ECG & Biosignal Processing Patents

Seven patents awarded for work at Hewlett-Packard / Agilent Technologies, Andover MA (1980–1995). These algorithms represented the first system in the industry to successfully monitor patients with pacemakers in real-time clinical environments, and remain deployed in intensive care units worldwide.

This body of work is the direct precursor to modern medical ML — built using signal decomposition, feature engineering, and real-time classification under noise before deep learning frameworks existed. The same principles now inform modern biosignal ML approaches.


  1. US 4,664,116 — Pace Pulse Identification Apparatus
  2. US 4,832,041 — Pace Pulse Eliminator
  3. US 4,539,999 — Method and Device for Subtracting a Pacer Signal from an ECG Signal
  4. US 4,838,278 — Paced QRS Complex Classifier
  5. US 5,447,164 — Interactive Medical Information Display System and Method for Displaying User-Definable Patient Events
  6. A61B5/7264 — Classification of Physiological Signals Using Neural Networks, Statistical Classifiers, and Expert Systems

Relevance to Modern Medical ML

The core problems these patents solved — detecting and classifying low-SNR physiological events in real time, handling pacemaker artifact, defining clinically meaningful event taxonomies — remain open research problems in modern form. Work in PCG (heart sound) classification, atrial fibrillation detection, and wearable biosignal processing all draw on the same signal processing foundations.

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