Crate elata_eeg_models 

EEG Analysis Models

This crate provides analysis models that process EEG data from the HAL. Currently implemented models:

• Alpha Bump Detection: Detects changes in alpha band power, indicating transitions between relaxed (eyes closed) and alert (eyes open) states.

• Alpha Peak Model: Finds the dominant frequency within the alpha band (8-13 Hz) and reports its power and signal-to-noise ratio.

• Calmness Model: Computes a continuous calmness score based on the ratio of relaxation-associated frequencies (alpha, theta) to alertness-associated frequencies (beta).

Usage

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

// Create models
let mut alpha_detector = AlphaBumpDetector::new(256);
let mut alpha_peak = AlphaPeakModel::new(256);
let mut calmness = CalmnessModel::new(256);

// Process data (assuming buffer is filled from a device)
let buffer = SampleBuffer::new(256, 4);
// ... fill buffer ...

// Get analysis results
// let alpha_result = alpha_detector.process(&buffer);
// let alpha_peak_result = alpha_peak.process(&buffer);
// let calmness_result = calmness.process(&buffer);

Structs

AlphaBumpDetector

Alpha bump detection model

AlphaBumpOutput

Output from the alpha bump detector

AlphaPeakModel

Alpha peak analysis model

AlphaPeakOutput

Output from the alpha peak model

CalmnessModel

Calmness analysis model

CalmnessOutput

Output from the calmness model

Enums

AlphaState

Detected alpha state

Traits

Model

Core trait for EEG analysis models

ModelOutput

Output from a model analysis