QIF-T0090
criticalWiFi CSI passive body sensing (through-wall vital signs, 3D pose reconstruction, respiratory and gait biometric inference via dedicated or commodity WiFi hardware)
Tier 3 — Demonstrated (Lab-proven)
Legacy status: DEMONSTRATED
WiFi Channel State Information (CSI) captures the multipath propagation characteristics between WiFi transmitter and receiver. Human body movements — including breathing (chest wall motion ~5mm), heartbeat (body surface vibration ~0.1mm), and walking — modulate the WiFi signal propagation paths. Two attack profiles: (1) DEDICATED HARDWARE — modified firmware on CSI-capable APs enables through-wall sensing (2-3 standard walls), 3D pose reconstruction, and multi-person vital sign extraction at up to 8m range. (2) CONSUMER-GRADE — standard WiFi chipsets (Intel 5300, Atheros, ESP32) with CSI-enabled drivers extract respiratory rate (±1 bpm at 3m) and gait identity (93% single-person, 78% multi-person) without dedicated hardware. Respiratory modulation: phase shift Δφ = 4π×Δd/λ ≈ 0.4-1.2 radians at 5 GHz (chest displacement 4-12mm). Gait produces Doppler shifts f_d = 2v×cos(θ)/λ ≈ 40 Hz at walking speed. CSI matrix: H(f,t) ∈ C^(N_tx × N_rx × N_sub). CRITICAL REGULATORY GAP: Respiratory rate = PHI under HIPAA (45 CFR 160.103) when linked to individual. Gait biometric = special category data under GDPR Art. 9. No consent mechanism exists for incidental WiFi CSI health data collection — a router collecting CSI for 'network optimization' simultaneously collects respiratory data from everyone in range. This is passive radar using existing infrastructure.
Technique Details
- Tactic
- QIF-S.HV
- Status
- DEMONSTRATED
- Bands
- S1, S2, S3
✚ Therapeutic Application
WiFi OFDM subcarrier amplitude and phase modulation by human body movement, respiration, and gait; works through walls without any device on the target; both dedicated CSI hardware and commodity WiFi chipsets enable contactless physiological surveillance
Clinical Analog
Contactless vital sign monitoring for sleep studies, elder care, and post-surgical recovery
Treats
- contactless sleep apnea detection (Liu et al. 2015, demonstrated ±1 bpm)
- elderly fall detection and activity monitoring (no wearable required)
- post-surgical respiration monitoring without chest bands (burn patients)
- PTSD and anxiety monitoring via nocturnal breathing pattern analysis
- COPD exacerbation early warning via respiratory pattern changes
- Parkinson's gait analysis for medication timing optimization
- smart home health sensing
Neural Impact
3 of 7 neural bands affected
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Scoring
NISS:1.1/BI:N/CR:N/CD:N/CV:I/RV:F/NP:N CVSS:4.0/AV:A/AC:L/AT:P/PR:H/UI:N/VC:H/VI:N/VA:N/SC:H/SI:N/SA:N Governance
Neurorights at Risk
This technique threatens 2 of the 4 proposed neurorights (Ienca & Andorno, 2017).
FDORA §3305 Compliance
- ! CVSS partially captures risk; neural dimensions missing
- ! No FDA pathway for consumer sensor exploitation
Population Vulnerability
CRB vulnerability adjustment (γ=0.30) accounts for age, diagnosis severity, consent capacity, and device dependency.
| Population | NISS Base | Adjusted | Severity | Delta |
|---|---|---|---|---|
| Adult (Default) | 2.0 | 2.0 | Low | - |
| Child (10yr) + ADHD | 2.0 | 2.4 | Low | +0.35 |
| Adult with ALS | 2.0 | 2.3 | Low | +0.32 |
Validation Status
Theoretical / Not yet validated. This technique has not been independently tested. See the validation dashboard for what has been tested.