3D motion capture system for assessing patient motion during Fugl‐Meyer stroke rehabilitation testing N Eichler, H Hel‐Or, I Shimshoni, D Itah, B Gross, S Raz IET Computer Vision 12 (7), 963-975, 2018 | 31 | 2018 |
Automatic and efficient fall risk assessment based on machine learning N Eichler, S Raz, A Toledano-Shubi, D Livne, I Shimshoni, H Hel-Or Sensors 22 (4), 1557, 2022 | 24 | 2022 |
Non-invasive motion analysis for stroke rehabilitation using off the shelf 3d sensors N Eichler, H Hel-Or, I Shmishoni, D Itah, B Gross, S Raz 2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018 | 21 | 2018 |
Predicting fall probability based on a validated balance scale A Masalha, N Eichler, S Raz, A Toledano-Shubi, D Niv, I Shimshoni, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 15 | 2020 |
Spatio-temporal calibration of multiple kinect cameras using 3d human pose N Eichler, H Hel-Or, I Shimshoni Sensors 22 (22), 8900, 2022 | 8 | 2022 |
Motion tracking with multiple 3D cameras I Shimshoni, H Hel-Or, NF Eichler, RAZ Shmuel US Patent 11,354,938, 2022 | 3 | 2022 |
A Novel 3D Motion Capture System using Multiple Consumer Depth Sensors N Eichler University of Haifa, 2014 | 1 | 2014 |
Automatic and efficient fall prediction assessment based on machine learning and a tracking system H Hel-Or, I Shimshoni, N Eichler, RAZ Shmuel US Patent App. 18/216,297, 2024 | | 2024 |
Systems and methods for diagnosing a stroke condition N Eichler, RAZ Shmuel, R Sivan-Hoffmann, A Frid, O Dror US Patent 11,699,529, 2023 | | 2023 |
Motion tracking with multiple 3d cameras I Shimshoni, H Hel-Or, NF Eichler, RAZ Shmuel US Patent App. 17/701,995, 2022 | | 2022 |
A Novel 3d Using Multiple Consumer Depth Sensors N Eichler PQDT-Global, 2017 | | 2017 |
Improving 3D Body Skeleton using Multiple Kinect Sensors N Eichler | | 2015 |