EMOTION DETECTION AND RECOGNITON FOR CLINICAL AND NEUROMARKETING APPLICATIONS THROUGH GALVANIC SKIN RESPONSE

Patients suffering from various neurological disorders show different emotions when exposed to certain environments, events, or stimuli. Understanding what kind of emotion is shown by a patient helps in the diagnosis and treatment of these patients. In neuromarketing, companies are adopting emotion recognition technologies to understand their customers’ motivations, preferences, and decisions, which will help them improve their product advertisement, product development, pricing, and marketing. Although many techniques have been developed for emotion recognition with a huge amount of success, they can often be said to be complicated and require expensive equipment. In this paper, we developed a desktop application that can detect and recognize participants’ emotions triggered by different experimental or neuromarketing stimuli through galvanic skin response (GSR), which is the aim of this paper. The application uses three different neuromarketing stimuli: an image-based experiment, a video-based experiment, and a web-based experiment. It also comprises other biomarkers for detecting human emotions, namely an eye tracker and facial recognition, which complement the GSR. The processes involved in the acquisition and analysis of the GSR measurement are described in detail in the paper. GSR data was measured using a galvanic skin sensor with its two electrodes wrapped around the index and middle finger of the same hand. Participants were enrolled and subjected to two different web-based experiments, and their data were recorded and analyzed over time. The result of the analysis shows the different frequency levels of participants over time when faced with the stimuli, which indicates the level of emotion of the participant towards a different section of the web experiment over time. This paper also illustrates how using other biomarkers complements GSR within the application. In general, the application shows the participant’s face being captured through a webcam as they browse through the website, and an eye tracker sensor monitors and records different sections of the screen the participant was looking at while the experiment was carried out, while the GSR sensor also measures the skin conductance of the participant.