| Benchmark datasets for bilateral lower-limb neuromechanical signals from wearable sensors during unassisted locomotion in able-bodied individuals B Hu, E Rouse, L Hargrove Frontiers in Robotics and AI 5, 14, 2018 | 82 | 2018 |
| Fusion of bilateral lower-limb neuromechanical signals improves prediction of locomotor activities B Hu, E Rouse, L Hargrove Frontiers in Robotics and AI 5, 78, 2018 | 75 | 2018 |
| Subject-and environment-based sensor variability for wearable lower-limb assistive devices NE Krausz, BH Hu, LJ Hargrove Sensors 19 (22), 4887, 2019 | 32 | 2019 |
| Deep generative models with data augmentation to learn robust representations of movement intention for powered leg prostheses B Hu, AM Simon, L Hargrove IEEE Transactions on Medical Robotics and Bionics 1 (4), 267-278, 2019 | 28 | 2019 |
| A novel method for bilateral gait segmentation using a single thigh-mounted depth sensor and IMU BH Hu, NE Krausz, LJ Hargrove 2018 7th IEEE International Conference on Biomedical Robotics and …, 2018 | 26 | 2018 |
| Using bilateral lower limb kinematic and myoelectric signals to predict locomotor activities: A pilot study BH Hu, EJ Rouse, LJ Hargrove 2017 8th International IEEE/EMBS Conference on Neural Engineering (NER), 98-101, 2017 | 10 | 2017 |
| Corrigendum: Benchmark Datasets for Bilateral Lower-Limb Neuromechanical Signals from Wearable Sensors during Unassisted Locomotion in Able-Bodied Individuals B Hu, E Rouse, L Hargrove Frontiers in Robotics and AI 5, 127, 2018 | 1 | 2018 |
| Applying Sensor Fusion and Deep Learning to Discover Robust Representations of Movement Intention for Powered Leg Prostheses BH Hu Northwestern University, 2019 | | 2019 |
Levi HargroveShirley Ryan AbilitylabVerified email at northwestern.edu
