Signal conditioning is the manipulation of a signal in a way that prepares it for the next stage of processing. Most analog signals require some form of preparation before they can be digitised.
Historically, ECG has been almost exclusive to the medical industry due to its strength as a diagnostic tool, where the data capture is highly controlled.
In a medical environment, an ECG requires a 12-lead configuration and is collected using wet electrodes.
Most ECG analysis software is designed for these ideal conditions and often suffers in accuracy when adapted for commercial applications on dry electrodes.
When attempting to obtain a lead 1 ECG signal from dry electrodes, the main problem that will occur is noise.
Noise can make it difficult to clearly detect the individual waves in the ECG signal which leads to inaccuracies which could include false positives. Therefore, it is vital that noise is identified and removed.
The main sources of noise can be found through mains noise, motion artefacts and varying ECG amplitudes e.g. low amplitude signals make it difficult to detect the correct R peak in the ECG waveform.
High quality signal conditioning is key to ensuring the ECG signal is detected correctly allowing highly accurate data extraction and an enhanced user experience. This provides the solid foundation for the other algorithms to be built upon.
HeartKey®’s intelligent and adaptive signal conditioning technology enables high accuracy ECG detention on dry electrodes in real time, forming the foundation of our more advanced algorithms.
At B-Secur, we have carried out extensive testing to ensure our algorithms perform to the highest levels of accuracies.
This graph shows results from the HeartKey® Heart Rate algorithm and from a well known medical holter monitor.
As seen on the graph, there is virtually no difference between the two, displaying HeartKey®'s excellent performance against a single lead holter monitor.
HeartKey® Signal Conditioning algorithm performance validation is available under NDA.