###### Abstract
Different studies have shown the potential offered by brain-computer interfaces (BCI)-based systems to be used as part of nonpharmacogical treatments in people living with ADHD [17]. In such cases, Plan-It Commander is a BCI video game designed to promote the learning of cognitive skills among children with ADHD [18]. Harvest Challenge is a 3D virtual reality video game designed to train attention self-regulation in children with ADHD using a BCI system [19]. Focus Focus is a themed training video game that is used in cognitive training therapies to reduce the symptoms of ADHD [20]. FarmerKeeper is a video game based on a BCI system designed to improve the attention of children with autism and ADHD [21]. CogniDron-EEG is a system based on a BCI for flying a drone indoors for cognitive training purposes [22]. The evolution of 3D printing technology has opened new doors for the rapid prototyping and customization of EEG headsets. The ninjaCap, a 3D printed headgear explicitly designed for functional Near Infrared Spectroscopy (fNIRS) and electroencephalography applications, was introduced by [23]. The ninjaCap offers a precise method for probe placement, using atlas-based or subject-specific head models and an innovative spring-relaxation algorithm to flatten 3D brain coordinates onto 2D printable panels. This approach improves sensor accuracy, reduces labor-intensive manual processes, and improves both comfort and signal quality, making it suitable for various research and clinical applications. A novel 3D-printed, directly conductive, and flexible EEG electrode system was presented in [24]. This system eliminates the need for Silver/Silver-Chloride (Ag/AgCl) coatings, significantly reducing manufacturing time and costs. The flexible electrodes are flexible to different head shapes and do not require conductive gels, making them more user-friendly in real-worldapplications. Despite the challenges posed by higher contact impedance and increased noise sensitivity, these electrodes offer promising advancements for low-cost personalized EEG systems, particularly in BCI applications [25]. In [26], an ergonomic EEG headset is developed using 3D anthropometry to improve fit and usability. Traditional EEG caps face challenges with comfort, proper electrode placement, and usability in real world environments. Using statistical shape modeling, the authors designed a one-size-fits-all BCI headset that accommodates human head shape and size variations. This approach promises to improve the stability and repeatability of electrode placement, offering a more user-friendly solution than current commercial headsets, which often suffer from poor fit and inconsistent signal quality [27]. The quality of electroencephalography (EEG) signals is essential both in clinical applications and in research. One of the most important factors influencing the quality of these signals is the design of the EEG helmet, especially regarding proper fit and the flexibility of the sensors. A well-designed helmet that ensures a good fit and proper electrode placement significantly improves the accuracy of the obtained signals. For example, the article [28] examines the latest research on ergonomic aspects in brain-computer interfaces (BCIs). It addresses dry electrodes, which allow the detection of brain signals with sufficient quality for BCI applications, analyzing their pros, cons, and performance. Additionally, a summary of the most recent efforts to create new interface designs that reduce fatigue and discomfort during prolonged and daily use is provided. Proper EEG signal acquisition is crucial for improving neurological therapies, such as neurorehabilitation in patients with brain damage, controlling devices through brain-computer interfaces (BCIs), and diagnosing disorders like epilepsy [29] or insomnia [30]. A well-designed helmet facilitates the collection of accurate signals, contributing to the effectiveness of therapies.