I've done a little work in this, and some related areas, and my response to the question depends on how much time you've got:
Short answer: Yes, with a but.
Simply put, as you've discovered previously, there are similarities in observed keystroke (or other behavioral biometric patterns). These can, theoretically, be used for additional security, but the false-positive and false-negative rates are still comparatively high, so usability is questionable, and there aren't any pre-built libraries that I would recommend as reliable.
Longer Answer: No, with a however.
The problem with behavioral biometrics in the context of security is that it doesn't fit with our current models. If you're given a password, it's either right, or it's wrong. If something's measuring your iris, it's a match or it isn't. There's no leeway or wiggle room, one or the other, binary authentication.
Behaviorals don't do this. Behaviors change depending on the time of day, the time of month, the weather outside. You can say "this looks like this person", but there's no cut and dry "yes/no" response, which makes them bad at traditional authentication, particularly with short sample sizes like passwords.
On the other hand, there are a lot of behavioral analytics that can be measured (network usage, keystroke, mouse usage, movement, and a wealth of others). These can be combined to give a sustained confidence indication over a prolonged period. So, for example, you could log onto your machine, and it wouldn't let you access your bank because it's not verified you yet. Do a few other things you need to, work for a while, and the algorithms return a good confidence value, and access is granted to privileged systems.
Essentially, the binary authentication routes currently in place are not well suited to behavioral biometrics, but there's a lot of promise for trust-based authentication further down the line.