Even window sizes up to 10 would not produce reliable results for fluctuations. So you should be careful to remove trends but leave the internal dynamics of the system for which you assume power law. DFA1 should be able to remove constant trend, DFA2 linear trend and so on. Another available option is to produce data with a periodic trend. You can observe the transition between two phases also and to see the differences in the heartbeat rate, in the variability of the signal, and in scaling properties of the data.
Some patients are divided to groups of healthy and sick.
Another kind of data is measurements of temperature in different cities for years. You can again check the scaling properties of this data within a couple of days, during one year or for a couple of years.