Chair Force One

Omnibus health-sensing platform for wheelchair users as operators in extreme environments — pressure, cardiac, posture, and environmental risk prediction. Emerge Hackathon 2026.

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CHAIR FORCE ONE

An omnibus sensing → reasoning → acting platform built for Emerge Hackathon 2026. The anchor use case is a wheelchair user, reframed as an operator in an extreme environment: pressure injuries are their radiation exposure, lost cellular signal is their degraded comms, cushion telemetry is their mission telemetry. Solve that problem with the same architecture you'd use for space or defense, and every module reinforces every other.

The result is one unified pipeline that predicts and prevents health crises across pressure, posture, cardiac, and environmental domains — because compounding, invisible risks escalate silently, and most systems today are reactive, not predictive.

Live Demo — Two-Stage ECG Classifier

The fastest way to see the platform do something real. It's a self-contained browser demo — no server, no hardware, no install. It loads TensorFlow.js from a CDN and pulls its models directly from Google's Teachable Machine, so you just open the file.

Just open it:

# from the repo root
open dashboard/two_stage_ecg_demo.html        # macOS
xdg-open dashboard/two_stage_ecg_demo.html     # Linux
start dashboard/two_stage_ecg_demo.html        # Windows

Or serve the whole dashboard folder (recommended — avoids browser file:// restrictions):

cd dashboard
python -m http.server 8000
# then visit http://localhost:8000/two_stage_ecg_demo.html

Prefer a front door? Open index.html at the repo root — a launcher that surfaces every dashboard and shows which ones run in-browser versus which need hardware attached.

What it does: upload or capture an ECG image and watch a two-stage pipeline run:

  1. Stage 1 — Image Detection (PTB-XL): "What are we even looking at?"
  2. Stage 2 — Cardiac Classification (Mendeley): the actual diagnosis.
  3. Subjective-Logic fusion: each stage emits an SL opinion; the two are fused, aged with a temporal-decay model (Chronofy), and framed for CBOR-LD transport.

Needs an internet connection (CDN scripts + hosted models). A webcam or a saved ECG image works as input.

There's also a single-stage variant at dashboard/ecg_classifier_demo.html if you want the simpler pipeline.

Repository Layout

The platform maps all 24 hackathon problems onto six reasoning modules, plus a hardware sensing layer (sensus/).

Module Path Focus Sponsor
BODY body/ Pressure-injury risk, relief quality, activity phenotypes, posture alerts (Problems 1–4) Kalogon
HEART heart/ Synthetic ECG, algo-vs-ML benchmarking, transformer model, lead extraction (21–24) Who We Play For
ENVIRONMENT environment/ Health-risk prediction, radiation/hazard protection (13–14) BoxMica
SPACE space/ Launch detection, object behavior, delay-tolerant ops, lunar awareness (15–18) BoxMica
AUTONOMY autonomy/ Autonomous delivery loop, analytics, safe-AI broker (5–7) BeeNex
OPERATIONS ops/ Conversation-to-state, workflow analysis, text-to-SQL, record linkage (8–12, 19–20) MyelAI · Steppingblocks
SENSUS sensus/ Contactless hardware layer — 60GHz mmWave, ESP32 CSI mesh, hazard node, Pi 5 edge —
CORE chairforce_core/ Cardiac monitor + Subjective-Logic integration shared across modules —

Design docs live at the root: ARCHITECTURE.md (full concept, data flow, hardware BOM) and DATABRICKS_STRATEGY.md (Lakehouse plan).

Dashboards at a Glance

Dashboard Path Runtime Needs
Two-Stage ECG Classifier ⭐ dashboard/two_stage_ecg_demo.html Browser Internet only
ECG Image Classifier dashboard/ecg_classifier_demo.html Browser Internet only
Contactless Health Monitor sensus/pi/services/dashboard.py Flask MQTT broker + sensors
60GHz mmWave sensus/mmwave_dashboard.py Web Seeed MR60BHA2 via ESPHome
Hazard Detection sensus/hazard_dashboard.py Web ESP32-C3 over serial

The two browser dashboards run anywhere. The three sensus/ dashboards are the live-hardware side of the platform — see sensus/README.md for wiring and setup.

Unified Data Flow

SENSORS                EDGE (Pi 5 / Laptop+4090)        CLOUD (Databricks)
─────────              ─────────────────────────         ──────────────────
Kalogon Mat ──┐         ┌─────────────────────────┐      ┌──────────────┐
ESP32 CSI ────┤  MQTT   │  CHAIR FORCE ONE Engine  │Delta │ Unity Catalog│
AD8232 ECG ───┤ ──────→ │  body/ heart/ env/       │ ───→ │  cushion_tel │
IMU/GPS ──────┤   BLE   │  space/ autonomy/ ops/   │      │  ecg_records │
Env sensors ──┘         │  Delay-tolerant queue    │      │  env_readings│
                        │  Gemini interpretation   │      └──────┬───────┘
                        │  ElevenLabs voice alerts │             │
                        └───────────┬──────────────┘      Text-to-SQL · Linkage
                              Dashboard :5000

Quick Start

git clone https://github.com/b-urge/chairforce-one.git
cd chairforce-one

# 1. See it work — no setup:
python -m http.server 8000 --directory dashboard
#    → http://localhost:8000/two_stage_ecg_demo.html

# 2. Explore a reasoning module:
python body/pressure_risk.py

# 3. Bring up the hardware layer:
#    follow sensus/README.md

Reasoning modules are Python; the sensus/ layer targets ESP32 / Raspberry Pi 5. Approximate hardware BOM is ~$204 (full table in ARCHITECTURE.md).

License

See sensus/LICENSE for the hardware layer. Confirm licensing for the rest of the platform before reuse.

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