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Attribution 4.0 International
Affective Computing group, MIT Media Lab
Epilepsy is the fourth most common neurological disease globally. In the U.S., 1.2% of the national population reported active epilepsy in …
Teddy is a cutting edge data collection platform available for both Android and iOS that lets you collect data from study participants in a…
Current methods to assess depression and select appropriate treatments have many limitations and need improvement. Diagnosis is usually bas…
Acu.ation is an intervention that aims to mediate the urge to smoke by pairing a wearable device that delivers transcutaneous electric acup…
In this project, we are exploring ways to design technology that promotes healing and care for young people who have experienced foster car…
Social deduction or deception games are games in which a player or team of players actively deceives other players who are trying to discov…
Check out our publications in PNAS, a workshop at IJCAI, and pre-print on arXiv. Check out a video from the Election Misinfo…
Different approaches and models have been used to detect driver’s stress and affective states, using physiology, facial expression, and sel…
Emotional arousal influences focus, attention, and decision-making, which are critical when driving. To help promote an optimal arousal lev…
The Affective Computing group is collaborating with Weill Cornell Medicine to build empathetic behavior in physicians working with opioid u…
We introduce–aSpire–a clippable, mobile pneumatic-haptic device designed to help users regulate their breathing rate via subtle tactile fee…
There is a consensus that the hospital experience is stressful for children and leads to anxiety and fear. Long term effects of stres…
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This project is supported by the Abdul Latif Jameel Clinic for Machine Learning in Health (J-Clinic), the National Institutes of Healt…
Before automobiles were invented and widely adopted, animals like horses were the most common mode of transportation. While this change bro…
Try Affective Network!Emotional contagion in online social networks has been of great interest over the past years. Previous studies have m…
Communication skills are critical for all. We design and develop systems to help people with communication issues, e.g., more empathi…
The Places dataset (website) is designed following principles of human visual cognition. Our goal is to build a core of visual kn…
We introduce SkinBot: a lightweight robot that moves over the skin's surface with a two-legged suction-based locomotion mechanism and captu…
A wearable olfactory display that monitors cardio-respiratory information with the aspiration to support mental wellbeing.BioEssence is a w…
The project aims to investigate the relationships between emotion, wellbeing, skin, and skincare cosmetics. In our first study, we mea…
In this project we explore how to recognize and localize affect in images.
This project aims to improve the prediction accuracy of wellbeing (stress, mood, and health levels) using temporal machine learning models.…
The goal of this project is providing machines with the ability of understanding what a person is experiencing from her frame of reference,…
The relationship between breathing and self-reported stress is bidirectional. Respiration pattern is an indicator of stress, but it can als…
Depression correlated with anxiety is one of the key factors leading to suicidal behavior, and is among the leading causes of death worldwi…
Conversations between two individuals—whether between doctor and patient, mental health therapist and client, or between two people romanti…
The SNAPSHOT study seeks to measure Sleep, Networks, Affect, Performance, Stress, and Health using Objective Techniques. It is an NIH-funde…
New generative AI technologies (such as the Generative Adversarial Network, or GAN) can allow us to imagine new species. Hidden within the …