Curve registration for study of P-wave morphing during exercise
The P-wave shape analysis remains an interesting objective in various situations. In this paper, the aim is to investigate how the P-wave morphology changes during time-varying effort. To perform this task, a method, Self-Modeling Registration (SMR), derived from the Curve Registration (CR) theory is used. This method permits to link different shapes by mean of time warping functions. First, using the SMR method, significant P-wave shapes are extracted from two ECG records under maximal and graded exercise test where the effort is released abruptly. Then, the selected shapes are linked by warping functions estimated by SMR method. The obtained warping functions show a reversible evolution of the P-wave shape independently of the possible superimposition of the T-wave. To give a physiological explanation of this P-wave morphing, an atrial contribution evolution scenario under exercise is proposed and validated by simulation.
New Automated Detection Method of OSA Based on Artificial Neural Networks Using P-Wave Shape and Time Changes
This paper describes a new method for automatic detection of obstructive sleep apnea (OSA) based on artificial neural networks (ANN) using regular electrocardiogram (ECG) recordings. ECG signals were pre-processed and segmented to extract the P-waves; then three P-wave features were extracted: the P-wave duration (Tp), the P-wave dispersion (Pd), and the time interval from the peak of the P-wave to the R-wave (Tpr). Combinations of the three features were used as features for classification using ANN. For each feature combination studied, 70% of the input data was used for training the ANN, 15% for validating, and 15% for testing the results. Perfect agreement between expert’s scores and the ANN scores was achieved when the ANN was applied on Tp, Pd, and Tpr taken together, while substantial agreements were achieved when applying the ANN on the feature combinations Tp and Pd, and Tp and Tpr.
Effects of signaling topic structure on text recall
Two experiments studied effects of signaling devices (headings, overviews, and summaries) on text memory. In Experiment 1, subjects read a text with or without signals, then recalled the topics of the text. Signaling produced better memory for the topics and their organization. In Experiment 2, subjects recalled the content of the text they read, and recalls were scored for the number of accurately recalled ideas. Signals produced recalls that were better organized by text topics. Signals also influenced the distribution of recall of ideas: Subjects remembered more topics but recalled less about each accessed topic if the text they read contained signals than if it did not