ZPE-Bio

Package Install

Installable package: python3.11 -m pip install zpe-bio. Current release: 0.2.1 on PyPI. Source: Zer0pa/ZPE-Bio.

python3.11 -m pip install zpe-bio

For full install, smoke, source, and developer commands, click here.

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00 · ZPE-BIO · ECG CODEC DEVELOPER-READY · PTB-XL OPEN ECG With Every Beat Encoded ECG-only staged codec · ZPE-Bio · PyPI zpe-bio v0.2.1 · github.com/Zer0pa/ZPE-Bio ZPE-Bio compresses heart-rhythm recordings and publishes the replay error on every dataset it touches. On MIT-BIH, all 48 records return inside the 2.32% clinical target with a mean replay error of 1.12%. PTB-XL processes cleanly but one record drifts to 5.29%, so the wider ECG surface is named, not claimed. This is a developer-ready archival codec, not a clinical device, wearable, or regulatory product.

Scope: ECG archive replay. MIT-BIH inside target; PTB-XL edge open. Not a clinical, wearable, or regulatory device.

01 · THE GAP MEASURED, NOT ASSUMED ECG codecs that report file size without naming their replay error leave clinicians guessing.

02 · MARKETS ADJACENT FORECASTS Digital cardiovascular health ’30 $141.0B Cardiac monitoring devices ’32 $31.6B Wearable ECG monitors ’30 $13.7B ECG monitoring devices ’30 $12.4B ECG data analytics ’30 $4.2B Where this codec belongs: archive replay and cardiology data stewardship. No clinical-device, wearable, or regulatory readiness claim.

03 · VALUE OF MARKET 48 /48 MIT-BIH records replay inside the 2.32% target · mean 1.12% replay error

04 · INSIGHT Every replayed ECG should carry its measured change.

05.1 · CURRENT TECH SIZE WITHOUT FIDELITY Lossless compressors preserve bytes and report file-size ratios. They tell a cardiology archive nothing about how closely a replayed waveform tracks the original signal on any named clinical corpus.

05.2 · OUR TECH REPLAY ERROR PUBLISHED ZPE-Bio reports replay error directly per dataset. On MIT-BIH, 48 of 48 records return at mean 1.12%, inside the 2.32% clinical target a cardiology archive can show its review board. PTB-XL processes 100 of 100 records with full integrity but a worst-case record reaches 5.29%, so that corpus is named openly as out of contract rather than buried.

05.3 · BENCHMARKS FOUR CORPORA MIT-BIH48/48PASS NSTDB15/15PASS EDB90/90PASS PRD target2.32%MIT-BIH MIT-BIH PASS NSTDB PASS PTB-XL out Reported today: MIT-BIH 48/48 · NSTDB 15/15 · EDB 90/90 · PTB-XL 5.29% out.

06 · MEASUREMENT PRD BY CORPUS Replay error reported per corpus, with MIT-BIH as the reference.

06.1 · COMPARATIVE PERFORMANCE PRD BY CORPUS MIT-BIH · mean 1.12% NSTDB · max 1.96% EDB · max 4.34% · LOG PTB-XL · max 5.29% · OUT MIT-BIH Arrhythmia (48 records), NSTDB (15), EDB (90), PTB-XL (100 sampled). MIT-BIH target: replay error ≤ 2.32%. File-size winners stay gzip and zstd; this codec competes on fidelity, not bytes.

07 · KEY METRICS MEASURED RESULTS

07.1 · MIT-BIH INTEGRITY 48/48 MIT-BIH records replay clean · integrity pass

07.2 · MEAN CR 1.12% MIT-BIH aggregate replay error · inside the clinical target

07.3 · PTB-XL INTEGRITY 100/100 PTB-XL 100-record sample · worst 5.29% disclosed

07.4 · PRD TARGET 2.32% MIT-BIH clinical target · met by mean

07.5 · MEAN PRD 1.12% MIT-BIH 48-record mean · inside target

08 · DETERMINISM CI PARITY PYTHON + RUST Python and Rust replay the ECG surface consistently.

08.1 · WHAT DETERMINISTIC MEANS ECG SURFACE ONLY Repo CI runs Python and Rust round-trips on every push across MIT-BIH, NSTDB, the European ST-T Database, and PTB-XL. Replay error is reported per dataset. MIT-BIH sits inside the 2.32% target at a mean of 1.12%. PTB-XL logs 100 of 100 records with full integrity, but the worst-case replay error reaches 5.29% and stays visible in the public results. PyPI 0.2.1 is stale and is not presented as fresh; the surface is ECG-only.

08.2 · THE FIDELITY GAP Honest Blocker · PTB-XL processes 100 of 100 records, but the worst-case replay error reaches 5.29%, outside the 2.32% MIT-BIH target. PyPI is stale at zpe-bio 0.2.1. Wearable-data scope and the 0x0400 marker policy are open. No clinical, regulatory, EEG, wearable, or raw-size superiority claim.

09 FIVE PATHS FROM ONE CLINICAL CONTRACT.

09.1 · THE AMBITION The hinge is the disclosed boundary, not the passed contract. A codec that names its worst-case excursion alongside its pass rate becomes the substrate cardiology archives can adopt before regulatory engagement — because the open question is already on the table, not waiting in the field.

09.2 · WHAT WORKS NOW EXTERNAL MIT-BIH 48/48 records pass; the mean replay error of 1.12% sits inside the 2.32% clinical target.

09.3 · WHAT'S STILL OPEN EXTERNAL PTB-XL excursion at 5.29%, stale PyPI release, wearable scope, and marker-policy decision are open.

09.4 · ARCHIVES · NEAR-TERM (12–24 MO) Cardiology archives gain a fidelity floor An academic cardiology lab can stop hoarding raw float32 MIT-BIH waveforms because every record returns inside a documented 2.32% replay error. Storage budgets fall and the archived signal still satisfies clinical research review.

09.5 · PROCUREMENT · NEAR-TERM (12–24 MO) Buyers decide before deployment, not after A cardiology archive buyer who sees the PTB-XL 5.29% excursion published alongside the MIT-BIH pass rate can choose with eyes open. Disclosure shifts procurement from a post-purchase surprise to a pre-purchase conversation about which corpora the buyer actually needs.

09.6 · CLINICAL RESEARCH · MID-TERM (24–48 MO) Reproducible studies travel between sites When two cardiology research groups share compressed waveforms with identical replay error, a finding produced at one institution can be re-run at another without arguing about whether the data was altered in transit. Reproducibility stops depending on raw-byte custody.

09.7 · BOUNDARY CLOSURE · MID-TERM (24–48 MO) PTB-XL becomes a routine corpus If codec tuning brings the PTB-XL worst-case replay error from 5.29% under the 2.32% target, the PTB-XL population — broader demographics, more leads, longer recordings — joins the safely archivable set. The cardiology research community gains a second large public corpus with a fidelity guarantee.

09.8 · INDUSTRY STANDARD · PARADIGM (48 MO+) Fidelity claims arrive with disclosure attached ECG codecs across the industry begin publishing their per-dataset thresholds, worst-case excursions, and pass rates as standard practice. Hospitals, regulators, and procurement teams stop accepting a single global fidelity number and start asking which corpus, which boundary, which pass rate.

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Install / Developer Commands Detailed

Package Install

Installable package: python3.11 -m pip install zpe-bio. Current release: 0.2.1 on PyPI. Source: Zer0pa/ZPE-Bio.

python3.11 -m pip install zpe-bio

Import smoke:

python3.11 - <<'PY'
import importlib.metadata as md
import zpe_bio

print("zpe-bio", md.version("zpe-bio"))
PY

CLI smoke:

zpe-bio --help

Install success only proves package acquisition/import. Product scope, stale PyPI state, platform limits, and blockers remain in the front-door sections below.

• PyPI copy is stale or pending refresh; install success is not product readiness.

Quick Start

python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev,validation]"
python -m zpe_bio roundtrip --mode clinical --samples 250

Further reading:

• validation/results/README.md
• validation/results/BENCHMARK_SUMMARY.md
• docs/ARCHITECTURE.md
• docs/LEGAL_BOUNDARIES.md

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