Title Information
Title
Using the Remotion Plus Platform to Predict Emotion and Attention State from Smartphone Behavioral Data in Remote Usability Tests
Type of Resource
text
Name: Personal
Name Part
Silva - Sassaman, Dinithi
Role
Role Term: Text
creator
Name: Personal
Name Part
Huang, Jeff
Role
Role Term: Text
Advisor
Name: Personal
Name Part
Crisco, Joseph
Role
Role Term: Text
Reader
Name: Personal
Name Part
Gonsher, Ian
Role
Role Term: Text
Reader
Name: Corporate
Name Part
Brown University. Biology and Medicine: Biomedical Engineering
Role
Role Term: Text
sponsor
Origin Information
Copyright Date
2020
Physical Description
Extent
iv, 53 p.
digitalOrigin
born digital
Note: thesis
Thesis (Sc. M.)--Brown University, 2020
Genre (aat)
theses
Abstract
When designing a smartphone app, it is critical to be able to determine the emotion and attention state of the users as they interact with your interface. Remotion Plus is a platform that gives analysts the ability to record, annotate, and analyze remote user data through a computer program with an intuitive graphical interface. It records microphone audio, screen capture video, device orientation, and rear finger pressure data remotely from a mobile device user, and it is able to audibly and visually play back user sessions. Remotion Plus is also able to automatically predict user emotion and attention state, including in real time, with a machine learning model that consistently reaches higher than 80% accuracy. This is considerably higher than humans given the same orientation and pressure data as their predictions only reached about 20%-40% accuracy.
Subject
Topic
emotions
Subject (fast) (authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/00820788")
Topic
Attention
Subject (fast) (authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/01743652")
Topic
Smartphones
Subject
Topic
remote usability
Subject
Topic
pressure pad
Subject (fast) (authorityURI="http://id.worldcat.org/fast", valueURI="http://id.worldcat.org/fast/01085499")
Topic
Quaternions
Language
Language Term (ISO639-2B)
English
Record Information
Record Content Source (marcorg)
RPB
Record Creation Date (encoding="iso8601")
20210607