Evaluating chatbot user experience (UX) through electroencephalography measures: A systematic literature review

Abstract

Brain activity is a biological signal with unique characteristics that can determine important patterns for recording and processing. The electroencephalogram (EEG) is the most used signal because it measures brain electrical activity, offering greater resolution and data accuracy. When associated to brain activities in user-computer interactions, it can provide information that allows analyzing adequacy and user satisfaction. Thus, the objective of this paper is to identify works that specify which information on electroencephalography assessment may be used to compose an analysis of its interactions with conversational systems. The delimited that the research problems are: (1) What information about user experience by electroencephalography can be used to compose an analysis of their interactions with conversational systems? (2) What techniques are used to present user experience information by EEG to individuals? Based on the Systematic Review method, seven studies were identified that examined commercial EEG devices for UX assessment between 2011 and 2022. The current study found that multiple emotional stimuli were used and reported. The most popular technique among researchers is event induced emotional stimulation, in which participants passively perceive emotional stimuli such as images, music and videos to evoke certain emotions.

Keywords

• User experience
• Chatbot
• Virtual assistant
• Conversational agent
• Natural language interface
• Brain-computer interface