best technique to remove noise from bio signal data I'm still learning about signal processing so sorry if this is an intro problem. I want to remove noise from the following data so I can separate each wave and run analysis on it.

The data is sampled at 41 hz, the red is the raw data and the blue is the data that I applied a lowess filter to with a window size of 41. As you can see it is smoothed to some extent but there is still a lot of peaks and noise in the mix. 

I read that you can use RNN or PCA or FFTs to remove noise for bio-signal data, in this case, what are the best techniques to remove noise from the red data so that the blue line is just 5 waves that is easily identifiable? 

My ideal result is that after applying the filter I can easily tell that there is 5 waves in this period of data and the resulting index of said waves.
Any input is appreciated!
As a first appraoch I would suggest to use a mean filter, which will calculate the average of the last n values.

$$y[n] = 1/N \sum_{k=0}^{N-1} x[n-k]$$

If you have access to the full signal (offline processing) you can perform forward and backward filtering which will avoid the delay introduced by a single filter. (Check matlab's filtfilt function for example)