As you probably know by now, I WAS doing a PhD at the University of New South Wales. My PhD is in machine learning in temporal domains. Machine Learning is a subfield of Artificial Intelligence, which is a subfield of Computer Science.
But now I am finished -- well, not exactly. I'm still waiting on the reviews to come back. They could refuse to give me a PhD, advise major or minor corrections.
You may also be interested in my Temporal Machine Learning page, which has links to researchers working on similar problems.
Here are some photos of the system: Equipment Glove In operation Everything
This is the data used in my thesis. It's available here as a bzipped, tarred, file. The file consists of 9 subdirectories tctodd1-9. Each directory consists of 3 samples of each sign, captured on a different day. In total there are 95 different signs, with 27 samples per sign. Signs were provided by a native signer volunteer.
Each file consists of a sequence of lines. Each line consists of 22 whitespace-separated numbers representing the 22 channels of information. The list of channels can be found in the domain description file. It also lists the classes. More information can be found in my PhD thesis above, in particular, section 6.3.1, and some in my honours thesis.
Finally, there's a list of the files and their class labels.
The files are: