# MuseStudio: Brain Activity Data Management Library for Low-Cost EEG Devices
## 2 Background  
An electroencephalogram is a data-intensive test that allows detecting abnormalities in brain waves, or the electrical activity of the brain [7]. During the procedure, electrodes consisting of small metal discs with thin wires are pasted onto the scalp. This technology has a wide variety of uses, especially in the emotion recognition domain, as the results of these articles showed [8; 9].  
Due to the previously annotated increasing demand of EEG devices, the number of available devices is on the rise, and they have many different characteristics [3, 10, 11]. Moreover, these devices are not only present in the research environment [12, 13, 14, 15, 16, 17], but also in the entertainment one [18, 19, 20]. A recent article [21] analyzed the number of electrodes included in devices depending on their design. The authors concluded that the availability of more or less electrodes depends on the final application in which the device will be used. However, in these scenarios, the number of sensors is not the only key factor: data collection and software for supporting them are other relevant factors for success.  
In our case, we focused on low-cost EEG devices [10, 22, 23]. The price requirement results in the number of electrodes being reduced, and then, the device has less capabilities depending on the field in which it is deployed [21]. Considering that there are still plenty of applications that can be explored and relate to meditation, relaxation, concentration, stress, and anxiety, many therapeutic and entertainment activities can be approached. In this research, Muse 2 was chosen among other viable alternatives. It features a sampling rate of 256 Hz for EEG concurrent signals, four dry capturing electrodes, plus frontal reference channels, an accelerometer, a gyroscope, a PhotoPlethysmoGraphy (PPG) sensor, a built-in battery, and Bluetooth. Following the 10-20 standard system, the device locates its sensors at AF7, AF8, TP9, and TP10.  
Muse has been validated as a device for conducting Event-Related Potential (ERP) research [24]. This device has been compared with other wearable sensors resulting in high performance in the fields of ease of integration and applied usability [25]. In addition, many other studies have used Muse for several purposes, including brain wave activity detection during training [26], enjoyment evaluation [27], accelerometer measurement of head movement during surgery [28], and concentration and stress measurement during surgery [29].  
In addition to the inherent hardware limitations of the devices, the software restrictions in terms of applications, software development kits, and application programming interfaces should be considered as well [3]. The great majority of software provided by manufacturers cannot manage activities, record sessions, and provide remote real-time visualization while participants are being evaluated. These issues are important limitations in supporting scientific activities. The community of users and researchers of, for instance, Muse products cannot perform data management for several sessions and different users and, later, analyze these data. The traditional manner of making evaluations with Muse is shown in Figure 1. To overcome some of these issues, MuseStudio allows storing data in a structured manner and sharing them.  
Figure 1: Traditional usage of Muse in experiments.  
Specifically, Muse does not include brain data management software, nor real-time visualization, nor recording, so one cannot make use of its potential features. Our solution provides a Python library that allows working with those functionalities, even with several devices and places at the same time.