Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Ventricular fibrillation (VF) is a medical condition that occurs due to rapid and irregular electrical activity of heart. If undiagnosed or untreated, VF leads to sudden cardiac death. VF has been studied by researchers for over 100 years to elucidate the mechanism that maintains VF, and thus to arrive at therapeutic options. VF is a nonstationary process, and it manifests into variations in the waveform morphology, phase, and frequency dynamics of the surface electrograms. Dominant frequency analysis (DF maps) and phase maps are two widely used complementary approaches in assessing the evolution of VF process. These techniques are applied to electrograms or fluorescence signals obtained with voltage-sensitive dyes. In spite of VF being a nonstationary process, most of the existing literature limits frequency analysis to a segmented, time-averaged spectral analysis, where valuable information on the instantaneous temporal evolution of the spectral characteristics is lost. In order to resolve this issue, in this paper,  present a joint time-frequency approach that is suited for VF analysis and demonstrate the application of instantaneous mean frequency (IMF) in interpreting VF episodes. Human VF sources are rarely anatomically stable and are migratory. Traditional DF techniques fail in tracking this migratory behavior. IMF, on the other hand, can deal with these migratory sources and conduction blocks better than DF approaches. Results of the analysis using the electrograms of 204 VF segments obtained from 13 isolated human hearts (explanted during cardiac transplantation) indicate that in 81% of the VF segments, there re significant changes in the spatiotemporal evolution of the frequency, suggesting that IMF provides better mechanistic insight of these signals. The IMF tool presented in this paper demonstrates potential for applications in tracking frequency patterns, conduction blocks, and arriving at ner therapies to modulate VF.
['Karthikeyan Umapathy', 'Stephane Masse', 'Elias Sevaptsidis', 'John Asta', 'Sridhar Krishnan', 'Kumaraswamy Nanthakumar']
I am writing a research paper on a idea Spatiotemporal Frequency Analysis of Ventricular Fibrillation in Explanted Human Hearts
[{"from": "human", "value": "I am writing a research paper on a idea Spatiotemporal Frequency Analysis of Ventricular Fibrillation in Explanted Human Hearts"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Ventricular fibrillation (VF) is a medical condition that occurs due to rapid and irregular electrical activity of heart. If undiagnosed or untreated, VF leads to sudden cardiac death. VF has been studied by researchers for over 100 years to elucidate the mechanism that maintains VF, and thus to arrive at therapeutic options. VF is a nonstationary process, and it manifests into variations in the waveform morphology, phase, and frequency dynamics of the surface electrograms. Dominant frequency analysis (DF maps) and phase maps are two widely used complementary approaches in assessing the evolution of VF process. These techniques are applied to electrograms or fluorescence signals obtained with voltage-sensitive dyes. In spite of VF being a nonstationary process, most of the existing literature limits frequency analysis to a segmented, time-averaged spectral analysis, where valuable information on the instantaneous temporal evolution of the spectral characteristics is lost. In order to resolve this issue, in this paper,  present a joint time-frequency approach that is suited for VF analysis and demonstrate the application of instantaneous mean frequency (IMF) in interpreting VF episodes. Human VF sources are rarely anatomically stable and are migratory. Traditional DF techniques fail in tracking this migratory behavior. IMF, on the other hand, can deal with these migratory sources and conduction blocks better than DF approaches. Results of the analysis using the electrograms of 204 VF segments obtained from 13 isolated human hearts (explanted during cardiac transplantation) indicate that in 81% of the VF segments, there re significant changes in the spatiotemporal evolution of the frequency, suggesting that IMF provides better mechanistic insight of these signals. The IMF tool presented in this paper demonstrates potential for applications in tracking frequency patterns, conduction blocks, and arriving at ner therapies to modulate VF."}]