no code implementations • 10 Jul 2023 • Albara Ah Ramli, Xin Liu, Kelly Berndt, Chen-Nee Chuah, Erica Goude, Lynea B. Kaethler, Amanda Lopez, Alina Nicorici, Corey Owens, David Rodriguez, Jane Wang, Daniel Aranki, Craig M. McDonald, Erik K. Henricson
The approach involves a combination of clinical observation, machine-learning-based step detection, and regression-based stride length prediction.
no code implementations • 12 May 2021 • Albara Ah Ramli, Xin Liu, Kelly Berndt, Erica Goude, Jiahui Hou, Lynea B. Kaethler, Rex Liu, Amanda Lopez, Alina Nicorici, Corey Owens, David Rodriguez, Jane Wang, Huanle Zhang, Daniel Aranki, Craig M. McDonald, Erik K. Henricson
We extracted temporospatial gait clinical features (CFs) and applied multiple machine learning (ML) approaches to differentiate between DMD and TD children using extracted temporospatial gait CFs and raw data.
no code implementations • 28 Apr 2015 • Daniel Aranki, Ruzena Bajcsy
We show cases where it is possible to achieve perfect privacy regardless of the adversary's auxiliary knowledge while preserving full utility of the information to the intended recipient and provide sufficient conditions for such cases.