Minimizing Error Rate in Lightweight and High Accurate RR Interval Compensation for Signals from Wearable ECG Sensors with Band Pass Filter

A novel lightweight and highly accurate RR intervals (RRIs) compensation method that works with wearable electrocardiogram (ECG) sensors is presented in this letter. Since RRIs are significant components of ECG signals, they are frequently employed in medical and healthcare applications. Wearable ECG sensors also frequently use their estimation. One of the variables affecting the RRI accuracy from ECG signals obtained by wearable sensors is the data sampling rate. High sample rates in wearable sensors, however, need a trade-off between power consumption and RRI accuracy due to their significant electrical power consumption. One of the traditional compensating techniques for producing high-resolution RRI at low sampling rates is spline interpolation. However, the high-order interpolation in the approach necessitates intensive computational processing. Therefore, for low power consumption in wearable measurement, a method that achieves extremely accurate RRI interpolation with lightweight computer processing is desirable.

Here, we created a brand-new, highly accurate, and lightweight RRI correction technique that may be used with wearable ECG sensors. The technique is especially made for algorithms that are frequently used in wearable ECG sensors to detect R waves. The suggested method outperforms the traditional cubic spline interpolation when it comes to accurate RRI estimate for sampling rates ranging from 50 to 1000 samples, as confirmed by validation results using simulated ECG signals. Additionally, even at a low sampling rate of 66.7 samples, the suggested method was shown to meet the accuracy requirements for heart rate variability analysis. Furthermore, the efficacy of the suggested approach was verified through experiments conducted on particular actions including different motion artifacts. These outcomes show how well the suggested technique for RRI adjustment in wearable ECG sensors works. We anticipate that our technique will offer the necessary balance between low power consumption and good resolution with the upcoming release of wearable ECG devices.

Keywords: Sensor Signal Processing, ElectroCardioGram (ECG), Interpolation, RR Interval (RRI), Sampling Rate, Wearable Sensors.