A piecewise geometric analysis method for real-time ambulatory ECG detection

Abstract

Abstract. BACKGROUND:As one of the pervasive healthcare services, Ubiquitous cardiac care (UCC) systems should have at least two significant characteristics: real-time detection capability for cardiac arrhythmia events and a small resource requirement for its computation and storage. PURPOSE: Due to the strict-constrained system support and ambulatory signal quality in the out-of-hospital pervasive healthcare applications, a dedicated real-time AED (Ambulatory Electrocardiograph Detection) algorithm has been implemented. METHODOLOGY: By adopting the piecewise geometric analysis method, this algorithm can provide a real-time continuous detection capability for QRS complexes, which consists of three main functional modules: the Data preparation; the R-wave vertex discovery; and the QRS complex recognition. Currently, this algorithm has been applied on an on-line UCC application system at the hospital for more than 30 patients. RESULT: The performance evaluation has been made not only on the standard MIT-BIH cardiac arrhythmia database but also on the clinical testing. The experiential results explore this algorithm has in average sensitivity of 99.37% and specificity of 99.72%. CONCLUSION: This AED algorithm has minimal beat detection latency and a less computation consumption, which make it meet the requirements of ubiquitous cardiac care applications.

A Novel Cardiac Arrhythmias Detection Approach for Real-Time Ambulatory ECG Diagnosis

“…Based on a dedicated temporal-domain feature extraction technique, 33 the features values are achieved to establish the diagnostic criteria and to grade the emergency events of cardiac arrhythmias, shown in Table 3. In particular, VT and VF, as the life-threatening cases that need for quick identi¯cation, have the highest priority-red.…”