J Med Syst - Field programmable gate array based fuzzy neural signal processing system for differential diagnosis of QRS complex tachycardia and tachyarrhythmia in noisy ECG signals.

Tópicos

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Resumo

The paper reports of a Field Programmable Gate Array (FPGA) based embedded system for detection of QRS complex in a noisy electrocardiogram (ECG) signal and thereafter differential diagnosis of tachycardia and tachyarrhythmia. The QRS complex has been detected after application of entropy measure of fuzziness to build a detection function of ECG signal, which has been previously filtered to remove power line interference and base line wander. Using the detected QRS complexes, differential diagnosis of tachycardia and tachyarrhythmia has been performed. The entire algorithm has been realized in hardware on an FPGA. Using the standard CSE ECG database, the algorithm performed highly effectively. The performance of the algorithm in respect of QRS detection with sensitivity (Se) of 99.74% and accuracy of 99.5% is achieved when tested using single channel ECG with entropy criteria. The performance of the QRS detection system has been compared and found to be better than most of the QRS detection systems available in literature. Using the system, 200 patients have been diagnosed with an accuracy of 98.5%.

Resumo Limpo

paper report field programm gate array fpga base embed system detect qrs complex noisi electrocardiogram ecg signal thereaft differenti diagnosi tachycardia tachyarrhythmia qrs complex detect applic entropi measur fuzzi build detect function ecg signal previous filter remov power line interfer base line wander use detect qrs complex differenti diagnosi tachycardia tachyarrhythmia perform entir algorithm realiz hardwar fpga use standard cse ecg databas algorithm perform high effect perform algorithm respect qrs detect sensit se accuraci achiev test use singl channel ecg entropi criteria perform qrs detect system compar found better qrs detect system avail literatur use system patient diagnos accuraci

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