Usage Examples

This chapter presents short examples of using RetractorDB to solve concrete problems encountered when building monitoring systems.

Every example is complete — it includes a problem description, the RQL query design, how to run it, and how to interpret the results. The examples can be run on their own: the required data files and scripts are described step by step.

Signal filtering (FIR)

This example demonstrates how to implement a digital FIR filter directly within an RQL query stream, without external DSP libraries. The topic is representative of a broad class of signal-processing problems: noise filtering, frequency-band separation, time-series smoothing.

The example covers:

• designing filter coefficients in GNU Octave (the Remez algorithm, the remez() method),
• transferring the coefficients into a text file and loading them as a DECLARE stream,
• implementing discrete convolution as a set of SELECT queries using the sliding-window @ operator and expansion of the _ symbol,
• real-time visualization of the filtering process using xqry and gnuplot.

The result is a working system that filters a pseudo-random signal (50 Hz) down to the 0–2 Hz band, observed live while xretractor is running.

Full description: Signal Filter Implementation

ECG Signal Analysis (MIT-BIH)

This example demonstrates using RetractorDB to process clinical ECG signals from the public MIT-BIH Arrhythmia Database (PhysioNet). It’s a complex use case combining several of the system’s mechanisms: multi-channel input streams, a multi-stage FIR filtering pipeline, an adaptive detection threshold, and real-time visualization.

The example covers:

• data preparation: converting MIT-BIH recordings (WFDB format) into text files compatible with RetractorDB,
• implementing the five-stage Pan-Tompkins algorithm in RQL: band-pass filter → differentiation → squaring → moving-window integration → threshold detection,
• visualizing the ECG signal and the QRS-detection result in a gnuplot window (RTL mode — newest samples on the right),
• interpreting the results: RR-interval readings, identifying arrhythmia episodes in MIT-BIH record 205.

The result is a working QRS detector processing a two-channel ECG signal (MLII + V1) at 360 Hz, implemented entirely with RQL queries, with no specialized libraries.

Full description: ECG Visualization and Arrhythmia Detection