Affective computing seeks to create computational systems that adapt content and resources according to the affective states of the users. However, the detection of the user's affection such as motivation and emotion is challenging especially when an attention problem is present. An approach to convey learning resources to children with learning problems is by means of game-based tools. The first step towards building these ludic experiences is to identify the skills and limitations of potential users. In this work we describe a case based study carried out to observe and get understanding of the level of attention, cognition and memory of children with ADHD (Attention Deficit Hyperactivity Disorder). Fifteen children were invited to play physical and digital versions of the Stroop and Flanker tests as well as memory-based games. The interaction with KAPEAN is allowed with both a mouse and a hand gestures recognition device. To collect data from the user's experiences the system integrates a webcam, a Microsoft Kinect device, a video camera, and an Emotiv EEG headset. Data was analyzed offline in order to study which affective states are present while children with ADHD played with KAPEAN.