The aim of this project is to design a platform to optimally estimate blood pressure using live ECG (Electrocardiogram) and PPG (Photoplethysmogram) based on PTT (Pulse Transit Time) and wavelet transform and Nueral Network for accuracy.
I already have the code of matlab I need to fix it and I need to take less sample than 400. So make 300 samples and need to filter that ecg signal. Bcos it’s not looks exact as ecg.
Using PPG to predict blood pressure may depend on the subject's body status. If there is a patient with heart diseases, this model will not be properly applied in business. But a small dataset may meet your requirement Daha Fazla
Bu iş için 8 freelancer ortalamada $172 teklif veriyor
Hello, there, I am very happy to put my bid on your project. I am an expert of algorithm and senior software developer, so I am interested in and confident to do this project. I hope to discuss everything of the pro Daha Fazla
I have well experienced in doing such kind of jobs............................................and i will do my level best..............
Expert in Matlab, Simulink, Power System, Signal Processing, Image Processing Artificial Intelligence. Excellent in Electrical Engg. Algorithms development, Power system, power electronics & drives. PV generation, Wi Daha Fazla
Hi, I'm a signal processing expert having lots of experience in Matlab programming and simulation. I can do your project in a couple of hours. You can find similar Matlab projects in my previous works by checking my pr Daha Fazla
I have experience in filtering ECG signals to remove noise and calculate the patients Heart Rate. Please look at the first item in my freelancer portfolio "EMI Suppression in biomedical signals". There are some more Daha Fazla
Hi,sir, I'm sure that I can be a excellent candidate for your project. Please contact me, so that we can discuss more over chat. I value my credits from clients. Thank you for your reading. I have worked for a long ti Daha Fazla
I have designed hardware and software for diagnoses of heart diseases by classification of RR interval.