Medical
applications
This group of
projects is similar to brain decoding projects in that here we
also use techniques from machine learning and statistical pattern
recognition to analyze medical data. However, in the case of medical
applications the
emphasis is more on diagnosis, monitoring and prediction. In
contrast to brain decoding projects, where we analyze only brain
signals, here we use EEG as well as other
physiological signals, such as the ECG,
galvanic skin response (GSR), and blood pressure and pulse.
Furthermore, in addition to analyzing neuroimages (such as fMRI
data), we consider various other medical images such as the
microscopic images obtained from biopsies.
We have recently
acquired a portable device for measuring biosignals (from
Guger Technologies) that
allows us to analyze brain, heart, and muscle-activity, eye movements,
respiration, galvanic skin response, and other body signals in
real-time. We are exploring applications to: health
monitoring, in-home training of elderly patients using neurofeedback,
and assessing and predicting a person’s cognitive performance while
operating in complex real-world sensory environments.
Some of the projects
are:
