Heartbeat Detection Using Energy Thresholding and Template Match

Abstract

Heartbeat detection is very important for retrieving the vital signs of heart functions. The morphologies and inter-beat intervals of heartbeats can reveal the condition of heart contraction. In this paper, we developed a heartbeat information integration scheme to deal with the information yielded by the energy thresholding and template match methods, which are usually used to detect the heartbeats and match the QRS, respectively. The proposed method are developed in SIMULINK 2.0 and assessed by the MIT/BIH arrhythmia database. The result demonstrated excellent sensitivity of detecting QRS and ventricular premature contraction in the proposed method.

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

“…Autocorrelation [19], [20] and template matching [21] are more robust approaches to prevent incorrect detection because these algorithms use the similarity of QRS complex waveforms and have no threshold calculation process. Autocorrelation has been used in a non-invasive monitoring system [20].…”

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

“…Autocorrelation [6,7] and template matching [8] are more robust approaches to prevent incorrect detection because these algorithms use the similarity of QRS complex waveforms and have no threshold calculation process. Autocorrelation has been used in a non-invasive monitoring system [7].…”

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

“…Autocorrelation [12,13] and template matching [14] are more robust approaches because these algorithms utilize the similarity of QRS complex waveforms and have no threshold calculation process. Previously, autocorrelation was used in a non-invasive monitoring system [15].…”