feat: Training mode, ADR docs, vitals and wifiscan crates
- Add --train CLI flag with dataset loading, graph transformer training, cosine-scheduled SGD, PCK/OKS validation, and checkpoint saving - Refactor main.rs to import training modules from lib.rs instead of duplicating mod declarations - Add ADR-021 (vital sign detection), ADR-022 (Windows WiFi enhanced fidelity), ADR-023 (trained DensePose pipeline) documentation - Add wifi-densepose-vitals crate: breathing, heartrate, anomaly detection, preprocessor, and temporal store - Add wifi-densepose-wifiscan crate: 8-stage signal intelligence pipeline with netsh/wlanapi adapters, multi-BSSID registry, attention weighting, spatial correlation, and breathing extraction Co-Authored-By: claude-flow <ruv@ruv.net>
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ruv
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//! Respiratory rate extraction from CSI residuals.
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//!
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//! Uses bandpass filtering (0.1-0.5 Hz) and spectral analysis
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//! to extract breathing rate from multi-subcarrier CSI data.
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//!
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//! The approach follows the same IIR bandpass + zero-crossing pattern
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//! used by [`CoarseBreathingExtractor`](wifi_densepose_wifiscan::pipeline::CoarseBreathingExtractor)
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//! in the wifiscan crate, adapted for multi-subcarrier f64 processing
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//! with weighted subcarrier fusion.
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use crate::types::{VitalEstimate, VitalStatus};
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/// IIR bandpass filter state (2nd-order resonator).
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#[derive(Clone, Debug)]
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struct IirState {
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x1: f64,
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x2: f64,
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y1: f64,
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y2: f64,
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}
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impl Default for IirState {
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fn default() -> Self {
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Self {
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x1: 0.0,
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x2: 0.0,
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y1: 0.0,
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y2: 0.0,
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}
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}
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}
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/// Respiratory rate extractor using bandpass filtering and zero-crossing analysis.
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pub struct BreathingExtractor {
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/// Per-sample filtered signal history.
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filtered_history: Vec<f64>,
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/// Sample rate in Hz.
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sample_rate: f64,
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/// Analysis window in seconds.
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window_secs: f64,
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/// Maximum subcarrier slots.
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n_subcarriers: usize,
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/// Breathing band low cutoff (Hz).
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freq_low: f64,
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/// Breathing band high cutoff (Hz).
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freq_high: f64,
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/// IIR filter state.
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filter_state: IirState,
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}
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impl BreathingExtractor {
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/// Create a new breathing extractor.
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///
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/// - `n_subcarriers`: number of subcarrier channels.
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/// - `sample_rate`: input sample rate in Hz.
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/// - `window_secs`: analysis window length in seconds (default: 30).
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#[must_use]
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#[allow(clippy::cast_possible_truncation, clippy::cast_sign_loss)]
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pub fn new(n_subcarriers: usize, sample_rate: f64, window_secs: f64) -> Self {
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let capacity = (sample_rate * window_secs) as usize;
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Self {
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filtered_history: Vec::with_capacity(capacity),
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sample_rate,
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window_secs,
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n_subcarriers,
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freq_low: 0.1,
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freq_high: 0.5,
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filter_state: IirState::default(),
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}
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}
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/// Create with ESP32 defaults (56 subcarriers, 100 Hz, 30 s window).
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#[must_use]
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pub fn esp32_default() -> Self {
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Self::new(56, 100.0, 30.0)
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}
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/// Extract respiratory rate from a vector of per-subcarrier residuals.
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///
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/// - `residuals`: amplitude residuals from the preprocessor.
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/// - `weights`: per-subcarrier attention weights (higher = more
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/// body-sensitive). If shorter than `residuals`, missing weights
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/// default to uniform.
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///
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/// Returns a `VitalEstimate` with the breathing rate in BPM, or
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/// `None` if insufficient history has been accumulated.
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pub fn extract(&mut self, residuals: &[f64], weights: &[f64]) -> Option<VitalEstimate> {
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let n = residuals.len().min(self.n_subcarriers);
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if n == 0 {
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return None;
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}
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// Weighted fusion of subcarrier residuals
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let uniform_w = 1.0 / n as f64;
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let weighted_signal: f64 = residuals
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.iter()
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.enumerate()
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.take(n)
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.map(|(i, &r)| {
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let w = weights.get(i).copied().unwrap_or(uniform_w);
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r * w
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})
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.sum();
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// Apply IIR bandpass filter
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let filtered = self.bandpass_filter(weighted_signal);
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// Append to history, enforce window limit
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self.filtered_history.push(filtered);
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let max_len = (self.sample_rate * self.window_secs) as usize;
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if self.filtered_history.len() > max_len {
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self.filtered_history.remove(0);
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}
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// Need at least 10 seconds of data
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let min_samples = (self.sample_rate * 10.0) as usize;
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if self.filtered_history.len() < min_samples {
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return None;
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}
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// Zero-crossing rate -> frequency
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let crossings = count_zero_crossings(&self.filtered_history);
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let duration_s = self.filtered_history.len() as f64 / self.sample_rate;
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let frequency_hz = crossings as f64 / (2.0 * duration_s);
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// Validate frequency is within the breathing band
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if frequency_hz < self.freq_low || frequency_hz > self.freq_high {
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return None;
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}
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let bpm = frequency_hz * 60.0;
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let confidence = compute_confidence(&self.filtered_history);
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let status = if confidence >= 0.7 {
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VitalStatus::Valid
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} else if confidence >= 0.4 {
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VitalStatus::Degraded
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} else {
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VitalStatus::Unreliable
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};
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Some(VitalEstimate {
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value_bpm: bpm,
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confidence,
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status,
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})
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}
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/// 2nd-order IIR bandpass filter using a resonator topology.
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///
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/// y[n] = (1-r)*(x[n] - x[n-2]) + 2*r*cos(w0)*y[n-1] - r^2*y[n-2]
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fn bandpass_filter(&mut self, input: f64) -> f64 {
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let state = &mut self.filter_state;
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let omega_low = 2.0 * std::f64::consts::PI * self.freq_low / self.sample_rate;
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let omega_high = 2.0 * std::f64::consts::PI * self.freq_high / self.sample_rate;
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let bw = omega_high - omega_low;
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let center = f64::midpoint(omega_low, omega_high);
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let r = 1.0 - bw / 2.0;
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let cos_w0 = center.cos();
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let output =
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(1.0 - r) * (input - state.x2) + 2.0 * r * cos_w0 * state.y1 - r * r * state.y2;
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state.x2 = state.x1;
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state.x1 = input;
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state.y2 = state.y1;
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state.y1 = output;
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output
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}
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/// Reset all filter state and history.
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pub fn reset(&mut self) {
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self.filtered_history.clear();
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self.filter_state = IirState::default();
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}
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/// Current number of samples in the history buffer.
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#[must_use]
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pub fn history_len(&self) -> usize {
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self.filtered_history.len()
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}
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/// Breathing band cutoff frequencies.
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#[must_use]
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pub fn band(&self) -> (f64, f64) {
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(self.freq_low, self.freq_high)
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}
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}
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/// Count zero crossings in a signal.
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fn count_zero_crossings(signal: &[f64]) -> usize {
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signal.windows(2).filter(|w| w[0] * w[1] < 0.0).count()
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}
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/// Compute confidence in the breathing estimate based on signal regularity.
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fn compute_confidence(history: &[f64]) -> f64 {
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if history.len() < 4 {
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return 0.0;
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}
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let n = history.len() as f64;
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let mean: f64 = history.iter().sum::<f64>() / n;
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let variance: f64 = history.iter().map(|x| (x - mean) * (x - mean)).sum::<f64>() / n;
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if variance < 1e-15 {
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return 0.0;
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}
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let peak = history
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.iter()
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.map(|x| x.abs())
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.fold(0.0_f64, f64::max);
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let noise = variance.sqrt();
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let snr = if noise > 1e-15 { peak / noise } else { 0.0 };
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// Map SNR to [0, 1] confidence
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(snr / 5.0).min(1.0)
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}
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#[cfg(test)]
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mod tests {
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use super::*;
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#[test]
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fn no_data_returns_none() {
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let mut ext = BreathingExtractor::new(4, 10.0, 30.0);
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assert!(ext.extract(&[], &[]).is_none());
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}
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#[test]
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fn insufficient_history_returns_none() {
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let mut ext = BreathingExtractor::new(2, 10.0, 30.0);
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// Just a few frames are not enough
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for _ in 0..5 {
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assert!(ext.extract(&[1.0, 2.0], &[0.5, 0.5]).is_none());
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}
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}
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#[test]
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fn zero_crossings_count() {
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let signal = vec![1.0, -1.0, 1.0, -1.0, 1.0];
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assert_eq!(count_zero_crossings(&signal), 4);
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}
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#[test]
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fn zero_crossings_constant() {
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let signal = vec![1.0, 1.0, 1.0, 1.0];
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assert_eq!(count_zero_crossings(&signal), 0);
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}
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#[test]
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fn sinusoidal_breathing_detected() {
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let sample_rate = 10.0;
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let mut ext = BreathingExtractor::new(1, sample_rate, 60.0);
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let breathing_freq = 0.25; // 15 BPM
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// Generate 60 seconds of sinusoidal breathing signal
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for i in 0..600 {
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let t = i as f64 / sample_rate;
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let signal = (2.0 * std::f64::consts::PI * breathing_freq * t).sin();
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ext.extract(&[signal], &[1.0]);
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}
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let result = ext.extract(&[0.0], &[1.0]);
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if let Some(est) = result {
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// Should be approximately 15 BPM (0.25 Hz * 60)
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assert!(
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est.value_bpm > 5.0 && est.value_bpm < 40.0,
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"estimated BPM should be in breathing range: {}",
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est.value_bpm,
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);
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assert!(est.confidence > 0.0, "confidence should be > 0");
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}
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}
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#[test]
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fn reset_clears_state() {
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let mut ext = BreathingExtractor::new(2, 10.0, 30.0);
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ext.extract(&[1.0, 2.0], &[0.5, 0.5]);
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assert!(ext.history_len() > 0);
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ext.reset();
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assert_eq!(ext.history_len(), 0);
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}
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#[test]
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fn band_returns_correct_values() {
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let ext = BreathingExtractor::new(1, 10.0, 30.0);
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let (low, high) = ext.band();
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assert!((low - 0.1).abs() < f64::EPSILON);
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assert!((high - 0.5).abs() < f64::EPSILON);
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}
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#[test]
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fn confidence_zero_for_flat_signal() {
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let history = vec![0.0; 100];
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let conf = compute_confidence(&history);
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assert!((conf - 0.0).abs() < f64::EPSILON);
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}
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#[test]
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fn confidence_positive_for_oscillating_signal() {
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let history: Vec<f64> = (0..100)
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.map(|i| (i as f64 * 0.5).sin())
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.collect();
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let conf = compute_confidence(&history);
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assert!(conf > 0.0);
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}
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#[test]
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fn esp32_default_creates_correctly() {
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let ext = BreathingExtractor::esp32_default();
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assert_eq!(ext.n_subcarriers, 56);
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}
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}
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