A Collective Biological Processing Algorithm for ECG Signals
نویسنده
چکیده
We establish and explore an analogy between hunting by packs of agents and signal processing. We present a version of adaptive ‘Hunting Swarm’ algorithm (HSA), apply it to EKG signals, and investigate the influence of the model parameters on the filtering of stationary and nonstationary noise. We show that results obtained with the HSA filter may outperform results obtained with several other filters.
منابع مشابه
Determining the Proper compression Algorithm for Biomedical Signals and Design of an Optimum Graphic System to Display Them (TECHNICAL NOTES)
In this paper the need for employing a data reduction algorithm in using digital graphic systems to display biomedical signals is firstly addressed and then, some such algorithms are compared from different points of view (such as complexity, real time feasibility, etc.). Subsequently, it is concluded that Turning Point algorithm can be a suitable one for real time implementation on a microproc...
متن کاملAdaptive-Filtering-Based Algorithm for Impulsive Noise Cancellation from ECG Signal
Suppression of noise and artifacts is a necessary step in biomedical data processing. Adaptive filtering is known as useful method to overcome this problem. Among various contaminants, there are some situations such as electrical activities of muscles contribute to impulsive noise. This paper deals with modeling real-life muscle noise with α-stable probability distribution and adaptive filterin...
متن کاملA comprehensive model using modified Zeeman model for generating ECG signals
Developing a mathematical model for the artificial generation of electrocardiogram (ECG) signals is a subject that has been widely investigated. One of its uses is for the assessment of diagnostic ECG signal processing devices. So the model should have the capability of producing a wide range of ECG signals, with all the nuances that reflect the sickness to which humans are prone, and this ...
متن کاملClassification of ECG signals using Hermite functions and MLP neural networks
Classification of heart arrhythmia is an important step in developing devices for monitoring the health of individuals. This paper proposes a three module system for classification of electrocardiogram (ECG) beats. These modules are: denoising module, feature extraction module and a classification module. In the first module the stationary wavelet transform (SWF) is used for noise reduction of ...
متن کاملA Novel Blind Watermarking of ECG Signals on Medical Images Using EZW Algorithm
Introduction:In this study, ECG signals have been embedded into medical images to create a novel blind watermarking method. The embedding is done when the original image is compressed using the EZW algorithm. The extraction process is performed at the decompression time of the watermarked image. Materials and Methods: The multi-resolution watermarking with a secret key algorithm developed in th...
متن کامل