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Symptoms of Attention Deficit Hyperactivity Disorder (ADHD) include excessive activity, difficulty sustaining attention, and inability to act in a reflective manner. Early diagnosis and treatment of ADHD is key but may be influenced by the observation and communication skills of caregivers, and the experience of the medical professional. Attempts to obtain additional measures to support the medical diagnosis, such as reaction time when performing a task, can be found in the literature. We propose an information recording system that allows to study in detail the behavior shown by children already diagnosed with ADHD during a car driving video game. We continuously record the participants' activity throughout the task and calculate the error committed. Studying the trajectory graphs, some children showed uniform patterns, others lost attention from one point onwards, and others alternated attention/inattention intervals. Results show a dependence between the age of the children and their performance. Moreover, by analyzing the positions by age over time using clustering, we show that it is possible to classify children according to their performance. Future studies will examine whether this detailed information about each child's performance pattern can be used to fine-tune treatment.

In the last few years, several computerized tasks have been developed to increase the objectivity of the diagnosis of attention-deficit hyperactivity disorder (ADHD). This article proposes the "running raccoon" video game to assess the severity of inattention in patients diagnosed with ADHD. Unlike existing tests, the proposed tool is a genuine video game in which the patient must make a raccoon avatar jump to avoid falling into different gaps. The distance to the gap is recorded for each jump. To evaluate the proposed game, an experiment was conducted in which 32 children diagnosed with ADHD participated. For each participant, the median and interquartile range of these distances were calculated, along with the number of omissions. Experimental results showed a significant correlation between the participants' inattention (measured by the Attention-Deficit/Hyperactivity Disorder Symptoms and Normal Behavior rating scale (SWAN) inattention subscale) with each of these three measures. In addition to its accuracy, other benefits are its short duration and the possibility of being run on both standard computers and mobile devices. These characteristics facilitate its acceptance in clinical environments or even its telematic use. The obtained results, together with the characteristics of the video game, make it an excellent tool to support clinicians in the diagnosis of ADHD.