… ECG segmentation based on hierarchic continuous density hidden Markov models. We …
previous state at time t − 1, ie P(St|St−1,St−2, ..., S1) = P(St|St−1). A continuous density HMM of …

… one state produces one single observation, a state in a semi-Markov model is defined as …
from one single signal, ie the RR series and the QRS durations from the same ECG signal in …

… a hidden Markov model to represent one beat of the signal. After … The signal is sampled at
1 kHz and bandpass filtered … transform with 4-levels of resolution is applied to the ECG signal. …

… series were extracted from the ECG of 32 preterm infants with frequent AB episodes as
described in [3, 17]. This procedure comprises: (1) beat detection from ECG signals and (2) the …

… The electrocardiogram (ECG) is the gold standard for HSS and it is generally … the ECG signal
are the corresponding positions of S1 and S2, respectively [13], as shown in Figure 1. Thus, …

… Conclusions: This study suggests that automatic OSA recognition from single-lead ECG
signals is possible, which can be used as an inexpensive and low complexity burden alternative …

… We show in figure 1 the one period (cycle) estimation by PSWT for different types of … single
set is performed with HSMM as described in section 3. We use the PSWT of the ECG signal as …

… The core of our method is the modeling of cardiac beats by a … designed for modeling each
cardiac waveform by a single function… The ECG signal is subsequently segmented into cardiac …

… a frequency of approximately 1 Hz. One cardiac cycle in an ECG signal consists of the P-QRS-T
waves. The majority of the clinically useful information in the ECG is originated in the …

… When applying the KLT, each heartbeat in the ECG signal is treated as a separate data vector.
… This particular cost function may be interpreted as the entropy of a Gauss-Markov process …