BackgroundDetection of characteristic waves, such as QRS complex, P wave and T wave, is one of the essential tasks in the cardiovascular arrhythmia recognition from Electrocardiogram (ECG).MethodsA multiscale morphological derivative (MMD) transform-based singularity detector, is developed for the detection of fiducial points in ECG signal, where these points are related to the characteristic waves such as the QRS complex, P wave and T wave. The MMD detector is constructed by substituting the conventional derivative with a multiscale morphological derivative.ResultsWe demonstrated through experiments that the Q wave, R peak, S wave, the onsets and offsets of the P wave and T wave could be reliably detected in the multiscale space by the MMD detector. Compared with the results obtained via with wavelet transform-based and adaptive thresholding-based techniques, an overall better performance by the MMD method was observed.ConclusionThe developed MMD method exhibits good potentials for automated ECG signal analysis and cardiovascular arrhythmia recognition.
b) Figure 1. Examples of different shapes a Robogami can transform into (a) a table (b) a pinwheel.
Abstract-The robotic origami (Robogami) is a low-profile, sheet-like robot with multi degrees-of-freedom (DoF) that embeds different functional layers. Due to its planar form, it can take advantage of precise 2D fabrication methods usually reserved for micro and nano systems. Not only can these methods reduce fabrication time and expenses, by offering a high precision, they enable us to integrate actuators, sensors and electronic components into a thin sheet. In this research, we study sensors, actuators and fabrication methods for Robogami which can reconfigure into various forms. Our main objective is to develop technologies that can be easily applied to Robogamis consisting of many active folds and DoFs. In this paper, after studying the performance of the proposed sensors and actuators in one fold, we use a design for a crawler robot consisting of four folds to assess the performance of these technologies.
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