Biosignal Quality Control in Real-World Intelligent Environments

Abstract

Despite the wealthy of information biosignals cary, with Intelligent Environments (IE) they are often disregarded. We discuss issues we faced with integrating reliable biosignals into a real-world IE. These include the limited conductivity of dry sensors, movement artifacts, and placement issues. Subsequently, we introduce a real-time Signal Quality Indicator (SQI) for ElectroCardioGram (ECG), which consists of a Signal Loss Indicator (SLI) that detects signal capping, flatlining, high-frequency noise, and low-frequency noise. If the SLI detects a signal, the Signal Usability Indicator (SUI) subsequently processes the signal using the reference Pan-Tompkins algorithm and a dedicated filter to extract heart rate. The SQI marks what parts of the signal can and cannot be used for analysis. As such, it allows empirical calibration and, hence, the use of biosensors in real-world IE.