How to Extract the following Frequency-domain Features in Python?

Question

Please feel free to point out any errors\/improvements in the existing code<\/h3>

So this is a very basic question and I only have a beginner level understanding of signal processing. I have a 1.02 second accelerometer data sampled at 32000 Hz. I am looking to extract the following frequency domain features after having performed FFT in python -

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The csv file containing data has four columns: Time, X Axis Value, Y Axis Value, Z Axis Value (The accelerometer is a triaxial one). So far on python, I have been able to visualize the time domain data, apply convolution filter to it, applied FFT and generated a Spectogram that shows an interesting shock

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#Matrix needs to be transformed in order to have horizontal time domain mfcc_features = mfcc_features.T plt.matshow(mfcc_features) plt.title('MFCC')<\/code><\/pre>
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Answer 1

我认为您的fft摄取程序不正确，fft输出通常是峰值，而在进行abs吸收时应该是一个峰值， 因为 ，可能应该将其更改为Y = np.fft.fftshift(np.abs(np.fft.fft(signal)))到Y=np.abs(np.fft.fftshift(signal)

Answer 2

Did you ever have any luck with generating RMSF, spectral kurtosis and spectral skewness? I'm struggling with these two.