Published on in Vol 6, No 9 (2022): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/33606, first published .
Personalized Energy Expenditure Estimation: Visual Sensing Approach With Deep Learning

Personalized Energy Expenditure Estimation: Visual Sensing Approach With Deep Learning

Personalized Energy Expenditure Estimation: Visual Sensing Approach With Deep Learning

Journals

  1. Prokopakis I, Gialelis J, Protopsaltis G. Real Time Estimation of Energy Expenditure during Physical Activity Using Ensemble Methods. Procedia Computer Science 2024;241:582 View
  2. Zhou N, Mu F, Zhang Y, Zang D, Zhu W, Wang X, Wang W, Li H, Wang J, Zhang X, Li C, Li Y, He M, Zhang W, Liu Q, Lu B, Han S, Li Y, Zhang Y, Xu L, Qian Y, Ding L, Xu C, Li H, Feng S, Yang L, Wei Y, Li B, RAVI R. How electronic health literacy influences physical activity behaviour among university students: A moderated mediation model. PLOS One 2025;20(8):e0330637 View
  3. Zhao Z, Chai W, Hao S, Hu W, Wang G, Cao S, Song M, Hwang J, Wang G. A Survey of Deep Learning in Sports Applications: Perception, Comprehension, and Decision. IEEE Transactions on Visualization and Computer Graphics 2025;31(10):9368 View
  4. Jin L, Zhang S, Shi M, Yu L, Wang M, Song M, Wen X. Vision-based multimodal energy expenditure estimation for aerobic exercise in adults. Frontiers in Physiology 2025;16 View

Books/Policy Documents

  1. Zhang S, Jin L, Wang Y, Wang X, Wen X, Feng Z, Song M. Computer Vision – ECCV 2024. View

Conference Proceedings

  1. Kasturi G, Shrestha P, Strath S, Kate R. 2024 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI). Estimating Physical Activity Energy Expenditure from Video View