Instantaneous Heart Rate detection using short-time autocorrelation for wearable healthcare systems

Abstract

This report describes a robust method of Instantaneous Heart Rate (IHR) detection from noisy electrocardiogram (ECG) signals. Generally, the IHR is calculated from the interval of R-waves. Then, the R-waves are extracted from the ECG using a threshold. However, in wearable biosignal monitoring systems, various noises (e.g. muscle artifacts from myoelectric signals, electrode motion artifacts) increase incidences of misdetection and false detection because the power consumption and electrode distance of the wearable sensor are limited to reduce its size and weight. To prevent incorrect detection, we use a short-time autocorrelation technique. The proposed method uses similarity of the waveform of the QRS complex. Therefore, it has no threshold calculation Process and it is robust for noisy environment. Simulation results show that the proposed method improves the success rate of IHR detection by up to 37%.

A Wearable Healthcare System With a 13.7 <formula formulatype="inline"><tex Notation="TeX">$\mu$</tex> </formula>A Noise Tolerant ECG Processor

“…However, the method necessitates numerous computations because it calculates the average heart-rate over a long duration (30 s). In our previous work, a short-term autocorrelation (STAC) technique was proposed for IHR detection [22]. Fig.…”

Noise-tolerant instantaneous heart rate and R-peak detection using short-term autocorrelation for wearable healthcare systems

“…Previously, autocorrelation was used in a non-invasive monitoring system [15]. However, the method requires numerous computations because it calculates the average heart-rate over a long duration (30 s).…”

“…7 and (14, 15). (15) The objective of this update is minimization of the window length to reduce the computational amount.…”

A 14 &#x00B5;A ECG processor with robust heart rate monitor for a wearable healthcare system

“…However, the method necessitates numerous computations because it calculates the average heart-rate over a long duration (30 s). In our previous work, a short-term autocorrelation (STAC) technique was proposed for IHR detection [9]. Fig.…”