Fgrieu has provided a good implementation of your question. But I would add some observations that you might want to consider.
Everything revolves around this entropy heat map:-
The paper's team have done something that I've never seen before. They have used selected NIST tests to qualitatively estimate the entropy coming from various hardware devices. I advisedly use the term qualitatively and not quantitatively as is typical in these cases. They have in fact inverted the usual method for true randomness extraction. So rather than pooling weak entropy and then whitening it with a cryptographic hash function, they have produced the majority of their randomness by initially triaging which bits to use (the black bits) or discard. The team seems to have gotten a reasonable set of final randomness test results, but it's via a very unusual method.
I don't like it. It's never done this way but I accept that that randomness tests can be used to identify random streams, even if they are created artificially. I would suggest that you approach this from the traditional way, and simply XOR all k streams together. Then estimate the entropy rate via Shannon's formula or better still, via compression.
There is a large rider on the paper's findings. The bit streams were taken all together from 37 devices. This is akin to XOR, and vastly improves the entropy of weak sources. XOR 37 of anything, and you'll probably get good entropy. You may find that in your case, each stream in itself is very weak. You need to measure it traditionally to know for sure.