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EDA Explorer

http://eda-explorer.media.mit.edu

Oct. 5, 2017

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An online tool for visualization and analysis of Electrodermal Activity data. The site can detect noise within the signal with 95% accuracy, detect Electrodermal Responses (EDRs), visualize the results, compute features which users can download, and help researchers label their own signal data. Researchers an also use our open sourced scripts to compute features themselves.

Contact: Natasha Jaques or Sara Taylor

Website: EDA Explorer

Multimodal Autoencoder: A Deep Learning Approach to Filling In Missing Sensor Data and Enabling Better Mood Prediction

Jaques, N., Taylor, S., Sano, A., and Picard, R. International Conference on Affective Computing and Intelligent Interaction (ACII), San Antonio, Texas, October 2017

Article Research

AI Songsmith Cranks Out Surprisingly Catchy Tunes

Google’s songwriting program learns by combining statistical learning and explicit rules—the same approach may make it easier for engineers…

Post Research

Natasha Jaques wins AAAC Outstanding PhD Dissertation Award 2021

Natasha Jaques, an alum of the Affective Computing group, has won this year's award for her thesis: "Social and Affective Machine Learning"

Event Events

Natasha Jaques Dissertation Defense

Towards Social and Affective Artificial IntelligenceSocial learning is a crucial component of human intelligence, allowing us to rapidly ad…