Development of QRS Detection using Short-time Fourier Transform based Technique

Abstract

This paper reports our study in QRS complex detection. The short-time Fourier transform (STFT) was employed in ECG filtering stage. The narrow rectangular window was used to transform ECG signals into time-frequency domain. The temporal information at 45 Hz from spectrogram was analyzed for detecting QRS locations. The automated thresholding combined with local maxima finding method was modified to find the QRS location. The data used in this study is MIT-BIH Arrhythmia database. As the results, our proposed technique achieved the detection rate better than 99% and fail ratio was 1.3%.

On the Beat Detection Performance in Long-Term ECG Monitoring Scenarios

“…Other families have not been considered here because they seem not to match with the specific LTM criteria, specially the computational efficiency. As an example, time–frequency analysis methods offer a versatile representation in both the frequency and time domains, by varying the scaled parameters according to global and local signal features, as in the case of detectors based on CWT [ 31 ], Discrete Wavelet Transformation [ 34 ], STFT [ 32 ], HiT [ 33 ], or HHT and Empirical Mode Decomposition [ 35 ]. The adaptation ability of these methods demand high computational requirements, which currently precludes their use in LTM scenarios.…”

“…Examples of this second type include the very well-known PT, as well as the Hamilton–Tompkins (HT) and the Chouhan methods [ 9 , 28 , 29 , 30 ]. Table 2 shows the accuracy rates benchmarked over the MIT–BIH of relevant methods on the literature, such as Continuous Wavelet Transform (CWT) [ 31 ], Short Time Fourier Transform (STFT) [ 32 ], Hilbert Transform (HiT) [ 33 ], or Hilbert–Huang Transform (HHT). These reported values should be considered as the standard target accuracy also for LTM scenarios, but the methods should also be competitive in terms of computational cost, taking into account the dramatically longer signal duration.…”

Analysis of Human Electrocardiogram for Biometric Recognition Using Analytic and AR Modeling Extracted Parameters

“…A number of research papers have investigated the problem of accurate QRS complex detection depending on the applications of wavelet filter banks [22] and the modified p-spectrum to detect heart beats in ECG signals [23]. The short-time Fourier transform (STFT) was also employed after ECG filtering stage in order to detect QRS complex [24].…”

Vizsgálati módszerek fejlesztése és alkalmazása a neurokardiológiai fluktuációk automatizált feldolgozásában

“…A neurokardiológiai jelek teljes Fourier-spektruma helyett gyakran a pontosabb képet szolgáltató időfüggő spektrális analízist [43][44] vagy wavelet-ábrázolást [45][46] használ-nak, mely az időben változó frekvenciatulajdonságokat is képes megjeleníteni.…”

“…Az alábbi ábrán a manuális eljárás gépi, automatizált implementációjának 'beatto-beat' eredményei láthatók, eltérő távolságú vizsgálópontok esetén. 44. ábra.…”