RESUMO
This paper introduces a new approach to process biomedical signals by surgically removing wave deflections in time domain. The method first determines the epochs of high frequency deflections, cuts out them from the signal, and then connects the two disconnected points. To determine the epoch of a deflection to be removed, four slope trace waves are used to isolate the deflection based on signal characteristics of amplitude, slope, duration, and distance from neighboring deflections. The method has been applied to simulated data and MIT-BIH arrhythmia database to show its practical efficacy in the case of baseline wandering removal. It is found that the method has the capability to identify and remove high frequency deflections appropriately, leaving low frequency deflection such as baseline drifting.
Assuntos
Algoritmos , Eletrocardiografia/estatística & dados numéricos , Arritmias Cardíacas/diagnóstico , Arritmias Cardíacas/fisiopatologia , Engenharia Biomédica , Bases de Dados Factuais , Diagnóstico por Computador , Humanos , Processamento de Sinais Assistido por ComputadorRESUMO
In this paper a simple signal segmentation algorithm is introduced. The algorithm determines the epochs of signal components of interest based on signal characteristic such as amplitude, slope, deflection width, or distance between neighboring deflections. The epochs are segmented indirectly by means of a slope trace wave that traces a signal with its average slope and predetermined delay. The algorithm is applied to ECG and electrogram to show its practical applicability and efficiency. It is found that the algorithm can be used to choose particular signal components appropriately without significant signal preprocessing or complexity.
