emotIOn
2018
Creating machines with empathy…
"Emotional programs" promise to promote Human - Computer Interactions (HCIs) to a new level in which humans and technology can start to function as a well orchestrated and natural symbiosis. emotIOn is an exploratory project that seeks to understand human emotions using machine learning to predict a user’s emotional state depending on the environmental state in which the user is in. A framework describing different emotional sources or weights was developed. These emotional weights represent the main variables that have a big impact on a human’s emotions. The models explored by emotIOn are models that are based only on the “Environmental State Weights”.
Collecting Data
A training data set was built by mounting an MIT terMITe (wireless environmental sensor that captures data to help us better understand our environments and human behavior) to the user and capturing values for X Acceleration, Y Acceleration, Z Acceleration, Temperature, Light and Humidity, those values were concatenated to the values obtained from the analog emotion interface which are adjusted by the user to reflect his/her emotional state.
Anger
Joy
Sadness
Disgust
Environmental State Monitoring (MIT terMITe)
Emotional State Adjustment
Collecting Environmental & Emotional Data
Building & Training NN Model
Model was created to be used with individual users.
Each individual user model is trained with more than half a million data points.
Analog emotion interface & terMITe mount design and construction
Wearable Case Design
3D Printing Y Modulator & Wearable
Soldering and construction of Y Modulator
Y Modulator Final Design
Model Results
The trained model is capable of predicting completely new data points with an accuracy of up to 87%.
Humidity vs Z Acceleration vs Emotional State
Light vs Temperature vs Emotional State
Light vs X Acceleration vs Emotional State
Credits and Acknowledgements
Carson Smuts (terMITe development) | Jason Nawyn (Project’s Vision) | Leonardo Garrido (Machine Intelligence Advisor)