Online interpolation of temporal signal
The idea of applying interpolation works well when you have a very high sampling rate. In some sense, what you are trying to do here is fit the missing data between the second and third green bars.

Approach

This approach is motivated from the results discussed in [1].


Construct gapped IMFs (Intrinsic Mode Functions)
Fill in gaps in each mode, based on geometrical constraints
Add up all gap-filled IMFs


Though, I am not sure if this can be implemented in real-time. You can make assumption that you are processing 100 ms data in every batch.

Reference

[1] A. Moghtaderi, P. Borgnat and P. Flandrin, "Gap-filling by the empirical mode decomposition," 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Kyoto, 2012, pp. 3821-3824.