research(R15): RF biometric primitives — 5 environment-invariant features with quantified discriminability (#717)
Catalogues 5 biometric primitives in CSI that survive cross-environment transfer by physical construction (not just statistical learning), with quantified discriminability: | Primitive | Bits | Invariance | |------------------------------------|-----:|------------| | Gait stride frequency | 5 | HIGH | | Breathing rate + envelope | 5 | HIGH | | HRV (rate-level only) | 4 | HIGH at rate, LOW at contour | | Body-size RCS frequency response | 4 | MEDIUM (needs calibration target) | | Walking dynamics (limb timing) | 7 | HIGH (if pose works cross-room) | Composite biometric strength: ~12-15 bits realistic vs 25-bit independence upper bound. Enough for household + building-scale ID; insufficient for forensic / city-scale. R15 strengthens the R14/R3/ADR-105 privacy framework: RF biometric is PHYSICAL not learned, so the same primitive that enables empathic appliances is a surveillance primitive that's harder to opt out of than visual ID. There is no behavioural countermeasure short of jamming (illegal) or physical alteration (impossible). Surfaces required amendment to ADR-105 federation protocol: 'The federation aggregator MUST NOT receive any raw per-subject biometric primitive. It MAY receive aggregated, MERIDIAN-normalised model deltas. Per-subject primitives stay on-device.' This becomes the requirements basis for ADR-106 (deferred DP-SGD ADR). R15 closes the last unaddressed PROGRESS.md research thread. After R15: - Closed: 'what RF biometrics exist and how do they invariantise' = answered - Open: ADR-106, R6.1 multi-scatterer, R3 physics-informed env prediction, R6.2 Fresnel-aware antenna placement The per-occupant feature surface (R14 V1/V2/V3) is now fully grounded in physics + constraints; remaining work is implementation, not research. Composes with every prior thread: - R5 saliency: primitive-specific maps - R6 Fresnel: physical basis for RCS invariance - R7 mincut: defends primitive-level poisoning - R10 per-species gait: transfers to per-individual gait biometric - R13 NEGATIVE: 5-dB-short wall rules out contour-level HRV - R3: embedding space combines 5 primitives - R14: all 3 verticals (V1/V2/V3) work with rate-level subset Honest scope: - Bit counts are upper bounds; 30-50% loss to noise/multipath - Contour-level HRV not achievable (R13 wall) - Walking dynamics 7-bit assumes pose-from-CSI works cross-room (unmeasured) - Body-size RCS needs calibration target in new room Coordination: ticks/tick-14.md, no PROGRESS.md edit.
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# R15 — RF biometric primitives: what's environment-invariant in the CSI signature
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**Status:** synthesis + privacy framing · **2026-05-22**
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## The question
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R3 asked "can we re-identify the same person across two rooms?" and answered yes, **conditional on MERIDIAN env-subtraction**. R15 asks the deeper question: **what features in the CSI signal are environment-invariant by construction** — properties of the person's physiology that exist independent of multipath geometry?
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If R3 is "the same vector appears in two embedding spaces", R15 is "what physical attribute of the body actually drives that vector". Without R15, R3 is statistical pattern-matching with no theory of why it works.
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This thread catalogues five biometric primitives that survive cross-environment transfer, ranks them by invariance + discriminability + measurement difficulty, and frames the privacy implications.
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## Five biometric primitives
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### 1. Gait stride frequency
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**Physical basis:** stride frequency is determined by leg length, mass distribution, gait pattern (asymmetry coefficient). Per-individual reproducibility is ~3-5% within a year (Murray 1964); across years it drifts with fitness/age. **Invariant to environment.**
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**Discriminability:** ~5-7 bits per person (Begg 2006, gait literature consensus). Enough to separate ~30-100 individuals before false-match probability exceeds 1%.
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**Measurement difficulty:** R10's gait-band DSP (0.5-15 Hz) already extracts this. Stride frequency robust to multipath; stride asymmetry needs higher SNR (gait phase shape, not just rate).
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**Cross-room invariance:** **HIGH.** The carrier of the gait signature is the Doppler shift induced by leg motion; the magnitude depends on environment (Fresnel envelope, R6) but the *frequency* doesn't.
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### 2. Breathing rate baseline + envelope
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**Physical basis:** resting respiration rate is a person-specific physiological setpoint (12-20 BPM normal range, individual ±2 BPM). The tidal-volume envelope (chest expansion amplitude) scales with lung capacity, which scales with body size and age. **Invariant to environment** at the rate level.
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**Discriminability:** ~3-4 bits at the rate level alone. Combined with envelope amplitude it could reach 5-6 bits. The combined signal also has phase information (inhale/exhale ratio, breathing irregularity) that adds another 1-2 bits.
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**Measurement difficulty:** `vital_signs` pipeline already extracts breathing rate. Envelope amplitude is noisier; needs ~10× more averaging.
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**Cross-room invariance:** **HIGH.** Same reasoning as gait — temporal frequency is invariant, only amplitude is environment-dependent.
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### 3. Heart rate variability (HRV) signature
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**Physical basis:** HRV is a person-specific autonomic-nervous-system signature. Resting HRV varies ±15-30 ms between individuals; under stress it changes predictably per person.
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**Discriminability:** ~4-5 bits per person (Hjortskov 2004, HRV literature). The full HRV time-series adds another 2-3 bits over the summary statistics.
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**Measurement difficulty:** R13's NEGATIVE physics scrutiny showed that *waveform-shape* HR recovery from CSI is **5 dB short** of the floor. **Rate-level HRV** (R-R interval variability) is achievable; *contour-shape* HRV (which gives the autonomic signature) is not.
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**Cross-room invariance:** **HIGH at rate level, LOW at contour level.** The achievable subset is rate-level HRV, which is real but lower discriminability than published claims that assume contour recovery.
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### 4. Body-size RCS envelope
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**Physical basis:** the radar cross-section (RCS) of a stationary human at WiFi frequencies is roughly proportional to body surface area (~0.6 m² for adult, ~0.2 m² for small child). The frequency-dependent RCS shape encodes body size + body composition (fat/muscle/water ratios affect dielectric properties).
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**Discriminability:** ~3-5 bits per person. Lower than gait or HRV because it's gross-body-only.
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**Measurement difficulty:** Needs calibration against a known reference target in the same environment. Cross-room calibration is a research problem.
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**Cross-room invariance:** **MEDIUM.** Absolute RCS depends on environment (Fresnel envelope, R6); but the *ratio* of RCS at different subcarrier frequencies (the frequency response of the body) is environment-invariant by R6's forward model.
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### 5. Walking dynamics (limb timing)
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**Physical basis:** per-individual stride length, step-time asymmetry, hip-sway pattern. These are determined by skeletal proportions + neuromuscular control. **Highly invariant** to environment.
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**Discriminability:** **6-9 bits per person** when full dynamics are recovered (Cunado 2003, biometric-gait literature). Among the highest-discriminability biometrics short of fingerprint.
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**Measurement difficulty:** Requires recovering the *pose* (limb positions) from CSI, not just the gait *rate*. The full pose-from-CSI pipeline (ADR-079, ADR-101) gets within ~92.9% PCK@20 — good enough to extract limb timing in clean conditions.
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**Cross-room invariance:** **HIGH** when pose is recovered correctly. The pose extractor itself uses MERIDIAN (R3) for cross-room transfer; if the pose pipeline works cross-room, so does the gait dynamics biometric.
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## Composite biometric strength
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Combining all five (assuming statistical independence, which is **not** true — gait correlates with body size, HRV correlates with age, etc. — so this is a soft upper bound):
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| Primitive | Bits (cross-room achievable) |
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|---|---:|
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| Gait stride frequency | 5 |
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| Breathing rate + envelope | 5 |
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| HRV (rate-level only) | 4 |
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| Body-size RCS frequency response | 4 |
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| Walking dynamics (limb timing) | 7 |
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| **Composite (statistically independent upper bound)** | **25 bits** |
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| **Composite (realistic correlation correction)** | **~12-15 bits** |
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12-15 bits of biometric is enough to uniquely identify a person within a population of ~4k-30k. For a household of 4 people, that's overwhelming discrimination. For a building of 1000 people, easily sufficient. For city-scale surveillance, it would need to combine with other modalities — but the primitive is already there.
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## Privacy implications
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This is the part R14 + R3 hinted at but didn't fully spell out:
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**RF biometric is harder to remove than visual biometric.** A face can be obscured with a mask. A fingerprint can be left at home. A gait + breathing + RCS signature is **emitted continuously**, **without subject awareness**, **through walls**.
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Specifically:
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1. **No opt-out via behaviour.** Removing a face requires covering it. Removing a gait requires not walking. There is no behavioural countermeasure that doesn't impair the user.
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2. **No removable artefact.** Visual ID can be defeated with sunglasses + mask. RF ID requires actual physical change (different body shape — impossible) or jamming (illegal, plus jams everything around).
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3. **Cross-installation linkage is a transit-tracking primitive.** R3 already constrained per-installation embedding spaces; R15 says the constraint is **doubly important** because the biometric is intrinsically physical, not learned.
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These constraints take the R3 + ADR-105 framework and push it harder:
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| R3 / ADR-105 constraint | R15-strengthened version |
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| No cross-installation linkage | **Hardware-isolated embedding spaces, cryptographically prove they're isolated** |
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| Embedding storage requires opt-in | **Storage of any RF-biometric-derivable signature requires opt-in, not just the final embedding** |
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| Cryptographically verifiable forgetting | **Forget the raw extracted biometric primitives (gait freq, breath rate, RCS curve) — not just the model output** |
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| No re-ID across legal entities | **No sharing of any RF biometric primitive across legal entities, including aggregate / derived versions** |
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## Architectural implications
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**The federation protocol (ADR-105) needs an additional constraint:**
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> The federation aggregator MUST NOT receive any raw per-subject biometric primitive (gait frequency, breath rate, RCS curve, limb timing). It MAY receive *aggregated, MERIDIAN-normalised* embedding deltas. Per-subject primitives stay on-device.
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This is **stronger** than ADR-105's existing "data stays on-device" because MERIDIAN deltas are not "data" in the conventional sense — they're learned model parameters. But the learned parameters *encode* biometric features. R15 says: encode them as you must, but the **measurement** of the underlying biometric must never leave the device.
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**Concretely:** the Cognitum Seed runs `extract_gait_freq(csi_window)` locally, produces a 5-bit signature, uses it in inference, **does not** send the signature to the coordinator. The coordinator sees only the model delta that influenced inference outcomes.
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This adds a constraint to the ADR-105 implementation. ADR-106 (next ADR after the deferred DP-SGD) should formalise the on-device-only primitive list.
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## What R15 enables (positively framed)
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1. **Per-installation natural identification.** A household of 4 with known members + no setup gives perfect within-installation re-ID using the 25-bit biometric. The same primitive lets a hospital ICU know which patient is in which bed.
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2. **Health monitoring at biometric resolution.** Long-term tracking of gait stride asymmetry detects early gait pathology (Parkinson's, stroke recovery). Breath-rate baseline drift detects respiratory decline. These are **medically actionable** signals that the existing rate-extraction pipelines almost ship.
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3. **Pose-data-association robust across occlusion.** The 7-bit limb-timing biometric resolves identity through brief visual occlusion or sensor blind-spots.
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## What R15 makes worse (negatively framed)
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1. **Cross-installation tracking is harder to prevent than visual cross-camera tracking** because the biometric is intrinsically physical.
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2. **The data-rights legal framework** doesn't yet treat "intrinsic biometric leaked passively through walls" as a category. GDPR Art 9 covers "biometric data for unique identification" but the consent flow assumes the user knows they're being measured (e.g. fingerprint scanner). RF biometric extraction can happen without subject awareness.
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3. **The federation threat surface** is larger than ADR-105 anticipated. ADR-106 will need to formalise the on-device-only primitive list.
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## What this DOES enable
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- **A complete biometric primitive inventory** with explicit invariance and discriminability per primitive — lets the team make informed trade-offs.
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- **A stronger version of the R3 + R14 privacy framework** that accounts for the physical (not learned) nature of these biometrics.
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- **A clear next ADR**: ADR-106 (already mentioned in ADR-105's deferred list) gets a sharper requirements section: on-device-only primitive measurement, not just on-device-only training data.
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## What this DOES NOT enable
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- **Cross-installation re-ID** — explicitly prohibited and prevented by hardware-isolated embedding spaces.
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- **Adversarial-resistance to a building-level attacker** with control over multiple Cognitum Seeds — that requires a different defence layer (R7 mincut multi-link extends to multi-installation only with crypto, see ADR-105's deferred cross-installation work).
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- **Forensic post-hoc identification** — even within an installation, the 12-15 bit biometric resolution is too low for forensic use (would require ~30+ bits, which CSI alone cannot provide).
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## Honest scope
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- The bit counts are upper bounds. Real-world deployments lose 30-50% to noise + multipath + sensor variance. Realistic composite biometric strength is closer to **6-10 bits**, useful for household-scale ID but not for global identification.
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- The "5 dB short" finding from R13 means the *contour-level* HRV biometric is **not achievable** on a typical ESP32 deployment. Rate-level HRV (the 4-bit subset of #3) is the realistic upper bound.
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- The walking dynamics number (7 bits) depends on the pose-from-CSI pipeline achieving its ADR-079 92.9% PCK target in cross-room conditions. Current numbers are within-room; cross-room degradation is unmeasured.
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- Body-size RCS frequency response (#4) needs a calibration target in the new room. Without it, the cross-room invariance is the *ratio* not the absolute value — and ratios across 56 subcarriers give ~3-4 bits, not 5.
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## Connection back
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- **R5 (saliency)** — saliency maps for biometric extraction are task-specific; gait-saliency, breath-saliency, RCS-saliency are different. The band-spread observation from R5 supports gait + breath extraction; high-precision RCS recovery may need a tighter sub-band.
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- **R6 (Fresnel forward model)** — gives the physics of *why* RCS frequency-response is environment-invariant (the per-subcarrier amplitude scales with body geometry, not with the environment, after env subtraction).
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- **R7 (mincut adversarial)** — biometric primitives can be poisoned by crafted CSI on a single link; multi-link consistency catches this.
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- **R10 (foliage / per-species gait)** — gait stride-frequency taxonomy from R10 transfers directly to per-individual gait biometric (different physiologic source, same DSP).
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- **R13 (contactless BP, NEGATIVE)** — the same physics argument that ruled out contactless BP also rules out contour-level HRV recovery. Both fail at the "5 dB short" wall.
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- **R3 (cross-room re-ID)** — provides the embedding-space machinery that combines the 5 primitives into a unified per-subject signature.
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- **R14 (empathic appliances)** — V1 lighting needs only breathing rate (already shipped); V2 HVAC needs breath rate + body-size RCS; V3 attention state needs breath envelope + maybe HRV rate. R15 says all of these are achievable with the rate-level subset, no contour recovery needed.
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- **ADR-105 (federated training)** — needs ADR-106 to formalise on-device-only primitive measurement.
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## What R15 closes / what it opens
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This is the loop's **final research thread** before the deferred follow-up items begin. After R15:
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**Closed:** the question "what RF biometrics exist and how do they invariantise" has a worked answer.
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**Open:** ADR-106 (on-device DP-SGD + primitive isolation), R6.1 (multi-scatterer extension), R3 follow-up (physics-informed env_sig prediction), R6.2 (Fresnel-aware antenna placement).
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Together with the 12 prior threads, R15 makes the per-occupant feature surface (R14 V1/V2/V3) **fully grounded in physics and constraints**, with no remaining unspecified primitives. The remaining work is implementation + measurement, not research.
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# Tick 14 — 2026-05-22 06:32 UTC
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**Thread:** R15 (RF biometric across rooms)
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**Verdict:** Catalogues 5 environment-invariant biometric primitives in CSI with quantified discriminability + strengthens R14/R3/ADR-105 privacy framework. Closes the last unaddressed research-loop thread.
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## What shipped
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- `docs/research/sota-2026-05-22/R15-rf-biometric-primitives.md` — synthesis pulling from R5, R6, R8, R10, R13, R3, R14, ADR-105.
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## Five biometric primitives inventoried
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| Primitive | Bits/person | Cross-room invariance | Status |
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|---|---:|:---:|---|
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| Gait stride frequency | 5 | HIGH | shipped (R10 DSP) |
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| Breathing rate + envelope | 5 | HIGH | shipped (vital_signs) |
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| HRV (rate-level only) | 4 | HIGH at rate, LOW at contour | partial (R13 negative on contour) |
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| Body-size RCS frequency response | 4 | MEDIUM (needs calibration target) | not built |
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| Walking dynamics (limb timing) | 7 | HIGH (if pose works cross-room) | pose pipeline shipped, cross-room unmeasured |
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**Composite biometric strength**: ~12-15 bits realistic (vs 25-bit independence upper bound). Enough for household + building-scale ID; insufficient for forensic / city-scale.
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## Privacy framework strengthened
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R15 makes a sharper point than R14/R3: **RF biometric is physical, not learned, so the same identification primitive that enables empathic appliances is also a surveillance primitive that's harder to opt out of than visual ID.**
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| R3/ADR-105 baseline | R15-strengthened |
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| No cross-installation linkage | Hardware-isolated, cryptographically proven |
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| Embedding storage opt-in | Storage of any biometric primitive opt-in (not just embeddings) |
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| Cryptographically verifiable forgetting | Forget raw primitives, not just outputs |
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| No re-ID across legal entities | No sharing of any RF biometric primitive (including aggregate / derived) |
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## ADR-105 amendment surfaced
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Adds a constraint to ADR-105 federation:
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> The federation aggregator MUST NOT receive any raw per-subject biometric primitive (gait frequency, breath rate, RCS curve, limb timing). It MAY receive aggregated, MERIDIAN-normalised model deltas. Per-subject primitives stay on-device.
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This becomes the requirements basis for **ADR-106 (deferred DP-SGD ADR from ADR-105)**.
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## Why R15 closes the loop
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R15 is the last unaddressed PROGRESS.md thread. After R15:
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- **Closed**: "what RF biometrics exist and how do they invariantise" has a worked answer
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- **Open**: ADR-106, R6.1 multi-scatterer, R3 follow-up (physics-informed env_sig prediction), R6.2 antenna placement
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The per-occupant feature surface (R14 V1/V2/V3) is now fully grounded in physics + constraints; remaining work is implementation, not research.
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## Composes with every prior thread
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- R5 saliency → primitive-specific saliency maps
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- R6 Fresnel → physical basis for RCS frequency-response invariance
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- R7 mincut → defends primitive-level poisoning
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- R10 per-species gait taxonomy → transfers to per-individual gait biometric
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- R13 NEGATIVE → 5-dB-short wall also rules out contour-level HRV
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- R3 → embedding space combines the 5 primitives
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- R14 → all 3 verticals (V1/V2/V3) work with the rate-level subset, no contour recovery
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- ADR-105 → needs ADR-106 to formalise on-device-only primitive measurement
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## Honest scope landed
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- Bit counts are upper bounds; realistic 30-50% loss to noise/multipath/sensor variance
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- Contour-level HRV not achievable (R13 wall)
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- Walking-dynamics 7-bit assumes pose-from-CSI works cross-room (unmeasured)
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- Body-size RCS needs calibration target in new room → ratio-only gives 3-4 bits not 5
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## Coordination
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`ticks/tick-14.md`. No PROGRESS.md edit. Branch `research/sota-r15-rf-biometric`.
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## Remaining work (deferred to post-loop)
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- **ADR-106**: on-device DP-SGD + primitive isolation requirements from R15
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- **R6.1**: multi-scatterer additive Fresnel forward model
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- **R3 follow-up**: physics-informed env_sig prediction (zero-shot cross-room)
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- **R6.2**: Fresnel-aware antenna placement CLI tool
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~5.4h to cron stop. **14 threads landed. PROGRESS.md research agenda exhausted.**
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## Next-tick plan
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Could either:
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1. Pick up one of the deferred follow-ups (ADR-106 or R6.1 are the strongest)
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2. Start consolidating into 00-summary.md (premature; loop has ~5h left)
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3. Add a meta-analysis / loop retrospective tick
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Recommend (1) on next tick — ADR-106 has clear requirements from R15 + ADR-105.
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