Publications

Atrial Fibrillation Detection Using Swarm Fuzzy Inference System and Electrocardiographic P-Wave Features

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A new technique for detecting atrial fibrillation (AF) is proposed and investigated. The technique employs a swarm fuzzy inference system (SFIS). SFIS is fuzzy system optimized by using a particle swarm optimization (PSO). The technique introduces new inputs for the SFIS to detect AF. The inputs involve the peaks number and width of electrocardiographic P-wave. … Read more

Premature ventricular contraction detection using swarm-based support vector machine and QRS wave features

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A novel strategy for detecting Premature Ventricular Contraction (PVC) is proposed and investigated. The strategy employs a Swarm-based Support Vector Machine (SSVM). An SSVM is an SVM optimised by using Particle Swarm Optimisation (PSO). The strategy proposes new inputs. The inputs involve the width and the gradient of the electrocardiographic QRS wave. Experiments with different … Read more

Evolvable rough-block-based neural network and its biomedical application to hypoglycemia detection system

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This paper focuses on the hybridization technology using rough sets concepts and neural computing for decision and classification purposes. Based on the rough set properties, the lower region and boundary region are defined to partition the input signal to a consistent (predictable) part and an inconsistent (random) part. In this way, the neural network is … Read more