Bringing electrophysiology lab precision to the back of an ambulance.
No CT scanner. No hospital. Just a vest and 90 seconds.
Every year, 30,000 people in the UK die from sudden cardiac arrest before reaching hospital. Paramedics have one tool: the 12-lead ECG — technology essentially unchanged since 1942.
Meanwhile, in hospital EP labs, cardiologists use 252-electrode systems with CT-derived heart geometry to map cardiac electrical activity in stunning 3D detail.
The gap is fatal.
What if you didn't need CT?
Our hypothesis: 700 electrodes + statistical shape modelling = CT-free geometry estimation accurate enough for pre-hospital use.
If we're right, this unlocks portable EP-grade cardiac mapping for the first time in history.
If we're wrong, we pivot to hospital-based systems and compete on electrode density.
| Parameter | Target | Evidence Level |
|---|---|---|
| Electrode Count | 700 | Design spec |
| Sampling Rate | 4000 Hz/channel | Validated |
| CT-free Accuracy | ±20mm | Hypothesis |
| Deployment Time | <120 seconds | Requires validation |
| Weight | <5 kg | Mass budget complete |
| Battery | 4 hours continuous | 15W power budget |
┌─────────────────────────────────────────────────────────────┐
│ SCENARIO NPV PROBABILITY EXPECTED │
├─────────────────────────────────────────────────────────────┤
│ Full Success £42M 15% +£6.3M │
│ Hospital Only £18M 25% +£4.5M │
│ CT-Based Pivot £5M 30% +£1.5M │
│ Component Sale -£8M 10% -£0.8M │
│ Total Failure -£15M 20% -£3.0M │
├─────────────────────────────────────────────────────────────┤
│ EXPECTED NPV 100% +£1.3M │
└─────────────────────────────────────────────────────────────┘
Break-even: 8% success probability. We estimate 15%.
| Month | Gate | Criterion | If Fail |
|---|---|---|---|
| 3 | Benchtop PoC | 64-ch optical mux <50μs skew | TERMINATE |
| 6 | Optical Engineer | Primary or backup secured | PAUSE |
| 9 | CT Data Access | ≥300 scans for training | PAUSE |
| 12 | Market Validation | N≥50 WTP study positive | PIVOT REVIEW |
| 18 | CT-Free Algorithm | ±30mm accuracy (N≥100) | PIVOT |
We kill fast. We pivot faster.
- ❌ Not a diagnosis machine — Clinical Decision Support only
- ❌ Not autonomous — Human-in-loop required
- ❌ Not validated — All performance figures are engineering targets
- ❌ Not built — This is a pre-prototype investment proposal
HD-ECGI/
├── docs/
│ └── HD-ECGI-Whitepaper-v6.docx # Full technical proposal
├── models/
│ └── [placeholder] # SSM training (Phase 1)
├── firmware/
│ └── [placeholder] # Optical mux control (Phase 1)
├── algorithms/
│ └── [placeholder] # CT-free estimation (Phase 1)
└── README.md
Investors: Read the whitepaper. Grill the assumptions. Fund the hypothesis test.
Optical Engineers: We need you. £90-120K + equity. Contact us.
EP Cardiologists: Clinical advisory board forming. Shape the product.
NHS Trusts: Interested in clinical validation partnership? Let's talk PACS access.
| Document | Description |
|---|---|
| Technical Whitepaper | Full investment memorandum with evidence classification |
| Liability Matrix | Who's responsible when things go wrong |
| Demographic Validation | How we're addressing training data bias |
-
CT-free may not work. Schulze 2019 achieved ±18mm with 12 leads. Extrapolating to 700 is conjecture.
-
Optical multiplexing at scale is unproven. 66% timing margin, but three components need PoC.
-
Market validation is weak. N=12 interviews is anecdote, not evidence. Phase 1 fixes this.
-
Demographic bias could kill. Training data underrepresents South Asian (4×) and obese (4×) populations.
-
If CT-free fails, we compete against CardioInsight's 10-year head start.
We document these risks because pretending they don't exist is how projects fail.
The best time to map a heart attack was in the EP lab.
The second best time is in the ambulance.
Aaron Garcia
aaron@garcia.ltd
Version 6.0 | December 2025 | Classification: CONFIDENTIAL