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QIF-T0078

high

LiDAR remote pulse detection (laser Doppler vibrometry for cardiac waveform extraction)

Tier 5 — Theoretical (Modeled / Simulated)

Legacy status: THEORETICAL

The iPhone LiDAR scanner uses a VCSEL (vertical-cavity surface-emitting laser) array emitting pulsed 940nm infrared laser light and a SPAD (single-photon avalanche diode) detector array measuring time-of-flight. In normal operation, it measures depth for AR applications. However, the same hardware can function as a simplified laser Doppler vibrometer (LDV): when the laser beam reflects off skin, the pulse wave from cardiac activity causes micro-vibrations (amplitude ~1-10 µm) on the skin surface. These vibrations create measurable Doppler shifts or time-of-flight variations in the reflected laser signal. Extracting the cardiac pulse waveform from LiDAR data requires raw access to the SPAD photodetector output (timing resolution in picoseconds) rather than the processed depth map. This requires either a jailbreak, hardware teardown, or compromised firmware. The extracted pulse waveform contains: heart rate, heart rate variability (HRV), pulse transit time (correlated with blood pressure), and potentially cardiac arrhythmia signatures. Unlike QIF-T0075 (ultrasonic sonar), this is optical and directional, requiring line-of-sight but working at greater precision for skin-surface vibrations. Range is limited to ~5m (LiDAR operational range) but could be extended with higher-power laser sources.

Technique Details

Tactic
QIF-S.HV
Status
THEORETICAL
Bands
S1, S2, S3

Therapeutic Application

iPhone VCSEL LiDAR array measures skin surface micro-vibrations via Doppler shift in reflected 940nm laser; pulse waveform extracted from raw SPAD photodetector timing data

Clinical Analog

Laser Doppler vibrometry for contactless cardiac monitoring

Treats

  • contactless vital sign monitoring in burn units
  • neonatal heart rate monitoring (no adhesive sensors)
  • remote triage in mass casualty events
  • sleep lab cardiac monitoring

Neural Impact

3 of 7 neural bands affected

S1 S2 S3

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Scoring

NISS v1.1 NISS:1.1/BI:N/CR:N/CD:N/CV:E/RV:F/NP:N
CVSS v4.0 CVSS:4.0/AV:L/AC:H/AT:P/PR:H/UI:N/VC:H/VI:N/VA:N/SC:L/SI:N/SA:N
1.4Low
BICRCDCVRVNP
 

Governance

Neurorights at Risk

This technique threatens 2 of the 4 proposed neurorights (Ienca & Andorno, 2017).

Consent Complexity
0.48 / 4.0

FDORA §3305 Compliance

Cyber Device
Regulatory Coverage
0.5 / 1.0
524B Requirements
TM VA SBOM SA PM
Regulatory Gaps
  • ! CVSS partially captures risk; neural dimensions missing
  • ! Threat not yet in regulatory threat catalogs

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) 1.4 1.4 Low -
Child (10yr) + ADHD 1.4 1.6 Low +0.25
Adult with ALS 1.4 1.6 Low +0.23

Validation Status

Theoretical / Not yet validated. This technique has not been independently tested. See the validation dashboard for what has been tested.

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