Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The paper presents an example of model-based estimation of blood pressure parameters (onset, systolic and diastolic pressure) from continuous measurements. First, the signal was low pass filtered and its quality was estimated. Good quality periods re divided into beats using an electrocardiogram. Next, the beginning of each beat of the blood pressure signal was approximated basing on the function created from the sum of two independent distributions: Gaussian and exponential. The nonlinear least square method was used to fit measurement data to the model. The initial conditions for the fitting procedure re selected for each beat on the basis of its parameters. Finally, the diastolic and systolic values of blood pressure and onset re determined.
['Artur Polinski', 'Tomasz Kocejko']
I am writing a research paper on a idea Estimation of blood pressure parameters using ex-Gaussian model
[{"from": "human", "value": "I am writing a research paper on a idea Estimation of blood pressure parameters using ex-Gaussian model"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The paper presents an example of model-based estimation of blood pressure parameters (onset, systolic and diastolic pressure) from continuous measurements. First, the signal was low pass filtered and its quality was estimated. Good quality periods re divided into beats using an electrocardiogram. Next, the beginning of each beat of the blood pressure signal was approximated basing on the function created from the sum of two independent distributions: Gaussian and exponential. The nonlinear least square method was used to fit measurement data to the model. The initial conditions for the fitting procedure re selected for each beat on the basis of its parameters. Finally, the diastolic and systolic values of blood pressure and onset re determined."}]