174, USA ABSTRACT Every day computers become more influential in our daily lives. In an attempt to improve our interaction with computers, the emerging field of Affective Computing strives to provide the necessary mechanisms that will make machines aware of the affective state of their users. This paper explains the challenges in pre-processing psychophysiological signals, including Blood Volume Pulse (BVP) , Galvanic Skin Response (GSR) and Skin Temperature (ST) for the determination of the emotional state of a computer user, particularly, as he/she experiences emotional stress. These signals are appropriate because they are non-invasive, non-obtrusive and their variation under stress is predictable. The Galvanic Skin Response measures the change in electrodermal activity (increase in conductance) as sweat glands are stimulated to produce a hydrate solution. The Blood Volume Pulse waveform reflects modifications in heart rate, stroke volume and peripheral cardiovascular resistance modulated by the sympathetic nervous system. The acral Skin Temperature experiences short term changes that originate from vasomotor activity in the arterioles. The following sections describe the instrumentation setup that has been developed to monitor these three variables as computer users experience varying levels of stress, elicited by the completion of a series of “Stroop Test”. Keywords: Affective Computing, Psycho-physiological, Blood Volume Pulse, Galvanic Skin Response, Skin Temperature, Electrodermal, Sympathetic Nervous System, Stroop Test. INTRODUCTION The role of computers has changed from number crunching tools used by a small group of scientist, to everyday tools that help organize and accomplish daily activities for people in fields as diverse as medicine, engineering, law, transportation, logistics, etc. Computers have revolutionized the way we perform tasks, and the efficiency we achieve in them. This is possible because of the evolution in interactions between humans and computers. At first we could only communicate by means of perforated coded cards. Now we can use the keyboard, mouse, microphones, cameras, and we have sophisticated Graphical User Interfaces that allow people with no knowledge of computer programming to use them for their particular interests. Affective Computing strives to take this interaction to new heights, by providing the necessary input for the computer to react to the emotional state of the computer user. This is a major challenge given the difficulties defining a trustworthy method of classifying and detecting emotions. This paper describes the development of the hardware for data acquisition that would allow determination of the affective state of a computer user. PHYSIOLOGY OF EMOTIONS Galvanic Skin Response (GSR), also known as electrodermal activity (EDA), is very popular in psychophysiological studies since Carl Jung and his students (1907) described it as a mean to enter the “sea of the unconscious” because “every stimulus accompanied by an emotion produced a deviation of the galvanometer” directly proportional to the strength of the emotion aroused. Eccrine sweat glands are intimately involved in EDA because they are concentrated in the palms of the hands and the soles of the feet and respond primarily to “psychic” stimulation, from the Sympathetic Nervous System (SNS), rather than ambient temperature changes. We used the exosomatic method to find the skin conductance, in which a small current is passed through the skin and measured. The cardiovascular system is in charge to keep us alive by maintaining the vital blood flow throughout the body, providing nutrients and oxygen to our cells. The SNS controls this system by shifting the flow in response to exercise, temperature, postural and emotional changes. Blood Volume Pulse (BVP) is the most common measure of vasomotor activity because it reflects the phasic pumping of the heart, the vasodilation of vessels that changes in the amount of acral blood delivered. [1] In our instrumentation setup we measured this variable through finger photoplethysmography, which shines light against the finger and measures how much is reflected to a photo transducer.