elata-eeg-models

Reference EEG analysis models for the Elata SDK.

This crate consumes elata-eeg-hal::SampleBuffer inputs and produces higher-level outputs that applications can use directly.

Currently included:

• AlphaBumpDetector for alpha-band state transitions
• AlphaPeakModel for dominant alpha-frequency tracking
• CalmnessModel for a continuous calmness-oriented score
• the shared Model and ModelOutput traits

What it is for

Use elata-eeg-models when you already have buffered EEG samples and want to run device-agnostic analysis without depending on a specific headset transport.

Basic example

use elata_eeg_hal::SampleBuffer;
use elata_eeg_models::{AlphaPeakModel, Model};

let mut model = AlphaPeakModel::new(256);
let buffer = SampleBuffer::new(256, 4);

let _maybe_output = model.process(&buffer);

elata-eeg-models is intended to sit above elata-eeg-hal and elata-eeg-signal in the stack.