Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A time lagged feedforward artificial neural network (TLFN) is used to detect QRS complexes for pacemakers in a noisy environment. The TLFN reduces the influence of lor frequencies in the invasive electrogram (EG) signals, such as the P and T waves. The TLFN output is then subjected to matched filtering with a dynamically updated impulse response. Detector performance is studied by means of databases containing electrograms and noise such that different types of noise and interferences from electronic appliances are added to the electrograms. Results show that the detector performs ll in many different noisy environments by considerably improving the signal-to-noise ratio (SNR).
['J. Neves Rodrigues', 'Viktor Öwall', 'Leif Sörnmo']
I am writing a research paper on a idea QRS detection for pacemakers in a noisy environment using a time lagged artificial neural network
[{"from": "human", "value": "I am writing a research paper on a idea QRS detection for pacemakers in a noisy environment using a time lagged artificial neural network"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: A time lagged feedforward artificial neural network (TLFN) is used to detect QRS complexes for pacemakers in a noisy environment. The TLFN reduces the influence of lor frequencies in the invasive electrogram (EG) signals, such as the P and T waves. The TLFN output is then subjected to matched filtering with a dynamically updated impulse response. Detector performance is studied by means of databases containing electrograms and noise such that different types of noise and interferences from electronic appliances are added to the electrograms. Results show that the detector performs ll in many different noisy environments by considerably improving the signal-to-noise ratio (SNR)."}]