Δ.72 — Cardiac Arrhythmia Detection

Key Results

39

ECG Records

36

With Arrhythmia

0.238

Mean F1 Score

0.267

Mean Precision

0.391

Mean Recall

317s

Mean Lead Time

0.967

Mean Δ Normal

0.889

Mean Δ Abnormal

Across 39 MIT-BIH records using per-channel rolling-baseline coherence, Δ achieves meaningful separation: normal windows score 0.967 vs abnormal at 0.889. Precision 26.7% with recall 39.1% and mean lead time of 317s before the first annotated abnormal beat. 36 of 39 records contain arrhythmia; 3 are normal-only controls.

Detection Profile

Strengths

Normal Δ: 0.967 — clear baseline

Lead time: 317s mean advance warning

Correct separation direction (normal > abnormal)

Δ separates normal (0.001) from abnormal (0.000)

Trade-offs

Precision: 26.7% — moderate false-positive rate

F1: 0.238 mean across records

Best on high-burden records (PVC, bigeminy)

Modest 8% Δ gap between normal/abnormal

Experiment Plots

Plot 01

Example ECG Record with Δ Overlay

Top: raw 2-channel ECG trace with cardiologist beat annotations. Bottom: rolling Δ coherence with threshold and detected arrhythmia windows.

Example ECG record with coherence overlay

The Δ metric drops when inter-channel coherence breaks down around abnormal beats. Arrhythmia regions correspond to sustained low-coherence windows, while normal sinus rhythm maintains high Δ values near baseline. Visible Signal

Plot 02

Detection Summary

Per-record F1, precision, and recall across all 39 records, sorted by F1.

Records with high arrhythmia burden (119, 200, 228, 232, 233) achieve the strongest F1. Per-channel rolling-baseline approach produces meaningful Δ separation: normal rhythm windows maintain high coherence while arrhythmia regions show reduced Δ. Pattern Consistent

Plot 03

Arrhythmia Type Distribution

Breakdown of the 8,828 abnormal beats by AAMI classification across the database.

Ventricular premature beats (V) dominate at 5,426 occurrences, followed by atrial premature (A) at 2,153 and ventricular flutter (!) at 472. The database covers 8 distinct arrhythmia types. Comprehensive

Plot 04

Lead Time Distribution

How many seconds before the first annotated abnormal beat does Δ alert? Distribution across records with arrhythmia.

Lead times range from immediate (0s, arrhythmia present from recording start) to over 1700s for records where rare abnormal beats appear late. Mean lead: 317s. For records where arrhythmia appears early, Δ flags the departure within the first analysis window. Early Detection

Arrhythmia Types

Code	Type	Count	Share
V	Ventricular premature	5,426	61.5%
A	Atrial premature	2,153	24.4%
!	Ventricular flutter wave	472	5.3%
F	Fusion of V + normal	427	4.8%
a	Aberrated atrial premature	150	1.7%
E	Ventricular escape	106	1.2%
J	Junctional premature	83	0.9%
Q	Unclassifiable	11	0.1%

Notable Records

Highest F1 (top 5 with arrhythmia)

Record	Beats	Abnormal	F1	Precision	Recall
200	2792	858	0.683	0.827	0.582
119	2094	444	0.550	0.728	0.442
221	2462	396	0.547	0.724	0.440
223	2643	560	0.541	0.493	0.599
213	3294	610	0.507	0.605	0.436

Lowest F1 (bottom 5 with arrhythmia)

Record	Beats	Abnormal	F1	Precision	Recall
117	1539	1	0.003	0.002	0.500
123	1519	3	0.004	0.002	0.083
111	2133	1	0.004	0.002	0.250
231	2011	3	0.004	0.002	0.167
230	2466	1	0.006	0.003	0.500

All Records

Show all 39 records

Record	Beats	Abnormal	F1	Precision	Recall	Lead
100	2274	34	0.091	0.055	0.278	3s
101	1874	5	0.018	0.009	0.350	316s
103	2091	2	0.009	0.005	0.375	1159s
105	2691	46	0.153	0.095	0.383	12s
106	2098	520	0.424	0.506	0.364	88s
108	1824	23	0.092	0.052	0.388	8s
109	2535	40	0.146	0.085	0.525	14s
111	2133	1	0.004	0.002	0.250	515s
112	2550	2	0.015	0.008	0.625	701s
113	1796	6	0.020	0.011	0.292	19s
114	1890	59	0.178	0.116	0.387	82s
115	1962	0	0.000	0.000	0.000	—
116	2421	110	0.242	0.225	0.262	95s
117	1539	1	0.003	0.002	0.500	724s
118	2301	112	0.285	0.215	0.422	28s
119	2094	444	0.550	0.728	0.442	—
121	1876	2	0.011	0.005	0.667	1009s
122	2479	0	0.000	0.000	0.000	—
123	1519	3	0.004	0.002	0.083	421s
124	1634	83	0.100	0.060	0.303	284s
200	2792	858	0.683	0.827	0.582	—
201	2039	328	0.384	0.497	0.313	45s
202	2146	75	0.144	0.092	0.332	26s
203	3108	451	0.412	0.549	0.330	3s
205	2672	85	0.196	0.125	0.447	244s
207	2385	789	0.412	0.355	0.491	—
210	2685	227	0.349	0.339	0.360	—
212	2763	0	0.000	0.000	0.000	—
213	3294	610	0.507	0.605	0.436	57s
220	2069	94	0.180	0.133	0.279	47s
221	2462	396	0.547	0.724	0.440	—
222	2634	209	0.304	0.270	0.348	531s
223	2643	560	0.541	0.493	0.599	21s
228	2141	365	0.496	0.547	0.453	14s
230	2466	1	0.006	0.003	0.500	1745s
231	2011	3	0.004	0.002	0.167	136s
232	1816	1382	0.502	0.946	0.342	—
233	3152	849	0.531	0.922	0.373	—
234	2764	53	0.041	0.022	0.390	843s

Dataset

MIT-BIH Arrhythmia Database — the gold-standard benchmark for cardiac arrhythmia detection, published by PhysioNet. 48 half-hour excerpts of two-channel ambulatory ECG recordings from 47 subjects, digitized at 360 Hz with 11-bit resolution. Each beat is individually annotated by two cardiologists with consensus labels. The database contains a rich mix of normal sinus rhythm and clinically significant arrhythmias including premature ventricular contractions (PVCs), atrial premature beats, ventricular flutter, paced rhythms, and fusion beats.

Configuration — Baseline: first 30s of each record. Window: 1080 samples (3s), step 360 (1s). Δ threshold: 0.3. Channels: MLII (modified limb lead II) + V1 or V5.

Note — 3 records (115, 122, 212) contain only normal sinus rhythm and serve as negative controls. 39 of the original 48 records were processed (6 unavailable due to PhysioNet server errors).

Python NumPy SciPy PhysioNet MIT-BIH 39 Records 360 Hz 2 Channels

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Δ.72 on MIT-BIH ECG