MIT Media Lab researchers Rosalind Picard, Matthew Goodwin and Rana el Kaliouby, along with collaborators at five other institutions, recently received a joint $10 million, five-year National Science Foundation (NSF) Expeditions award to develop novel technologies for measuring and analyzing behavior during face-to-face social interactions.
This collaboration will be the first large-scale effort of computer and behavioral scientists to jointly address diagnosing and intervening early in the lives of those with Autism spectrum disorders (ASD).
ASD, which refers to a group of complex neurodevelopmental disorders that cause social, communication and behavioral impairments in children and adults, currently affects 1 in 110 children in the United States. In addition, ASD has a substantial economic impact on society, with the lifetime cost of care for those with ASD exceeding $3 million per person.
Over the past several years, Media Lab researchers have developed a number of technologies to track and measure emotional states, and, working with the ASD community, refined them into specialized tools. These technologies include novel wearable physiological sensors and corresponding software that can be used to measure variables such as heart rate and skin conductivity — indicators of internal stress and arousal. These technologies provide new, more precise ways to understand behavior, and will help individuals with ASD communicate cognitive and emotional states, as well as help others — scientists, therapists, teachers, caregivers — to understand those states.
Along with colleagues at the other institutions included in the grant — Georgia Tech, Carnegie Mellon, the University of Southern California, Boston University and the University of Illinois at Urbana-Champaign — the Media Lab team will apply its expertise to the building of test beds and methodologies for capturing behavior data accurately and noninvasively, resulting in a more objective, data-driven approach to behavioral assessment. This multi-year, multi-step program will include research in computer vision, audio and speech analysis, and physiological recording with wireless sensors.
This NSF-funded collaborative project aims to combine computer science and behavioral science to create an entirely new field of inquiry: computational behavior science. Just as medical imaging such as MRIs or X-rays have allowed doctors to identify and treat previously unobservable problems (a brain tumor, aneurysm, a broken bone), computational behavior science aims to quantify behavioral dynamics in a concrete and objective way.
This collaboration will be the first large-scale effort of computer and behavioral scientists to jointly address diagnosing and intervening early in the lives of those with Autism spectrum disorders (ASD).
ASD, which refers to a group of complex neurodevelopmental disorders that cause social, communication and behavioral impairments in children and adults, currently affects 1 in 110 children in the United States. In addition, ASD has a substantial economic impact on society, with the lifetime cost of care for those with ASD exceeding $3 million per person.
Over the past several years, Media Lab researchers have developed a number of technologies to track and measure emotional states, and, working with the ASD community, refined them into specialized tools. These technologies include novel wearable physiological sensors and corresponding software that can be used to measure variables such as heart rate and skin conductivity — indicators of internal stress and arousal. These technologies provide new, more precise ways to understand behavior, and will help individuals with ASD communicate cognitive and emotional states, as well as help others — scientists, therapists, teachers, caregivers — to understand those states.
Along with colleagues at the other institutions included in the grant — Georgia Tech, Carnegie Mellon, the University of Southern California, Boston University and the University of Illinois at Urbana-Champaign — the Media Lab team will apply its expertise to the building of test beds and methodologies for capturing behavior data accurately and noninvasively, resulting in a more objective, data-driven approach to behavioral assessment. This multi-year, multi-step program will include research in computer vision, audio and speech analysis, and physiological recording with wireless sensors.
This NSF-funded collaborative project aims to combine computer science and behavioral science to create an entirely new field of inquiry: computational behavior science. Just as medical imaging such as MRIs or X-rays have allowed doctors to identify and treat previously unobservable problems (a brain tumor, aneurysm, a broken bone), computational behavior science aims to quantify behavioral dynamics in a concrete and objective way.
