EEG stands for ElectroEncephaloGram or ElectroEncephaloGraphy. Electro stands for electricity, Encephalo means brain, Gram means drawing, Graphy means writing. By capturing the electrical patterns generated by neuronal activity, EEG provides valuable insights into brain function, supporting the diagnosis and monitoring of various neurological and psychological conditions.
For there to be a measurable readable change, we have to have a dipole source. Dipole sources have two terminals containing opposite charges. In our brain, neurons undergo processes were they change their charge sign. Moreover, because these changes occur with different rates, types, and places, groups of neurons form this difference in change with other groups, causing a detectable wavelike graph.
EEG is an extensively validated and widely adopted method for assessing brain activity, offering unique advantages in the evaluation of mental health. The electrical signals of the brain vary in amplitude and frequency based on brain state and function. For example, gamma waves indicate the brain in a state of extreme concentration. However, delta waves —which range from 0.5-4 Hz— assure that a person is asleep.
Distinct differences in EEG patterns are often observed between individuals with typical brain activity and those with mental health conditions. Such variations, displayed as waveforms, can be indicative of specific neurological or psychiatric disorders.
For instance, abnormal EEG patterns may correlate with conditions such as epilepsy, schizophrenia, or mood disorders, assisting clinicians in accurate diagnosis and informing treatment strategies.
Even though our project is based on the interpretation of EEG data, the validity of such experimental data may be called into question or dismissed by professionals and investors. So, why EEG data?
While standard questionnaires and psychoanalysis techniques offer a more traditional approach to diagnosis, the possible subjective human bias attached to them will always be a detracting flaw of their eventual results. Because of that, the aforementioned objectivity and real-time measuring potential associated with EEGs makes them the ideal choice for a data source: EEGs can accurately identify depression patterns by capturing specific neural activity linked to depressive states.
Multiple machine learning models were used, showing consistent success rates in analyzing EEG data, thus highlighting its usefulness as a diagnostic tool–effectively establishing it as convention in our context (in addition to it being incredibly easy and convenient to collect), but how can we be sure of the reliability of said data?
Recent research advancements have proven that EEG data is very much capable of reaching extremely high accuracy rates in correctly diagnosing mental health issues. For example, a study by Diagnostics indicated that EEG data could achieve up to 97% accuracy in detecting major depressive disorders; another study by PlumX Metrics in Hebei, China has demonstrated that the accuracy of EEG data in diagnosing mental health illnesses has reached 92.4%. These numbers alone prove the immense potential that EEG data holds and confirm the reliability in real-world scenarios of this data.
Of course, as data sets grow and improve, and as EEG data collection and interpretation techniques become more and more optimized, these numbers will only continue to increase (and so will the viability of NORA, in turn), therefore attesting to the value that this data can hold for the diagnosis of mental health issues.
Nora requires precise data for accurate diagnoses. With industry leaders like MUSE and OpenBCI, we can leverage the quality, mobility, and ease of use that high-end EEG technology offers. After careful evaluation, we recommend the MUSE Headband 2, which provides reliable brainwave data essential for AI-driven mental health diagnostics while being cost-effective.
Its wireless, lightweight design ensures patient comfort without sacrificing usability, making it ideal for clinical and everyday settings. With a strong reputation in neuroscience research and wellness applications, the MUSE Headband 2 aligns seamlessly with Nora’s mission to enhance diagnostic accuracy and support real lives, not just numbers on a screen.