bac6962689
Extends R6's point-scatterer to distributed-body model (6 scatterers: head + chest + 2 arms + 2 legs). Combined CSI = coherent sum of per-body-part contributions. Headline finding: 5 m link, 2.4 GHz, subject 25 cm off LOS, breathing at 0.25 Hz with 8 mm chest amplitude: | Configuration | Breathing SNR (best subcarrier) | |----------------------------------------|--------------------------------:| | Single-scatterer ideal (R6) | +23.7 dB | | Multi-scatterer realistic (R6.1) | +19.0 dB | | MULTI-SCATTERER PENALTY | +4.7 dB | This 4.7 dB penalty matches R13's 5-dB-shortfall finding to within 0.3 dB. R13 NEGATIVE concluded that pulse-contour recovery needs +25 dB SNR, only +20 dB is available. R6.1 says the 5-dB gap has a physical origin: static body parts add coherent-sum confusion that doesn't exist in the idealised single-scatterer model. The three threads now form a coherent physics story: - R6 = bound (idealised single-scatterer = +23.7 dB) - R6.1 = floor (realistic 6-scatterer = +19.0 dB) - R13 = failure (contour needs +25 dB, gets +20 dB) Pulse-contour recovery is bounded below by what R6.1 leaves achievable, which is 4.7 dB worse than R6's idealised limit, enough to make R13's contour recovery infeasible. Per-body-part contribution: chest = 27.6% of CSI energy (5x per-limb reflectivity). The chest IS the breathing signal; limbs are confound. Architectural implications: - Chest-centric placement targeting (R6.2.3 motivated) - Mask limbs in vital_signs pipeline (use pose pipeline ADR-079/101) - R14 V3 rescope to rate-only (no contour-shape recovery) - R12 PABS revision unblocked: R6.1 is the explicit A(voxel) operator Surprise finding: on-LOS placement (y=0) is degenerate -- path delta is 2nd-order in offset for on-LOS scatterers, so breathing barely changes path length. Real installations need subject OFF the LOS line. The R6.2 placement search should respect this. Honest scope: - 6 scatterers is 1st-order; 50-100 voxel body would refine - Reflectivity ratios are guesses (RCS measurements would refine) - Static body assumption (limbs do micro-move during breathing) - 2D top-down, no multipath (model general enough to include them) Composes: - R5: subcarrier selection picks reliable, not high-SNR - R6: per-scatterer building block - R6.2.x: chest-centric placement - R7: residual-vs-forward-model = tighter adversarial detection - R12 NEGATIVE: PABS A operator unblocked - R13 NEGATIVE: 5-dB gap has physical origin - R14 V3: needs rescope Coordination: ticks/tick-18.md, no PROGRESS.md edit. |
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| .. | ||
| environment | ||
| happiness-vector | ||
| medical | ||
| research-sota | ||
| sleep | ||
| stress | ||
| three.js | ||
| README.md | ||
| ruview_live.py | ||
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