565 lines
20 KiB
Rust
565 lines
20 KiB
Rust
//! Heart rate extraction from CSI phase coherence.
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//!
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//! Uses bandpass filtering (0.8-2.0 Hz) and autocorrelation-based
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//! peak detection to extract cardiac rate from inter-subcarrier
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//! phase data. Requires multi-subcarrier CSI data (ESP32 mode only).
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//!
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//! The cardiac signal (0.1-0.5 mm body surface displacement) is
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//! ~10x weaker than the respiratory signal (1-5 mm chest displacement),
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//! so this module relies on phase coherence across subcarriers rather
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//! than single-channel amplitude analysis.
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use crate::types::{VitalEstimate, VitalStatus};
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use std::collections::VecDeque;
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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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/// Lowest physiologically plausible heart rate, in BPM. Estimates below this
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/// (e.g. a lock onto a breathing harmonic, which the firmware #987 fix also
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/// guards against) are rejected rather than emitted as a confident vital — a
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/// false low HR is a safety problem. Value-identical to the prior literal.
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const HR_PLAUSIBLE_MIN_BPM: f64 = 40.0;
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/// Highest physiologically plausible heart rate, in BPM. Estimates above this
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/// are rejected. Value-identical to the prior literal.
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const HR_PLAUSIBLE_MAX_BPM: f64 = 180.0;
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/// Heart rate extractor using bandpass filtering and autocorrelation
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/// peak detection.
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pub struct HeartRateExtractor {
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/// Per-sample filtered signal history (sliding window; O(1) push/pop).
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filtered_history: VecDeque<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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/// Cardiac band low cutoff (Hz) -- 0.8 Hz = 48 BPM.
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freq_low: f64,
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/// Cardiac band high cutoff (Hz) -- 2.0 Hz = 120 BPM.
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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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/// Minimum subcarriers required for reliable HR estimation.
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min_subcarriers: usize,
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}
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impl HeartRateExtractor {
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/// Create a new heart rate 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: 15).
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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: VecDeque::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: 0.8,
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freq_high: 2.0,
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filter_state: IirState::default(),
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min_subcarriers: 4,
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}
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}
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/// Create with ESP32 defaults (56 subcarriers, 100 Hz, 15 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, 15.0)
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}
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/// Extract heart rate from per-subcarrier residuals and phase data.
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///
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/// - `residuals`: amplitude residuals from the preprocessor.
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/// - `phases`: per-subcarrier unwrapped phases (radians).
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///
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/// Returns a `VitalEstimate` with heart rate in BPM, or `None`
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/// if insufficient data or too few subcarriers.
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pub fn extract(&mut self, residuals: &[f64], phases: &[f64]) -> Option<VitalEstimate> {
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let n = residuals.len().min(self.n_subcarriers).min(phases.len());
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if n == 0 {
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return None;
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}
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// For cardiac signals, use phase-coherence weighted fusion.
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// Compute mean phase differential as a proxy for body-surface
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// displacement sensitivity.
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let phase_signal = compute_phase_coherence_signal(residuals, phases, n);
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// Apply cardiac-band IIR bandpass filter
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let filtered = self.bandpass_filter(phase_signal);
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// Defense-in-depth: a non-finite filter output (e.g. a diverged
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// resonator pole at a pathological sample rate) must never enter the
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// history buffer, or `acf0` would become NaN and the extractor would
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// stall permanently. Mirrors the NaN-bypass guard in ADR-154 §3.
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if !filtered.is_finite() {
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return None;
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}
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// Append to history, enforce window limit. `VecDeque` gives O(1)
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// push_back + pop_front for the sliding window (was a `Vec` with an
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// O(n) `remove(0)` per sample — ADR-157 §A1).
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self.filtered_history.push_back(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.pop_front();
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}
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// Need at least 5 seconds of data for cardiac detection
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let min_samples = (self.sample_rate * 5.0) 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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// Use autocorrelation to find the dominant periodicity. The
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// autocorrelation/peak loop needs a contiguous slice; `make_contiguous`
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// rotates the ring buffer in place once per `extract()` so the slice is
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// free for the rest of this call.
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let history = self.filtered_history.make_contiguous();
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let (period_samples, acf_peak) =
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autocorrelation_peak(history, self.sample_rate, self.freq_low, self.freq_high);
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if period_samples == 0 {
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return None;
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}
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let frequency_hz = self.sample_rate / period_samples as f64;
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let bpm = frequency_hz * 60.0;
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// Validate BPM is in the physiological plausibility band. An estimate
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// outside [HR_PLAUSIBLE_MIN_BPM, HR_PLAUSIBLE_MAX_BPM] is rejected
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// rather than emitted, so an out-of-band autocorrelation lock can never
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// surface as a confident heart rate.
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if !(HR_PLAUSIBLE_MIN_BPM..=HR_PLAUSIBLE_MAX_BPM).contains(&bpm) {
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return None;
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}
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// Confidence based on autocorrelation peak strength and subcarrier count
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let subcarrier_factor = if n >= self.min_subcarriers {
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1.0
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} else {
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n as f64 / self.min_subcarriers as f64
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};
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let confidence = (acf_peak * subcarrier_factor).clamp(0.0, 1.0);
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let status = if confidence >= 0.6 && n >= self.min_subcarriers {
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VitalStatus::Valid
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} else if confidence >= 0.3 {
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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 (cardiac band: 0.8-2.0 Hz).
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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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// Resonator pole radius. The pole magnitude is `|r|`; stability needs
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// `|r| < 1`. When the normalized bandwidth `bw = 2*pi*(f_high-f_low)/fs`
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// exceeds 4 (i.e. a very low `fs` relative to the band width),
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// `1 - bw/2` falls below -1, pushing the pole *outside* the unit circle
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// and diverging the filter exponentially to ±inf. A merely-negative `r`
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// (|r| < 1) is still stable, so the clamp's job is the `|r| >= 1` case.
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// Clamp to a stable range so the pole stays inside the unit circle for
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// any `sample_rate` / band-edge configuration (ADR-157 §A3).
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let r = (1.0 - bw / 2.0).clamp(0.0, 0.9999);
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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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// Self-healing non-finite guard (ADR-158 §A1). A single non-finite
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// sample — a NaN/inf residual from a corrupt CSI frame, or a transient
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// overflow — would otherwise be written into `y1`/`y2` and poison the
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// resonator recurrence *permanently*: every later output stays NaN, the
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// `extract()` finite-check drops it, `acf0` never recomputes on fresh
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// data, and heart-rate extraction is dead until `reset()`. Resetting the
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// filter state here lets the resonator recover on the next clean frame;
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// the 0.0 returned for this frame is still dropped by the caller's
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// `is_finite()` check, so no spurious sample enters history.
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if !output.is_finite() {
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*state = IirState::default();
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return 0.0;
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}
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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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/// Cardiac 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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/// Compute a phase-coherence-weighted signal from residuals and phases.
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///
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/// Combines amplitude residuals with inter-subcarrier phase coherence
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/// to enhance the cardiac signal. Subcarriers with similar phase
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/// derivatives are likely sensing the same body surface.
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fn compute_phase_coherence_signal(residuals: &[f64], phases: &[f64], n: usize) -> f64 {
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if n <= 1 {
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return residuals.first().copied().unwrap_or(0.0);
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}
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// Compute inter-subcarrier phase differences as coherence weights.
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// Adjacent subcarriers with small phase differences are more coherent.
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let mut weighted_sum = 0.0;
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let mut weight_total = 0.0;
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for i in 0..n {
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let coherence = if i + 1 < n {
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let phase_diff = (phases[i + 1] - phases[i]).abs();
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// Higher coherence when phase difference is small
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(-phase_diff).exp()
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} else if i > 0 {
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let phase_diff = (phases[i] - phases[i - 1]).abs();
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(-phase_diff).exp()
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} else {
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1.0
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};
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weighted_sum += residuals[i] * coherence;
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weight_total += coherence;
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}
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if weight_total > 1e-15 {
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weighted_sum / weight_total
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} else {
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0.0
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}
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}
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/// Find the dominant periodicity via autocorrelation in the cardiac band.
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///
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/// Returns `(period_in_samples, peak_normalized_acf)`. If no peak is
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/// found, returns `(0, 0.0)`.
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fn autocorrelation_peak(
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signal: &[f64],
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sample_rate: f64,
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freq_low: f64,
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freq_high: f64,
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) -> (usize, f64) {
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let n = signal.len();
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if n < 4 {
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return (0, 0.0);
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}
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// Lag range corresponding to the cardiac band
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let min_lag = (sample_rate / freq_high).floor() as usize; // highest freq = shortest period
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let max_lag = (sample_rate / freq_low).ceil() as usize; // lowest freq = longest period
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let max_lag = max_lag.min(n / 2);
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if min_lag >= max_lag || min_lag >= n {
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return (0, 0.0);
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}
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// Compute mean-subtracted signal
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let mean: f64 = signal.iter().sum::<f64>() / n as f64;
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// Autocorrelation at lag 0 for normalisation
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let acf0: f64 = signal.iter().map(|&x| (x - mean) * (x - mean)).sum();
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if acf0 < 1e-15 {
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return (0, 0.0);
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}
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// Search for the peak in the cardiac lag range
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let mut best_lag = 0;
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let mut best_acf = f64::MIN;
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for lag in min_lag..=max_lag {
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let acf: f64 = signal
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.iter()
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.take(n - lag)
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.enumerate()
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.map(|(i, &x)| (x - mean) * (signal[i + lag] - mean))
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.sum();
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let normalized = acf / acf0;
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if normalized > best_acf {
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best_acf = normalized;
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best_lag = lag;
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}
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}
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if best_acf > 0.0 {
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(best_lag, best_acf)
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} else {
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(0, 0.0)
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}
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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 = HeartRateExtractor::new(4, 100.0, 15.0);
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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 = HeartRateExtractor::new(2, 100.0, 15.0);
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for _ in 0..10 {
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assert!(ext.extract(&[0.1, 0.2], &[0.0, 0.0]).is_none());
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}
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}
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#[test]
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fn sinusoidal_heartbeat_detected() {
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let sample_rate = 50.0;
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let mut ext = HeartRateExtractor::new(4, sample_rate, 20.0);
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let heart_freq = 1.2; // 72 BPM
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// Generate 20 seconds of simulated cardiac signal across 4 subcarriers
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for i in 0..1000 {
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let t = i as f64 / sample_rate;
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let base = (2.0 * std::f64::consts::PI * heart_freq * t).sin();
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let residuals = vec![base * 0.1, base * 0.08, base * 0.12, base * 0.09];
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let phases = vec![0.0, 0.01, 0.02, 0.03]; // highly coherent
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ext.extract(&residuals, &phases);
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}
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let final_residuals = vec![0.0; 4];
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let final_phases = vec![0.0; 4];
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let result = ext.extract(&final_residuals, &final_phases);
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if let Some(est) = result {
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assert!(
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est.value_bpm > 40.0 && est.value_bpm < 180.0,
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"estimated BPM should be in cardiac range: {}",
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est.value_bpm,
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);
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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 = HeartRateExtractor::new(2, 100.0, 15.0);
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ext.extract(&[0.1, 0.2], &[0.0, 0.1]);
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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 = HeartRateExtractor::new(1, 100.0, 15.0);
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let (low, high) = ext.band();
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assert!((low - 0.8).abs() < f64::EPSILON);
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assert!((high - 2.0).abs() < f64::EPSILON);
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}
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#[test]
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fn autocorrelation_finds_known_period() {
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let sample_rate = 50.0;
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let freq = 1.0; // 1 Hz = period of 50 samples
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let signal: Vec<f64> = (0..500)
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.map(|i| (2.0 * std::f64::consts::PI * freq * i as f64 / sample_rate).sin())
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.collect();
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let (period, acf) = autocorrelation_peak(&signal, sample_rate, 0.8, 2.0);
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assert!(period > 0, "should find a period");
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assert!(acf > 0.5, "autocorrelation peak should be strong: {acf}");
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let estimated_freq = sample_rate / period as f64;
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assert!(
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(estimated_freq - 1.0).abs() < 0.1,
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"estimated frequency should be ~1 Hz, got {estimated_freq}",
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);
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}
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#[test]
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fn phase_coherence_single_subcarrier() {
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let result = compute_phase_coherence_signal(&[5.0], &[0.0], 1);
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assert!((result - 5.0).abs() < f64::EPSILON);
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}
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#[test]
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fn phase_coherence_multi_subcarrier() {
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// Two coherent subcarriers (small phase difference)
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let result = compute_phase_coherence_signal(&[1.0, 1.0], &[0.0, 0.01], 2);
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// Both weights should be ~1.0 (exp(-0.01) ~ 0.99), so result ~ 1.0
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assert!(
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(result - 1.0).abs() < 0.1,
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"coherent result should be ~1.0: {result}"
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);
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}
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#[test]
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fn esp32_default_creates_correctly() {
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let ext = HeartRateExtractor::esp32_default();
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assert_eq!(ext.n_subcarriers, 56);
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}
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/// Pin the physiological plausibility band to its documented values. If a
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/// future edit widens these, an implausible HR could be emitted as a
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/// confident vital — this characterization test forces that to be a
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/// deliberate, reviewed change.
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#[test]
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fn plausibility_band_constants_pinned() {
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assert!((HR_PLAUSIBLE_MIN_BPM - 40.0).abs() < f64::EPSILON);
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assert!((HR_PLAUSIBLE_MAX_BPM - 180.0).abs() < f64::EPSILON);
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}
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/// ADR-158 §A1 bug-catching test: a single non-finite residual must NOT
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/// permanently poison the IIR filter state.
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///
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/// The cardiac resonator latches `y[n]` into `state.y1`/`y2`. Before the
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/// fix, one NaN/inf residual produced a NaN `output` that was stored into
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/// the state; the `extract()` finite-guard dropped that frame from history,
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/// but every subsequent output stayed NaN, so the history buffer never
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/// refilled and HR extraction was dead until `reset()`. After a leading NaN
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/// frame, the OLD code returned `None` with `history_len() == 0` forever.
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/// This asserts recovery (FAILS on the old code).
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#[test]
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fn nan_frame_does_not_permanently_poison_filter() {
|
|
let sr = 50.0;
|
|
let feed_clean = |ext: &mut HeartRateExtractor| {
|
|
let mut last = None;
|
|
for i in 0..1200 {
|
|
let t = i as f64 / sr;
|
|
let base = (2.0 * std::f64::consts::PI * 1.2 * t).sin();
|
|
let r = vec![base * 0.1, base * 0.08, base * 0.12, base * 0.09];
|
|
last = ext.extract(&r, &[0.0, 0.01, 0.02, 0.03]);
|
|
}
|
|
last
|
|
};
|
|
|
|
let mut control = HeartRateExtractor::new(4, sr, 20.0);
|
|
feed_clean(&mut control);
|
|
assert!(control.history_len() > 0, "control clean run must accumulate history");
|
|
|
|
let mut ext = HeartRateExtractor::new(4, sr, 20.0);
|
|
ext.extract(&[f64::NAN, 0.1, 0.1, 0.1], &[0.0, 0.01, 0.02, 0.03]);
|
|
feed_clean(&mut ext);
|
|
assert!(
|
|
ext.history_len() > 0,
|
|
"HR extractor must recover and refill history after a NaN frame (got {})",
|
|
ext.history_len()
|
|
);
|
|
}
|
|
|
|
/// Safety negative: pure broadband noise (no cardiac component) must NOT be
|
|
/// reported as a clinically `Valid` heart rate. A false "HR = 72 bpm" on
|
|
/// noise is a safety problem (false reassurance / false alert). The
|
|
/// extractor may still emit a low-confidence guess, but its status must be
|
|
/// `Degraded`/`Unreliable`, never `Valid`. Mirrors the honest-negative
|
|
/// requirement in the review brief.
|
|
#[test]
|
|
fn pure_noise_is_never_reported_valid() {
|
|
let mut seed: u64 = 0x1234_5678;
|
|
let mut rng = || {
|
|
seed = seed
|
|
.wrapping_mul(6_364_136_223_846_793_005)
|
|
.wrapping_add(1_442_695_040_888_963_407);
|
|
((seed >> 33) as f64 / (1u64 << 31) as f64) - 1.0
|
|
};
|
|
let mut ext = HeartRateExtractor::new(8, 50.0, 20.0);
|
|
let mut last = None;
|
|
for _ in 0..1500 {
|
|
let r: Vec<f64> = (0..8).map(|_| rng()).collect();
|
|
let p: Vec<f64> = (0..8).map(|_| rng()).collect();
|
|
last = ext.extract(&r, &p);
|
|
}
|
|
if let Some(est) = last {
|
|
assert_ne!(
|
|
est.status,
|
|
VitalStatus::Valid,
|
|
"pure noise must not yield a clinically Valid HR (bpm={}, conf={})",
|
|
est.value_bpm,
|
|
est.confidence
|
|
);
|
|
assert!(
|
|
est.confidence < 0.6,
|
|
"noise HR confidence must stay below the Valid cutoff: {}",
|
|
est.confidence
|
|
);
|
|
}
|
|
}
|
|
|
|
/// ADR-157 §A3 bug-catching test.
|
|
///
|
|
/// Divergence needs the pole *magnitude* `|r| >= 1`, i.e. `bw >= 4`. With
|
|
/// the cardiac band widened to 0.1-0.9 Hz at `fs = 0.5` Hz,
|
|
/// `bw = 2*pi*(0.9-0.1)/0.5 = 10.05`, so the OLD pole radius
|
|
/// `r = 1 - bw/2 = -4.03` has `|r| = 4.03 > 1` — the filter diverges
|
|
/// exponentially. After ~600 unit-step frames the OLD output overflows f64
|
|
/// to ±inf/NaN; once that lands in `filtered_history`, `acf0` becomes NaN
|
|
/// and the extractor stalls permanently. The clamp (`r.clamp(0.0, 0.9999)`)
|
|
/// plus the finite-guard before the push keep every accumulated sample
|
|
/// finite. This test FAILS on the old code (verified by reverting).
|
|
#[test]
|
|
fn low_sample_rate_filter_stays_finite() {
|
|
let mut ext = HeartRateExtractor::new(4, 0.5, 3600.0);
|
|
ext.freq_low = 0.1;
|
|
ext.freq_high = 0.9;
|
|
// Feed a unit step across 4 coherent subcarriers for 600 frames — enough
|
|
// for the un-clamped resonator to overflow to inf.
|
|
for _ in 0..600 {
|
|
ext.extract(&[1.0, 1.0, 1.0, 1.0], &[0.0, 0.01, 0.02, 0.03]);
|
|
}
|
|
assert!(
|
|
ext.history_len() > 0,
|
|
"history should have accumulated samples"
|
|
);
|
|
for (i, &v) in ext.filtered_history.iter().enumerate() {
|
|
assert!(v.is_finite(), "filtered_history[{i}] must be finite, got {v}");
|
|
}
|
|
}
|
|
}
|