Published on in Vol 7, No 2 (2019): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/11201, first published .
Applying Multivariate Segmentation Methods to Human Activity Recognition From Wearable Sensors’ Data

Applying Multivariate Segmentation Methods to Human Activity Recognition From Wearable Sensors’ Data

Applying Multivariate Segmentation Methods to Human Activity Recognition From Wearable Sensors’ Data

Kenan Li   1 , PhD ;   Rima Habre   1 , PhD ;   Huiyu Deng   1 , MSc ;   Robert Urman   1 , PhD ;   John Morrison   1 , MSc ;   Frank D Gilliland   1 , PhD ;   José Luis Ambite   2 , PhD ;   Dimitris Stripelis   2 , MSc ;   Yao-Yi Chiang   3 , PhD ;   Yijun Lin   3 , MSc ;   Alex AT Bui   4 , PhD ;   Christine King   5 , PhD ;   Anahita Hosseini   6 , MSc ;   Eleanne Van Vliet   1 , PhD ;   Majid Sarrafzadeh   6 , PhD ;   Sandrah P Eckel   1 , PhD

1 Department of Preventive Medicine, Keck School of Medicine of University of Southern California, Los Angeles, CA, United States

2 Information Sciences Institute, University of Southern California, Los Angeles, CA, United States

3 Spatial Sciences Institute, University of Southern California, Los Angeles, CA, United States

4 Department of Radiological Sciences, University of California Los Angeles, Los Angeles, CA, United States

5 Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States

6 Department of Computer Science, University of California Los Angeles, Los Angeles, CA, United States

Corresponding Author:

  • Kenan Li, PhD
  • Department of Preventive Medicine
  • Keck School of Medicine of University of Southern California
  • Soto Building Room 202-09
  • 2001 North Soto Street
  • Los Angeles, CA, 90089
  • United States
  • Phone: 1 2256102559
  • Email: kenanl@usc.edu