Published on in Vol 23, No 10 (2021): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18403, first published .
Circadian Rhythm Analysis Using Wearable Device Data: Novel Penalized Machine Learning Approach

Circadian Rhythm Analysis Using Wearable Device Data: Novel Penalized Machine Learning Approach

Circadian Rhythm Analysis Using Wearable Device Data: Novel Penalized Machine Learning Approach

Xinyue Li   1, 2 , PhD ;   Michael Kane   3 , PhD ;   Yunting Zhang   2, 4 , PhD ;   Wanqi Sun   5 , MD ;   Yuanjin Song   5 , MD ;   Shumei Dong   5 , MSc ;   Qingmin Lin   5 , PhD ;   Qi Zhu   5 , MSc ;   Fan Jiang   4, 5 , MD, PhD ;   Hongyu Zhao   3, 6 , PhD

1 School of Data Science, City University of Hong Kong, Hong Kong, China (Hong Kong)

2 Child Health Advocacy Institute, Shanghai Children’s Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China

3 Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States

4 School of Public Health, Shanghai Jiao Tong University, Shanghai, China

5 Department of Developmental and Behavioral Pediatrics, Shanghai Children’s Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China

6 Yale Joint Center for Biostatistics, Shanghai Jiao Tong University, Shanghai, China

Corresponding Author:

  • Hongyu Zhao, PhD
  • Department of Biostatistics
  • Yale School of Public Health
  • 300 George Street
  • Suite 503
  • New Haven, CT, 06511
  • United States
  • Phone: 1 203 785 3613
  • Fax: 1 203 785 6912
  • Email: hongyu.zhao@yale.edu