*2.5. Real-Time Remote View*

Performing neural experiments usually requires real-time visualization of the brain signals captured. With time-based graphs, it is possible to detect how good the data received from the electrodes are, due to the fact that they may not have full contact with the skin and produce extra noise. Muse, with four electrodes, is especially vulnerable to this issue because one bad sensor can invalidate a full recording. The current available solution [30] only shows real-time visualization for one device at a time. Moreover, it only works on the same computer to which Muse is connected. This problem narrows down the flexibility when researchers want to perform experiments with multiple devices at once. The MuseStudio library provides access to real-time graphs no matter the number of devices attached. Additionally, it shows when the contact of the sensors with the skin is good for each of them independently.

Globalization has broken many barriers, and healthcare is one of them. Telemedicine [36] is increasingly being adopted for receiving medical treatment at a distance. In fact, patients who receive palliative care by telemedicine are very satisfied with the results. For this reason, we want everyone to be able to access neuroevaluations anywhere in the world without need to travel long distances to reach experts.

Instead of creating a local instance of a program, we created a web server with an IP address and a port that users can access through a web browser. This allows many users to be connected to the same endpoint, even if they are located outside the local area network. However, as a prerequisite, the server port must be connected to the Internet for external access. The implementation can be used straight away without authentication, and it is modular, so it can be integrated with other Python environments without adaptation, such as a website with a log-in required. The web browser must have JavaScript enabled to show the graphs. Finally, the complete set of options added is: sensor selection, update interval (from 200 ms to 5 s), play/pause, zoom in/out, and expand graphs.

## **3. Method**

This section identifies and describes the internal characteristics of the MuseStudio library [5] available at https://github.com/miguelascifo/MuseStudio, accessed on 26 February 2021, which can be installed through the Python pip package manager (https: //pypi.org/project/musestudio/, accessed on 3 March 2021) as well. The main internal

requirements derived from the functionality of MuseStudio are presented in this section, including raw data importation and real-time data visualization. Raw data importation involves two activities: data conversion and data organization with the BIDS. All these activities are described below.
