分析模型

import { initEegWasm, WasmAlphaBumpDetector, getEegInterleavedSamples } from "@elata-biosciences/eeg-web";

await initEegWasm();

const detector = new WasmAlphaBumpDetector(256, 4); // sampleRateHz, channelCount

const result = detector.process(getEegInterleavedSamples(frame));
if (result?.state_changed) {
  console.log(result.state, result.alpha_power, result.baseline); // state: "high" | "low" | "transitioning" | "unknown"
}

import { WasmAlphaPeakModel } from "@elata-biosciences/eeg-web";

const model = new WasmAlphaPeakModel(256, 4);

const result = model.process(interleaved);
if (result) {
  console.log(result.peak_frequency, result.smoothed_peak_frequency, result.snr);
}

import { WasmCalmnessModel } from "@elata-biosciences/eeg-web";

const model = new WasmCalmnessModel(256, 4);

const result = model.process(interleaved);
if (result) {
  console.log(result.score);          // 0.0 (alert) to 1.0 (very calm)
  console.log(result.smoothed_score); // less jittery
  console.log(result.alpha_beta_ratio);
}

import { AthenaWasmDecoder } from "@elata-biosciences/eeg-web";

const decoder = new AthenaWasmDecoder();

decoder.reset();
decoder.set_use_device_timestamps(true);
decoder.set_clock_kind("monotonic");
decoder.set_reorder_window_ms(50);

const output = decoder.decode(rawBytes);

import { BleTransport } from "@elata-biosciences/eeg-web-ble";
import { AthenaWasmDecoder } from "@elata-biosciences/eeg-web";

const transport = new BleTransport({
  deviceOptions: {
    athenaDecoderFactory: () => new AthenaWasmDecoder(),
  },
});