Breakthrough technology to detect pain
Maxi Rodriguez of Liverpool is injured during the Barclays Premier League match between Chelsea and Liverpool at Stamford Bridge on February 6, 2011 in London, England.
Dr. Sean Mackey is chief of the division of pain management at Stanford University School of Medicine. Using a neuro-imaging scanner, his team has been able to look at patterns of brain activity and determine whether somebody is actually in pain. Think of what that means for someone who has suffered a stroke and is unable to speak. Think of what that means for newborn babies in a neonatal intensive care unit.
Mackey says the nature of pain has made this a hard technology to develop: "The first thing we have to recognize is that pain is by its very definition a subjective experience, not unlike other subjective experiences like love, fear, hate. For many, many decades, we've been trying to find the pain meter, people have used blood pressure changes, heart rate changes, facial grimacing. The problem is all of them have been inadequate."
Mackey uses a system called "machine learning," which associates brain wave patterns with particular meanings. He says, "We train this computer algorithm, based upon a known set of parameters. In this case, whether someone is in pain or not in pain. And we run this over and over and the machine algorithm learns. And then what we do is we feed it novel independent subjects the computer has never seen. Take your best guess on whether these people who it had never seen before, never seen this data were in pain or not in pain."
The computer ended up being right over 80 percent of the time, which was the real Eureka moment. The research is far from complete, however. Mackey and his colleagues will be looking at how to apply these tools. "An additional application of this," he says, "is the way of having an objective bio-marker of pain that we can use to tailor our treatments for an individual person. Wouldn't it be wonderful if we had a way of objectively determining whether therapy was working for a specific person? And we understood why so we could do without that laborious trial and error process we currently go through of giving patient one treatment after another until we find something that works."
Also in today's program, a short play about Amazon.com's partnership with libraries to lend Kindle books.