Published on in Vol 9, No 8 (2021): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25415, first published .
Assessing Electrocardiogram and Respiratory Signal Quality of a Wearable Device (SensEcho): Semisupervised Machine Learning-Based Validation Study

Assessing Electrocardiogram and Respiratory Signal Quality of a Wearable Device (SensEcho): Semisupervised Machine Learning-Based Validation Study

Assessing Electrocardiogram and Respiratory Signal Quality of a Wearable Device (SensEcho): Semisupervised Machine Learning-Based Validation Study

Haoran Xu   1 , MSc ;   Wei Yan   2 , MD ;   Ke Lan   3 , MSc ;   Chenbin Ma   4 , BSc ;   Di Wu   3 , MSc ;   Anshuo Wu   5 , BSc ;   Zhicheng Yang   6 , PhD ;   Jiachen Wang   1 , BSc ;   Yaning Zang   7 , BM ;   Muyang Yan   2 , PhD, MD ;   Zhengbo Zhang   8 , PhD

1 Medical School of Chinese PLA, Beijing, China

2 Department of Hyperbaric Oxygen, The First Medical Center, Chinese PLA General Hospital, Beijing, China

3 Beijing SensEcho Science & Technology Co., Ltd., Beijing, China

4 School of Biological Science and Medical Engineering, Beihang University, Beijing, China

5 University of Washington, Seattle, WA, United States

6 PAII Inc., Palo Alto, CA, United States

7 Department of Kinesiology, Shanghai University of Sport, Shanghai, China

8 Centre for Artificial Intelligence in Medicine, Medical Innovation Research Department, Chinese PLA General Hospital, Beijing, China

Corresponding Author:

  • Zhengbo Zhang, PhD
  • Centre for Artificial Intelligence in Medicine
  • Medical Innovation Research Department
  • Chinese PLA General Hospital
  • 28 Fuxing Road, Haidian District, Beijing
  • Beijing, 100853
  • China
  • Phone: 86 13693321644
  • Email: zhengbozhang301@gmail.com