• E. A. Kamienski, P. Bonato and H. Harry Asada, “Time-Critical Fall Prediction Based on Lipschitz Data Analysis and Design of a Reconfigurable Walker for Preventing Fall Injuries,” in IEEE Access, doi: 10.1109/ACCESS.2023.3347263.

  • E. Kamienski and H.H. Asada, “Assessing Dataset Learnability Using Lipschitz Quotient Analysis Applied to Fall Prediction”. ICRA, 2024. Under Review.

  • I. Nozawa, E. Kamienski, C. O’Neill, and H. Asada, “A Monte Carlo Approach to Koopman Direct Encoding and Its Application to the Learning of Neural-Network Observables”, IEEE Robotics and Automation Letters (RA-L), 2023.

  • J. Bell, E. Kamienski, S. Teshigawara, H. Itagaki and H. H. Asada, “Gear Ratio Optimization of a Multifunctional Walker Robot Using Dual-Motor Actuation,” 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Prague, Czech Republic, 2021, pp. 9339-9346, doi: 10.1109/IROS51168.2021.9636482.

  • E. Kamienski and H. H. Asada, “Pants with Embedded Harness for Daily Use”. US Patent 63/342601, Filed May 16, 2022. (Submitted)

  • E. Kamienski and H. H. Asada, “A Reconfigurable Walker for Predicting and Preventing Fall of Patients”. US Patent 63/252,367, May 10, 2021. (Provisional)