Classification of EEG Waves and Their Application in Wearable Brain-Computer Interfaces (BCIs)

     The human brain comprises billions of neurons, and electroencephalogram (EEG) signals represent the electrical activity generated by synaptic interactions among these neurons. EEG captures the brain’s dynamic electrical fluctuations, reflecting the collective electrophysiological activity of neural cells on the cerebral cortex or scalp surface.

     To detect EEG signals, electrodes are typically placed on the scalp (non-invasive BCI) or implanted beneath it (invasive BCI). Specialized EEG monitoring devices then collect and process these signals.

Classification of EEG Waves
     EEG waves, as spontaneous rhythmic neural activities, exhibit frequencies ranging from 1 to 30 Hz. In wearable BCI applications, their frequency bands and associated physiological states are categorized as follows:

·   Delta (δ) Waves (0.5–4 Hz): Deep sleep or unconscious states, with minimal energy variation during sleep.

·   Theta (θ) Waves (4–7 Hz): Light sleep, deep relaxation, or low-stress states.

·   Alpha (α) Waves (8–13 Hz): Awake, relaxed states, often observed during closed-eye meditation.

·   Beta (β) Waves (14–28 Hz): Focus, alertness, stress, or fatigue. Increased beta activity correlates with heightened concentration.

·   Gamma (γ) Waves (30–45 Hz): High focus, heightened awareness, and cognitive processing.

Key Insights

1.  Higher frequencies (Beta, Gamma) indicate intense mental effort, focus, and potential stress, requiring periodic rest.

2.  Lower frequencies (Theta, Delta) correspond to drowsiness or sleep.

3.  Alpha waves serve as the threshold between relaxation and alertness.

4.  Above Alpha: Beta and Gamma waves reflect increasing focus and clarity.

5.  Below Alpha: Theta and Delta waves signify deeper relaxation or sleep stages.

Challenges in Wearable BCI Applications
     Wearable BCIs face constraints in portability, signal accuracy, cost, size, and power consumption. Most commercial EEG headbands suffer from limited precision, susceptibility to noise, high costs, or bulkiness, hindering widespread adoption.

Kingsense Electronics’ Breakthrough Solution
     Addressing these challenges, Kingsense Electronics has launched the EEGM102 Bluetooth EEG Module, a cutting-edge solution for wearable BCIs. The module integrates:

·   A dual-channel low-noise EEG front-end chip (KS1092) for high-precision signal acquisition.

·   A low-power 32-bit ARM® Cortex-M4F Bluetooth 5.0 MCU for robust signal processing.

Key Features:

·   Supports metal electrodes for non-invasive EEG signal capture from the forehead.

·   Embedded energy-efficient algorithms preprocess and analyze EEG data, wirelessly outputting raw α/β/γ/δ/θ wave spectra and quantifiable metrics (e.g., focus, emotional states, stress, fatigue, relaxation).

·   Compact size: 12mm × 20mm (including Bluetooth MCU and antenna).

·   Ultra-low power consumption: 5mA maximum operating current.

Applications:
     The EEGM102 module is ideal for wearable EEG devices, focus training, meditation aids, sleep/emotion monitoring, and next-gen wireless BCI products.