I have acceleration data in 3D vectors (x
,y
,z
).
For detecting certain patterns within the data stream, I use a fixed moving window to generate many statistic features, like mean, max, kurtosis,...
I use these feature vectors to detect key strokes.
My results are already quite ok, but I want to improve them.
And many papers in this field used the fourier transformation (or fft
) to improve their results.
I never worked in the frequency domain, so I don't know what this is used for and what information I could gain from using fft
.
Most articles I found on this topic are focused on audio stuff.
Here a sample plot of the data I capture (only the right graph):
These graphs correspond to the sequence of "0123034880". The spikes occur during a tap event
Can someone please give me a more general explanation of the fft
and what information I can gain from it having a time series of data?