Connecting Emotions, Brain, and Behavior with Wearables — Dr. Rosalind Picard

Connecting Emotions, Brain, and Behavior with Wearables — Dr. Rosalind Picard

NIMH Director’s Innovation Speaker Series
March 3, 2016

Dr. Rosalind Picard is Director of Affective Computing Research at the MIT Media Lab, Faculty Chair of MIT’s Mind+Hand+Heart initiative for mental health, and Chief Scientist of Empatica. Picard is best known for writing the book Affective Computing, which helped give rise to the field by that name. She and her team have invented many ways in which technology can objectively measure and communicate human emotion, including new tools for facial and physiological analysis. Her inventions have applications in autism, epilepsy, depression, PTSD, sleep, stress, dementia, autonomic nervous system disorders, human and machine learning, health behavior change, and human-computer interaction. In 2005 she was named a Fellow of the IEEE for contributions to image and video analysis and affective computing. CNN named her one of seven “Tech SuperHeros to Watch in 2015”. Her group’s technologies have been spun out into companies such as Affectiva, Empatica, Cardiio, and Itskoko, where they are used worldwide by researchers and patients.

In this talk, Dr. Picard provides an overview of recent work her lab has conducted (also with partners at Harvard Medical School) measuring emotion and physiology in daily life for improving mental health. This work includes long-term measurement of sympathetic nervous system changes captured from a wristband in daily life wear. While the initial focus was on capturing and measuring autonomic stress, and helping people with autism to be better understood, the team soon encountered a number of surprises of what could be learned from sensing on the surface of the skin. Picard describes interesting patterns found in non-REM sleep that may relate to memory formation, in seizures and brain-wave suppression, and in anxiety and depression, which are revealing marvelous ways in which wearables may provide important unobtrusive biomarkers for activity deep in our brain.