Emotion-recognition using smart watch accelerometer data

preliminary findings

Juan C. Quiroz, Min Hooi Yong, Elena Geangu

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

12 Citations (Scopus)

Abstract

This study investigates the use of accelerometer data from a smart watch to infer an individual's emotional state. We present our preliminary findings on a user study with 50 participants. Participants were primed either with audio-visual (movie clips) or audio (classical music) to elicit emotional responses. Participants then walked while wearing a smart watch on one wrist and a heart rate strap on their chest. Our hypothesis is that the accelerometer signal will exhibit different patterns for participants in response to different emotion priming. We divided the accelerometer data using sliding windows, extracted features from each window, and used the features to train supervised machine learning algorithms to infer an individual's emotion from their walking pattern. Our discussion includes a description of the methodology, data collected, and early results.

Original languageEnglish
Title of host publicationUbiComp/ISWC 2017
Subtitle of host publicationAdjunct Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers
Place of PublicationNew York, New York
PublisherAssociation for Computing Machinery, Inc
Pages805-812
Number of pages8
ISBN (Electronic)9781450351904
DOIs
Publication statusPublished - 11 Sep 2017
Externally publishedYes
Event2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers, UbiComp/ISWC 2017 - Maui, United States
Duration: 11 Sep 201715 Sep 2017

Conference

Conference2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and ACM International Symposium on Wearable Computers, UbiComp/ISWC 2017
CountryUnited States
CityMaui
Period11/09/1715/09/17

Keywords

  • Accelerometer
  • Emotion-recognition
  • Supervised learning

Fingerprint Dive into the research topics of 'Emotion-recognition using smart watch accelerometer data: preliminary findings'. Together they form a unique fingerprint.

Cite this