In ambulatory e.c.g. monitoring, a high level of noise results in false QRS detection. We present a compact low-powered QRS detector design. We present a noise detector circuit that identifies most false QRS detections so that it can disable alarms. We present a standardised exercise protocol for testing the QRS detector. Data collected from subjects bending forward (for baseline drift), lifting a weight (for e.m.g.), and jogging (for motion artefact) present a realistic test set for an ambulatory QRS detector. We observe error rates of the order of 1%, the noise detector identifies more than half of these. These techniques should reduce false alarms in arrhythmia monitoring systems.
ASJC Scopus subject areas
- Health Information Management
- Health Informatics
- Biomedical Engineering
- Computer Science Applications
- Computational Theory and Mathematics