There isn't an exact minimum per se - the problem is that when you have small samples you have low statistical power, and a higher chance of failing to reject the null hypothesis (equal group means on your outcome variables) even if the population means are not equal - i.e. higher chances of Type 2 error.
What you probably need to is a power analysis - this site has an online calculator you can use. This'll require estimating the mean values and standard deviations for each population (heel pain/normal), which you can do based on the existing literature in the area or informed guesstimates. The calculator then spits out a statistical power figure that indicates the chance of rejecting the null hypothesis given that the null hypothesis is false (or more accurately, that the alternative hypothesis is true at the specified level).
If you find you have statistical power under around 80% for any of the analyses, you probably have a problem. The power depends heavily on the mean difference and standard deviations of the groups - so if you expect large differences between the groups and small standard deviations within them, you might be ok. If not... - 8 is definitely a rather small sample sub-group, I'm afraid.