OpenECS — the Open EEG Codec Standard

A universal, vendor-neutral benchmark standard for EEG signal compression. Grade any codec — lossless, lossy, neural, classical, hybrid, in any language — against a hash-pinned corpus and get a single, reproducible, comparable verdict.

Crate: open-eeg-codec-standard · library: open_eeg_codec_standard · reference CLI: openecs
Spec: SPEC/OpenECS-v1.0.md (normative) · STANDARD.md (narrative) · JSON schemas in SPEC/schemas/

Tiers (strictness order L < N < C < M < A)

Grade	Tier	Gate
`ECS-L`	Lossless	bit-exact (integer-domain PRD = 0), CR ≥ 0.8
`ECS-N`	Near-Lossless	R ≥ 0.99, PRD ≤ 5 %, CR ≥ 1.0
`ECS-C`	Clinical	R ≥ 0.95, PRD ≤ 9 %, CR ≥ 20 + per-band δθαβγ
`ECS-M`	Monitoring	R ≥ 0.85, PRD ≤ 20 %, CR ≥ 100 + per-band
`ECS-A`	Alerting	R ≥ 0.70, PRD ≤ 40 %, CR ≥ 200 + per-band
`—`	below floor	fails even the A gate

The grade is the highest tier a codec fully satisfies, verified through its encode/decode boundary only — the lossless claim is checked, not trusted.

Install

# the `openecs` command-line benchmark
cargo install open-eeg-codec-standard

# or use it as a library
cargo add open-eeg-codec-standard      # then: use open_eeg_codec_standard::...

60-second quickstart (zero download)

A tiny synthetic smoke corpus ships in-repo, so you can grade immediately:

# grade a codec + built-in baselines (store, gzip), ranked, with an HTML report
openecs bench --codec gzip --corpus-manifest corpora/ecs-smoke.toml \
    --charts --report report.html

Out comes a colored, ranked leaderboard (grade + pooled CR + mean-R 95 % CI + a paired significance test vs the strongest baseline), terminal charts, and a self-contained report.html (inline SVG, no JS):

  rank  codec      grade   pooled CR   mean R (95% CI)            PRD%   p vs base
    1   gzip       ECS-L      24.57:1   1.0000 [1.0000,1.0000]    0.00       —
    2   store      ECS-L       1.00:1   1.0000 [1.0000,1.0000]    0.00    1.0000

Other subcommands: openecs grade (one codec), openecs verify-corpus (check a corpus's SHA-256 pins), openecs emit-corpus-manifest (hash a directory of EDFs into a pinned manifest). Run openecs <cmd> --help for each.

Grade YOUR codec (any language)

Your codec just needs an executable that speaks the file-based contract (full spec: SPEC/OpenECS-v1.0.md §6):

<cmd> [prefix…] encode <in.edf>  <out.blob>
<cmd> [prefix…] decode <in.blob> <out.raw> --channels N --samples M --rate FS --dtype DT

Describe how to invoke it in a codec-manifest.toml (schema):

spec_version = "1.0"
[codec]
name = "my-codec"
cmd = "python3"                  # any binary/script; resolved on PATH
prefix_args = ["my_codec.py"]
declared_lossless = false        # your claim — verified, not trusted
sample_dtype = "i32"             # raw decode width: i16 | i32 | i64
input_format = "edf"             # edf (default) | ecs0
output_format = "raw"            # raw (default) | ecs0

Then benchmark it against the baselines:

openecs bench --codec-manifest codec-manifest.toml \
    --corpus-manifest corpora/ecs-smoke.toml --report report.html

No Rust, no source access, no special build — the standard grades whatever comes out the other end.

Use it as a library

use open_eeg_codec_standard::{adapter::Gzip, harness};

// `signal` is one Vec<i64> per channel (integer ADC counts); `fs` is the rate.
let report = harness::run(&Gzip, &signal, 256.0);
println!("grade ECS-{}  CR {:.2}  R {:.4}", report.grade, report.cr, report.r);
// Implement the `Codec` trait for your own in-process codec, or drive an
// external one via `open_eeg_codec_standard::manifest` + `corpus::grade_manifest_parallel`.

Canonical corpus (cross-lab comparable numbers)

For citable results, grade against the pinned public corpus bench/ECS-Bench-v1/ (PhysioNet CHB-MIT subset):

cd bench/ECS-Bench-v1
sh fetch.sh                                              # download (~170 MB)
openecs verify-corpus --corpus-manifest ECS-Bench-v1.toml   # SHA-256 + shape
openecs bench --codec-manifest <yours> --corpus-manifest ECS-Bench-v1.toml --report r.html

Data is not redistributed — only the record list + SHA-256 pins, so every lab grades byte-identical data.

License

Apache-2.0. See LICENSE.

open-eeg-codec-standard 0.9.0