That's like asking if moving averages are useful. Of course they are, because they are components of basic signal processing. What you do with the data however is entirely on you. Most of these techniques are to improve the signal-to-noise ratio, but they won't help if you don't have an idea of what you are trying to look for in the first place.

More broadly, financial markets (in certain cases and depending on asset) can generally be modeled by a random walk, and that's something Kalman filters can help with as mentioned in another comment.