A low-complexity ECG processing algorithm based on the Haar wavelet transform for portable health-care devices

Abstract

This paper presents a simple Electrocardiogram (ECG) processing algorithm for portable healthcare devices. This algorithm consists of the Haar wavelet transform (HWT), the modulus maxima pair detection (MMPD) and the peak position modification (PPM). To lessen the computational complexity, a novel no multiplier structure is introduced to implement HWT. In the MMPD, the HWT coefficient at scale 24 is processed to find candidate peak positions of ECG. The PPM is designed to correct the time shift in digital process and accurately determine the location of peaks. Some new methods are proposed to improve anti-jamming performance in MMPD and PPM. Evaluated by the MIT-BIH arrhythmia database, the sensitivity (Se) of QRS detection is 99.53% and the positive prediction (Pr) of QRS detection is 99.70%. The QT database is chosen to fully validate this algorithm in complete delineation of ECG waveform. The mean µ and standard deviation σ between test results and annotations are calculated. Most of σ satisfies the CSE limits which indicates that the results are stable and reliable. A detailed and rigorous computational complexity analysis is presented in this paper. The number of arithmetic operations in N input samples is chosen as the criterion of complexity. Without any multiplication operations, the number of addition operations is only about 16.33N. This algorithm achieves high detection accuracy and the lower computational complexity.