left image

John Guttag

In the age-old rivalry between New York City and Boston, CSAIL may be winning. In a July 2012 story in Boston Globe Magazine about the longstanding competition between the two cities that spans sports, size and now technology, it turns out that New York is drawing inspiration for its newest technological advances from CSAIL.
 
“In his office, Huttenlocher had told me that he saw MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) as an important model of excellence for what he was trying to build. So a few weeks after our meeting, I attend CSAIL’s annual meeting at MIT’s palace of forced architectural funkiness, the Stata Center,” wrote Neil Swidey for the Boston Globe Magazine.


New research from Professor John Guttag, Professor Fredo Durand and graduate student Guha Balakrishnan provides a new means for determining an individual’s heart rate by analyzing an ordinary digital video, with results consistently within a few beats per minute of those produced by electrocardiograms (EKGs). The algorithm developed by the CSAIL researchers analyzes small head movements that accompany the rush of blood caused by the heart’s contractions to accurate determine heart rate.
 
A video-based pulse-measurement system could be useful for monitoring newborns or the elderly, whose sensitive skin could be damaged by frequent attachment and removal of EKG leads.
 


New research by Professor and CSAIL Principal Investigator John Guttag and Professor Collin Stultz is featured in famed photographer Rick Smolan’s new book on big data. The Human Face of Big Data, which will be released in November, was formally announced last week. The book will feature numerous photographs, including one of Guttag and Stultz, depicting the ways in which the massive onslaught of new data being collected through websites, sensors and other channels is being used by scientists to gain new insight into human behavior. Guttag and Stultz developed a new software system that combs through a patient’s EKG data to predict a patient’s risk of death following a heart attack.