## 3 Materials and Methods
### EEG Data Acquisition and Monitoring Through the Muse 2 Headband  
A central component of this platform is the Muse 2 EEG headband, a sophisticated wearable device equipped with four electrodes (TP9, AF7, AF8, TP10) capable of capturing brainwave data at a 256 Hz sampling rate. The Muse 2 headband was utilized in this study primarily for testing purposes and was not a primary data source, serving to explore its potential integration into the NeuroPredict platform, which aims to provide real-time, continuous monitoring of mental health conditions, such as schizophrenia. The hardware-to-software transition involved capturing raw EEG signals from the four electrodes, which are strategically located to capture neural activity from both frontal and temporal brain regions, which are particularly relevant to schizophrenia research. Once the EEG signals are captured by the headband, they are transmitted via Bluetooth to a mobile application called Mind Monitor, which acts as the primary interface for managing the data acquisition process. In Mind Monitor, the raw EEG signals are visualized in real time and stored in formats such as CSV or European Data Format (EDF). These formats are widely used for EEG research, allowing flexibility in subsequent analysis.  
The transition from raw EEG data to usable signals involves several key preprocessing steps, which are performed within the Mind Monitor software [65]. First, the raw signals are passed through a bandpass filter, typically set between 1 and 50 Hz, to remove noise and muscle artifacts that fall outside the EEG frequency range. Additionally, baseline correction is applied to remove any DC offset or slow drifts in the data, ensuring that the signals accurately represent moment-to-moment brain activity.  
Following the initial filtering and correction, the EEG data are transformed into a frequency domain representation using Fast Fourier Transform (FFT). This step decomposes the time domain signal into its constituent frequency bands--Delta, Theta, Alpha, Beta, and Gamma. These frequency components are crucial for subsequent analysis, particularly in the context of schizophrenia research, where specific abnormalities in frequency bands (such as reduced Alpha power in frontal regions) can be indicative of cognitive dysfunction [66].  
The primary frequencies and features of human EEG waves are as follows. There are five brain waves that are commonly recognized, which are described the Table 1.  
In the context of this study, the Muse 2 was tested to evaluate its compatibility with the proposed DL models and TE analysis pipeline. Although the primary data in this research were obtained from another openly available source, the Muse 2 was integrated conceptually into the framework of the NeuroPredict platform and was not used to generate the primary EEG dataset analyzed in this study. Its role will be further highlighted in future applications that will involve continuous monitoring of EEG signals to detect early signs of cognitive decline or schizophrenia relapse, potentially improving patient outcomes through real-time interventions. This conceptual integration highlights the importance of the Muse 2 headband's technical capabilities for non-invasive, real-time monitoring in remote or clinical settings.