wifi-densepose/examples
rUv 2e89fe61ef
research(R6.2.4): 3D chest-centric N-anchor — validates R6.2.2.1 prediction with refinement (#728)
Composes R6.2.2.1 (3D N-anchor) with R6.2.3 (chest-centric zones).
Tests R6.2.2.1's prediction: 'switching to chest-centric should recover
80%+ coverage at N=5 in 3D.'

Result: 3D chest-centric N=5 = 76.8% (close to but below 80%);
        3D chest-centric N=6 = 81.6% (knee shifts one anchor higher).

4-way comparison at N=5:
- R6.2.2 (2D body):    96.8%
- R6.2.3 (2D chest):   82.4%
- R6.2.2.1 (3D body):  49.4%
- R6.2.4 (3D chest):   76.8%

3D chest recovers 27 pp of the 47 pp gap R6.2.2.1 surfaced. Most of
the architectural fix works.

COUNTER-FINDING: no ceiling anchors selected for chest-centric zones.
Greedy picks 100% low (0.8 m) + mid (1.5 m). R6.2.1's 'include ceiling'
recommendation was correct for full-body coverage, NOT chest-centric.

Sharpened recommendation: anchor heights should match target-zone heights.
- Bed-only (z=0.3-0.6):       Low only
- Chair sitting (z=0.5-1.0):  Low + mid
- Standing chest (z=1.2-1.5): Mid only
- Mixed chest (z=0.3-1.5):    Low + mid (NO ceiling)
- Full body (z=0.3-1.7):      Low + mid + high

FINAL ADR-029 anchor-count table (4-axis dimension x zone-mode):
- 2D body-centric:    N=5  -> 97%
- 2D chest-centric:   N=5  -> 82%
- 3D body-centric:    N=7-8 -> 65%+
- 3D chest-centric:   N=6  -> 82%   <- recommended for vital-signs cogs

For vital-signs cogs in real 3D deployments: N=6 + chest-centric +
low/mid anchor heights. This is the strongest single placement
recommendation the R6 family produces.

R6 family substantively complete after this tick (8 ticks total):
R6, R6.1, R6.2, R6.2.1, R6.2.2, R6.2.2.1, R6.2.3, R6.2.4.

Second self-corrective tick of the loop: R6.2.2.1 predicted 80%; actual
is 76.8%. Self-correction documented (prediction was 3.2 pp optimistic,
knee shifts to N=6). Integrity pattern continues.

Honest scope:
- Greedy + 4 restarts (N=5 likely 2-4 pp shy of true global optimum)
- 0.1 m grid, single 5x5x2.5 geometry
- Three chest zones; multi-subject = future
- R6.2.1's ceiling rec was for full-body, not invalidated -- refined

Composes:
- R6.2.1 / R6.2.2 / R6.2.2.1 (same physics, different zones)
- R6.2.3 motivated this tick
- R7 / ADR-029 / ADR-105 (N=6 still byzantine-safe)
- R14 V1/V2/V3 (chest + N=6 = deployment recipe)

Coordination: ticks/tick-25.md, no PROGRESS.md edit.
2026-05-22 05:12:48 -04:00
..
environment feat: 4 sensing examples — sleep apnea, stress, room environment 2026-03-15 16:50:04 -04:00
happiness-vector chore(repo): rename rust-port/wifi-densepose-rs → v2/ (flatten to one level) (#427) 2026-04-25 21:28:13 -04:00
medical feat: 10-in-1 medical vitals suite from single mmWave sensor 2026-03-15 18:05:42 -04:00
research-sota research(R6.2.4): 3D chest-centric N-anchor — validates R6.2.2.1 prediction with refinement (#728) 2026-05-22 05:12:48 -04:00
sleep feat: 4 sensing examples — sleep apnea, stress, room environment 2026-03-15 16:50:04 -04:00
stress feat: 4 sensing examples — sleep apnea, stress, room environment 2026-03-15 16:50:04 -04:00
three.js fix(three.js): graceful banner when X Bot.fbx 404s on gh-pages (#651) 2026-05-19 18:43:21 -04:00
README.md feat: 10-in-1 medical vitals suite from single mmWave sensor 2026-03-15 18:05:42 -04:00
ruview_live.py feat: happiness scoring pipeline + ESP32 swarm with Cognitum Seed (#285) 2026-03-20 18:46:34 -04:00

README.md

Examples

Real-time sensing applications built on the RuView platform.

Unified Dashboard (start here)

pip install pyserial numpy
python examples/ruview_live.py --csi COM7 --mmwave COM4

The live dashboard auto-detects available sensors and displays fused vitals, environment data, and events in real-time. Works with any combination of sensors.

Individual Examples

Example Sensors What It Does
ruview_live.py CSI + mmWave + Light Unified dashboard: HR, BR, BP, stress, presence, light, RSSI
Medical: Blood Pressure mmWave Contactless BP estimation from HRV
Medical: Vitals Suite mmWave 10-in-1: HR, BR, BP, HRV, sleep stages, apnea, cough, snoring, activity, meditation
Sleep: Apnea Screener mmWave Detects breathing cessation events, computes AHI
Stress: HRV Monitor mmWave Real-time stress level from heart rate variability
Environment: Room Monitor CSI + mmWave Occupancy, light, RF fingerprint, activity events

Hardware

Port Device Cost What It Provides
COM7 ESP32-S3 (WiFi CSI) ~$9 Presence, motion, breathing, heart rate (through walls)
COM4 ESP32-C6 + Seeed MR60BHA2 ~$15 Precise HR/BR, presence, distance, ambient light

Either sensor works alone. Both together enable fusion (mmWave 80% + CSI 20%).

Quick Start

pip install pyserial numpy

# Unified dashboard (recommended)
python examples/ruview_live.py --csi COM7 --mmwave COM4

# Blood pressure estimation
python examples/medical/bp_estimator.py --port COM4

# Sleep apnea screening (run overnight)
python examples/sleep/apnea_screener.py --port COM4 --duration 28800

# Stress monitoring (workday session)
python examples/stress/hrv_stress_monitor.py --port COM4 --duration 3600

# Room environment monitor
python examples/environment/room_monitor.py --csi-port COM7 --mmwave-port COM4

# CSI only (no mmWave)
python examples/ruview_live.py --csi COM7 --mmwave none