Published on in Vol 5, No 12 (2017): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9177, first published .
Addendum of: Fall Detection in Individuals With Lower Limb Amputations Using Mobile Phones: Machine Learning Enhances Robustness for Real-World Applications

Addendum of: Fall Detection in Individuals With Lower Limb Amputations Using Mobile Phones: Machine Learning Enhances Robustness for Real-World Applications

Addendum of: Fall Detection in Individuals With Lower Limb Amputations Using Mobile Phones: Machine Learning Enhances Robustness for Real-World Applications

Journals

  1. Yao L, Yang W, Huang W. A data augmentation method for human action recognition using dense joint motion images. Applied Soft Computing 2020;97:106713 View
  2. Zelman S, Dow M, Tabashum T, Xiao T, Albert M. Accelerometer-Based Automated Counting of Ten Exercises without Exercise-Specific Training or Tuning. Journal of Healthcare Engineering 2020;2020:1 View
  3. Maldonado-Contreras J, Bhakta K, Camargo J, Kunapuli P, Young A. User- and Speed-Independent Slope Estimation for Lower-Extremity Wearable Robots. Annals of Biomedical Engineering 2024;52(3):487 View