Desarrollo de casco de electroencefalografía (EEG) para apoyo en diagnóstico de trastorno del espectro autista (TEA)
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| Publicado en: | PQDT - Global (2025) |
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ProQuest Dissertations & Theses
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| Acceso en línea: | Citation/Abstract Full Text - PDF Full text outside of ProQuest |
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| Resumen: | A mechatronic system for noninvasive scalp electroencephalography (EEG) reading was developed, designed to operate with 8 channels and following the international 10-20 standard for electrode placement. The system is compatible with both foam electrodes, suitable for patients with short or no hair, and spoon electrodes, intended for patients with thick hair or small skulls. The system integrates three main domains. In the electronics domain, a board was designed to amplify and filter EEG signals, allowing them to be processed by an Arduino microcontroller. The implemented filtering discards signals with frequencies above 100 Hz, although it does not completely eliminate 60 Hz signals resulting from physical artifacts. In the graphical interface domain, a Python application was developed that allows viewing 8-channel signals in a 98 MB executable file. The interface includes a digital filter that classifies signals into frequency bands (delta, theta, alpha, beta, and gamma) and is optimized for subsequent analysis, with adjustable initial settings for instant recordings. In the mechanical domain, the headset design was based on the OpenBCI model. The system was evaluated using simulated data preloaded into the Arduino, which validated its ability to adequately process and display EEG signals. These tests demonstrated that the system meets the established objectives, offering a functional solution for capturing and analyzing EEG signals. The graphical interface allowed for the differentiation of frequency bands and facilitated the analysis of simulated data, highlighting its potential for future applications. It is concluded that this system represents a significant advance as a basis for further developments, with medical interest in its validation under clinical standards and the possibility of expanding its functionalities in neurological diagnosis and monitoring. |
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| ISBN: | 9798288812965 |
| Fuente: | ProQuest Dissertations & Theses Global |