AbstractEmotional intelligence (EI) is a basic concept in psychology that is gaining social importance. According to Goleman, it refers to the ability to be aware of and to handle one’s emotions in varying situations. Current research indicates that EI can be improved through training, leading to an increased awareness of how we can contribute to the emotional management. In this paper, a low-cost ElectroEncephaloGraphy (EEG) and PhotoPlethysmoGraphy (PPG) based proposal is introduced in order to assess the level of emotional intelligence among elderly people during cognitive stimulation sessions. Twenty-five older people , who were baby boomers (people born from 1946 to 1964), were recruited during 2 months, while they participated in a cognitive stimulation program. During those months, these participants were trained in different techniques of emotional management and they learned how to use several low-cost EEG and PPG devices. They were subjected to several emotional stimulation sessions where stress and anxiety scenarios were considered. By using our proposal, different supervised learning algorithms were evaluated in order to allow emotion detection, having the Support Vector Machine (SVM) technique as the one that reached better scores. Later, our solution supports emotional intelligence test and promising outcomes were achieved.