**6. Conclusions and Further Work**

An electroencephalogram is an electrophysiological monitoring method that records the electrical activity of the brain. It is a noninvasive technique through electrodes placed on the scalp, and therefore, it is suitable for use in a wide variety of situations, not just the laboratory ones. Moreover, this method is data intensive, and in order to successfully manage these data, effective data visualization and collection are important. Software applications are needed for brain data management.

The article had special interest in affordable and low-cost EEG devices. A particular one is Muse from Interaxon, which although limited by the number of electrodes, is widely used for meditation and relaxation activities [14,15,17], being useful in the contexts of stress and anxiety. In this paper, we wanted to identify internal and external features for EEG data management and low-cost EEG devices; this collection of features should be the answer to our research question. These requirements were proposed and identified in the Method and Validation sections of this paper. In the internal dimension, several requirements were proposed, data import and conversion, the BIDS management of data, and real-time data visualization, and all these features were considered in the MuseStudio implementation. Later, using DESMET, external requirements were proposed and used in a validation activity. These external features were related to session data management (data importation and exportation), data visualization (signal visualization, consistency, scenario identification, easy for data reviewing), and ease of operation (scalability, same time, and different place).

Nevertheless, the software associated (manufacturer developed) with this device has many limitations, due to the lack of support for data collection and management. In this article, we overcame this deficiency with the creation of a library to manage brain activity data using Muse (different versions of Muse, Muse 2 and Muse S). MuseStudio provides a set of tools that facilitate storing, importing, exporting, visualizing, and sharing data. This article described the main features and strengths of the library, as well as a validation of those features, including to what extent they were achieved. In terms of hardware limitations, they were set by the particular low-cost device, Muse in this case. Depending on the specifications, some domains may be out of scope, not providing valuable insights.

Initially, several experts from the Psychology Department of the University of Castilla-La Mancha helped to determine which were the functional and nonfunctional features that a library related to brain data should include. Thanks to this collaboration, a set of features was identified by these experts to determine what tasks a software brain data management software tool should be able to perform. These features were used in order to validate MuseStudio by other experts, but additionally, these features can be used to compare MuseStudio with other alternatives in the future. In our functional and nonfunctional validation, other experts identified the presence or absence of those features using surveys, heuristic evaluation techniques, and analyzing MuseStudio in particular.

The library implemented is already a relevant contribution because it covers the initial necessities established. This library has been shared with the community through an opensource license [5]. Since its inception, MuseStudio has not been intended for the general public, but rather for researchers who are already familiar with the use and interpretation of brain signals. However, we can address other evaluations in the future as the library grows and improves. For instance, it could be useful as soon as a graphical interface is included, which is the main nonfunctional limitation. This feature would encourage the use of the library.

The library can be further improved by adding authentication and additional security capabilities. At this moment, for instance, the authentication of users and sessions must be performed by analysts, and these identification activities are not supported by the current version of MuseStudio. In this sense, users that need remote access should be able to establish secure connections between peers.

**Author Contributions:** Conceptualization, M.Á.S.-C. and F.M.; methodology, M.Á.S.-C., F.M. and M.T.L.; validation, M.Á.S.-C., F.M. and M.T.L.; investigation, M.Á.S.-C.; resources, M.T.L.; writing original draft preparation, M.Á.S.-C.; writing—review and editing, F.M. and M.T.L.; funding acquisition, M.T.L. and F.M. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by the European Regional Development Fund under the Grant Evaluando la eXperiencia de Usuario de personas mayores con técnicas de Neuroevaluación—NeUX (SBPLY/17/180501/000192).

**Data Availability Statement:** Not Applicable.

**Acknowledgments:** The authors acknowledge the participation of the staff from the Psychology Department and the Computer Science Department at the University of Castilla-La Mancha and the Spanish Ministerio de Economía y Competitividad for partially supporting this research through Grant 2gether (PID2019-108915RB-I00).

**Conflicts of Interest:** The authors declare no conflict of interest.
