{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "cell-0",
   "metadata": {},
   "source": [
    "# Autonomic and ECG/PPG Feature Engineering\n",
    "\n",
    "This notebook demonstrates ECG morphology analysis, PPG autonomic nervous system features, SpO2 and perfusion index from dual-wavelength PPG, and ECG-PPG synchronization metrics."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cell-1",
   "metadata": {},
   "source": [
    "## Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cell-2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import plotly.io as pio\n",
    "pio.renderers.default = \"sphinx_gallery\"\n",
    "from plotly import graph_objects as go\n",
    "from vitalDSP.notebooks import load_sample_ecg_small, load_sample_ppg, plot_trace\n",
    "\n",
    "fs = 128\n",
    "signal_col, date_col = load_sample_ecg_small()\n",
    "signal_col = np.array(signal_col)\n",
    "\n",
    "ppg_col, ppg_date = load_sample_ppg()\n",
    "ppg_col = np.array(ppg_col)\n",
    "\n",
    "print(f\"ECG: {len(signal_col)} samples at {fs} Hz\")\n",
    "print(f\"PPG: {len(ppg_col)} samples\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cell-3",
   "metadata": {},
   "source": [
    "## ECG Morphology Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cell-4",
   "metadata": {},
   "outputs": [],
   "source": [
    "from vitalDSP.feature_engineering.ecg_autonomic_features import ECGExtractor\n",
    "\n",
    "ecg_extractor = ECGExtractor(signal_col, sampling_frequency=fs)\n",
    "\n",
    "# Detect R peaks\n",
    "r_peaks = ecg_extractor.detect_r_peaks()\n",
    "print(f\"R peaks detected: {len(r_peaks)}\")\n",
    "\n",
    "# Compute ECG morphology intervals\n",
    "qrs_duration = ecg_extractor.compute_qrs_duration()\n",
    "pr_interval  = ecg_extractor.compute_pr_interval()\n",
    "qt_interval  = ecg_extractor.compute_qt_interval()\n",
    "st_interval  = ecg_extractor.compute_st_interval()\n",
    "\n",
    "print(\"ECG Morphology Features:\")\n",
    "print(f\"  QRS Duration : {qrs_duration:.4f} s\")\n",
    "print(f\"  PR Interval  : {pr_interval:.4f} s\")\n",
    "print(f\"  QT Interval  : {qt_interval:.4f} s\")\n",
    "print(f\"  ST Interval  : {st_interval:.4f} s\")\n",
    "\n",
    "# Visualize R peaks on ECG\n",
    "fig = go.Figure()\n",
    "t = np.arange(len(signal_col)) / fs\n",
    "fig.add_trace(go.Scatter(x=t[:512], y=signal_col[:512], mode='lines', name='ECG'))\n",
    "r_in_range = [r for r in r_peaks if r < 512]\n",
    "if r_in_range:\n",
    "    fig.add_trace(go.Scatter(\n",
    "        x=np.array(r_in_range) / fs,\n",
    "        y=signal_col[r_in_range],\n",
    "        mode='markers', marker=dict(color='red', size=8, symbol='x'),\n",
    "        name='R Peaks'\n",
    "    ))\n",
    "fig.update_layout(title='ECG with R Peak Detection', xaxis_title='Time (s)', yaxis_title='Amplitude')\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cell-5",
   "metadata": {},
   "source": [
    "## P-Wave and S-Wave Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cell-6",
   "metadata": {},
   "outputs": [],
   "source": [
    "p_wave_dur = ecg_extractor.compute_p_wave_duration()\n",
    "s_wave     = ecg_extractor.compute_s_wave()\n",
    "\n",
    "print(f\"P-Wave Duration : {p_wave_dur:.4f} s\")\n",
    "print(f\"S-Wave Feature  : {s_wave}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cell-7",
   "metadata": {},
   "source": [
    "## Arrhythmia Detection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cell-8",
   "metadata": {},
   "outputs": [],
   "source": [
    "arrhythmias = ecg_extractor.detect_arrhythmias()\n",
    "print(\"Arrhythmia Detection:\")\n",
    "print(arrhythmias)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cell-9",
   "metadata": {},
   "source": [
    "## PPG Autonomic Nervous System Features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cell-10",
   "metadata": {},
   "outputs": [],
   "source": [
    "from vitalDSP.feature_engineering.ppg_autonomic_features import PPGAutonomicFeatures\n",
    "\n",
    "ppg_auto = PPGAutonomicFeatures(ppg_col, sampling_frequency=fs)\n",
    "\n",
    "# Respiratory Sinus Arrhythmia — autonomic balance indicator\n",
    "rsa = ppg_auto.compute_rsa()\n",
    "print(f\"RSA (Respiratory Sinus Arrhythmia): {rsa:.4f}\")\n",
    "\n",
    "# Respiratory Rate Variability\n",
    "rrv = ppg_auto.compute_rrv()\n",
    "print(f\"RRV (Resp. Rate Variability)       : {rrv:.4f}\")\n",
    "\n",
    "# Fractal dimension of PPG\n",
    "fd = ppg_auto.compute_fractal_dimension()\n",
    "print(f\"Fractal Dimension                  : {fd:.4f}\")\n",
    "\n",
    "# DFA scaling exponent\n",
    "dfa = ppg_auto.compute_dfa()\n",
    "print(f\"DFA Scaling Exponent               : {dfa:.4f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cell-11",
   "metadata": {},
   "source": [
    "## PPG Light Features (SpO2, Perfusion Index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cell-12",
   "metadata": {},
   "outputs": [],
   "source": "from vitalDSP.feature_engineering.ppg_light_features import PPGLightFeatureExtractor\n\n# Simulate IR and Red PPG signals (in real use, load dual-wavelength sensor data)\nir_signal  = ppg_col\nred_signal = ppg_col * 0.95 + np.random.normal(0, 0.001, len(ppg_col))\n\nppg_light = PPGLightFeatureExtractor(ir_signal=ir_signal, red_signal=red_signal, sampling_freq=fs)\n\nspo2_values, spo2_indices = ppg_light.calculate_spo2()\npi   = ppg_light.calculate_perfusion_index()\nrr   = ppg_light.calculate_respiratory_rate()\nppr  = ppg_light.calculate_ppr()\n\nprint(\"PPG Light-Based Features:\")\nprint(f\"  SpO2 (mean)        : {float(np.mean(spo2_values)):.1f} %\")\nprint(f\"  Perfusion Index    : {pi:.4f} %\")\nprint(f\"  Respiratory Rate   : {rr:.2f} breaths/min\")\nprint(f\"  PPR (Pulse/Pleth)  : {ppr:.4f}\")"
  },
  {
   "cell_type": "markdown",
   "id": "cell-13",
   "metadata": {},
   "source": [
    "## ECG-PPG Synchronization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cell-14",
   "metadata": {},
   "outputs": [],
   "source": [
    "from vitalDSP.feature_engineering.ecg_ppg_synchronization_features import ECGPPGSynchronization\n",
    "\n",
    "sync = ECGPPGSynchronization(\n",
    "    ecg_signal=signal_col,\n",
    "    ppg_signal=ppg_col,\n",
    "    ecg_fs=fs,\n",
    "    ppg_fs=fs\n",
    ")\n",
    "\n",
    "# Pulse Transit Time — correlates with blood pressure\n",
    "ptt = sync.compute_ptt()\n",
    "print(f\"Pulse Transit Time (PTT)  : {ptt:.4f} s\")\n",
    "\n",
    "# Pulse Arrival Time\n",
    "pat = sync.compute_pat()\n",
    "print(f\"Pulse Arrival Time (PAT)  : {pat:.4f} s\")\n",
    "\n",
    "# Heart rate / pulse rate synchrony\n",
    "hr_pr = sync.compute_hr_pr_sync()\n",
    "print(f\"HR-PR Synchrony           : {hr_pr:.4f}\")\n",
    "\n",
    "# PPG rise time\n",
    "rise_time = sync.compute_ppg_rise_time()\n",
    "print(f\"PPG Rise Time             : {rise_time:.4f} s\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cell-15",
   "metadata": {},
   "source": [
    "## ECG-PPG Overlay Visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cell-16",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Show ECG and PPG overlaid, aligned in time\n",
    "n = min(len(signal_col), len(ppg_col), 512)\n",
    "t = np.arange(n) / fs\n",
    "\n",
    "ecg_norm = (signal_col[:n] - signal_col[:n].mean()) / (signal_col[:n].std() + 1e-8)\n",
    "ppg_norm = (ppg_col[:n] - ppg_col[:n].mean()) / (ppg_col[:n].std() + 1e-8)\n",
    "\n",
    "fig = go.Figure()\n",
    "fig.add_trace(go.Scatter(x=t, y=ecg_norm, mode='lines', name='ECG (normalized)'))\n",
    "fig.add_trace(go.Scatter(x=t, y=ppg_norm, mode='lines', name='PPG (normalized)'))\n",
    "fig.update_layout(\n",
    "    title='ECG-PPG Synchronization',\n",
    "    xaxis_title='Time (s)', yaxis_title='Normalized Amplitude'\n",
    ")\n",
    "fig.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "name": "python",
   "version": "3.9.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}