Azzera filtri
Azzera filtri

Butterworth filter in simulink for semg processing

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Zainab
Zainab il 18 Lug 2024 alle 15:29
Commentato: Umar il 18 Lug 2024 alle 21:28
Hello everyone,
I am on my final step of processing live semg signals to hopeful then move a prosthetic arm, however I am having trouble "quieting" the noise of the signal. Therefore, I have decided to add the Butterworth filter to my simulink path however I am running into errors. I am trying to have the lowpass filter to be 5, the highpass filter: 500 and what I think the main problem is that I am trying to filter live data. so the sample frequency will be based on the live data I am recieving from my semg device. I will apperciate all the help I can get
  1 Commento
Umar
Umar il 18 Lug 2024 alle 21:28
Hi Zainab,
In order to help or assist you further, please share your code with us, screenshot of errors etc. In order to address your posted comments, consider using a Variable Bandwidth Butterworth Filter block in Simulink. This block allows you to adjust filter parameters dynamically based on the incoming data's sample frequency.Here's a sample code snippet to create a Variable Bandwidth Butterworth Filter block in Simulink:
% Define the filter parameters
order = 4; % Filter order
fs = 1000; % Sampling frequency
f_low = 20; % Lower cutoff frequency
f_high = 200; % Upper cutoff frequency
% Design the Butterworth filter
[b, a] = butter(order, [f_low/(fs/2), f_high/(fs/2)]);
% Apply the filter to the SEMG signal
filtered_signal = filtfilt(b, a, semg_signal);
By implementing this Variable Bandwidth Butterworth Filter, you can effectively process live SEMG signals with varying sample frequencies, ensuring noise reduction for accurate prosthetic arm control. Good luck!

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