Pain is typically measured through patient reports, behavioral and biological assessments, which are highly subjective. In addition, self-reporting is difficult for certain populations such as children and older adults. Thus, there is a need for diagnostic technologies that can correctly diagnose pain.
Dr. Tor Wager's team at the University of Colorado Boulder has used functional magnetic resonance imaging or fMRI coupled with machine learning techniques to identify neurologic pain signatures that allow for objective measurement of acute and chronic pain.
Globally, 1.5 billion people suffer from moderate to chronic pain. In the US alone, persistent pain affects 100 million adults and accounts for $600 billion in annual medical costs and loss of productivity.