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BCI

BCIs, or Brain-Computer Interfaces, also known as BMIs, or Brain-Machine Interfaces, are devices that process brain activity to control external devices, allowing users to interact with them using their thoughts. They fall into two main paradigms: invasive, which involves neurological implants, and non-invasive, which involves an electrode headset placed near the scalp. These types of technology are used in the medical field and for user interaction with machines.

Brain-Wave Reference:

😪 Delta (0.5–4 Hz) - Deep sleep

🧘 Theta (4–8 Hz) - Drowsiness, meditation

😌 Alpha (8–12 Hz) - Calm focus

⚠️ Beta (13–30 Hz) - Alert, thinking

🤔 Gamma (30–100 Hz) - High-level cognition

Video Overviews

EEG (Electroencephalogram) Explained

  • EEG (electroencephalogram) measures electricity in the brain and records it
  • electrodes analyze the difference in charge between two areas of different charge, known as a dipole
  • Excitatory Postsynaptic Potential (EPSP), positive inside, negative outside, distant extracellular space becomes relatively more positive
  • Inhibatory Postsynaptic Potential, vice versa to EPSP
  • cerebral cortex contains billions of pyramid shape neurons parallel to each other but perpendicular to scalp
  • combined creates a larger dipole that is detectable
  • years of training to accurately read EEG signals

Open-Ended Questions

1.) Why might tests like noisy signals like EEG still be useful in serious tech like brain-computer interfaces? --- Despite having a low signal-to-noise ratio (SNR), noisy signals in EEGs are still useful as they provide real-time, non-invasive access to brain activity patterns that can be decoded using advanced signal processing and machine learning techniques to control external devices or interpret cognitive states.

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First project for Brain-Computer Interface

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  • C++ 60.1%
  • Python 39.9%