Filtering out spikes in data at n*60 +1

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Emma Walker
Emma Walker 2021-11-29
评论： Emma Walker 2021-11-29
Hello,
I have been working on a spectogram figure for some time now and have been unsuccessful in eliminating spikes in the data that occur at every 60 plus 1 i.e. 61, 121,181, ... etc. I have tried treating my data with a notch filter, filtfilt, medfilt1, and sgolay filt. In the past, I tried whitening it and using an fft to no advantage. Ideally, I would like to use something like butter or fir1 but this is a recorded data set with 64 channels and not a set frequency. What would be the best way to go about filtering this? Aside from the sgolay figure, the results are identical.
Sgolay: third order, framelength of 61
All of the other filters:
Below are the notch filters:
%% Notch Filter: Did not work
% method 1:
wo = 61/(30000/2); %removes 60Hz tome from a signal at 30,000 Hz
bw = wo/35; % Q factor of 35, this can be modified for varied results
[b,a] = iirnotch(wo,bw); % output's num and dom but we are not workign with a function to which they can be applied
% method 2: design butterworth notch filter
% d = designfilt('bandstopiir','FilterOrder',2, ...
% 'HalfPowerFrequency1',60,'HalfPowerFrequency2',62, ...
% 'DesignMethod','butter','SampleRate',samplingRate);
% dataFilt = filtfilt(d,lfp.data);
dataFilt = filtfilt(b,a,lfp.data);
Below are the other filters:
%% Median Filter: did not work
dataFilt = medfilt1(lfp.data,3);
%% Standard Filter: requires the inpouts of numerator and denominator functions 'filter(n,d,X)' where X is the data set, we are not trying to match this data to a filter
% did not work
dataFilt = filter(61,1,lfp.data); % the 1/1 is just a test
%% Savitzky - Golay Filter:
order = 3;
framelength = 61;
dataFilt = sgolayfilt(lfp.data, order, framelength);
%% FIR - Bandpass filter
dataFilt = fir1(lfp.data,60);
Thank you for taking a look at this. There must be a simple way to accomplish this.

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Image Analyst
Image Analyst 2021-11-29
If you know the indexes, how about just setting them to zero, or the median of neighboring values.
smoothy = movmedian(y, 5); % Smooth it
index = find(x == 181);
y(index) = smoothy(index); % Replace with median.
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Emma Walker
Emma Walker 2021-11-29
Thank you very much. This would have been a better approach. What do you mean by 'x' here instead of just having the index within the parentheses?

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