Autonomous and Portable Soft Exosuit for Hip Extension Assistance with Online Walking and Running Detection Algorithm
Autor: | Giuk Lee, Asa Eckert-Erdheim, David Perry, Roman Heimgartner, Dabin Kim Choe, Nikos Karavas, Jinsoo Kim, Conor J. Walsh, Patrick Murphy, Danielle Louise Ryan, Ignacio Galiana |
---|---|
Rok vydání: | 2018 |
Předmět: |
030506 rehabilitation
Computer science Powered exoskeleton 02 engineering and technology Thigh 021001 nanoscience & nanotechnology Exoskeleton 03 medical and health sciences Acceleration medicine.anatomical_structure Wearable robot Hip extension Inertial measurement unit medicine Treadmill 0210 nano-technology 0305 other medical science Algorithm |
Zdroj: | ICRA |
Popis: | We present an autonomous and portable hip-only soft exosuit, for augmenting human walking and running that assists hip extension by delivering peak forces of 300N to the user. Different fixed assistance profiles for walking and running were applied based on an online classification algorithm. The approach is based on the biomechanical understanding that the center of mass potential energy fluctuations during walking and running are out of phase. Specifically, we monitor the vertical acceleration with an abdomen-mounted IMU at the moment of maximum hip extension. Validation is demonstrated with six subjects on the treadmill and with eight subjects outdoors. Our results demonstrated a 99.99% accuracy on average over the fourteen participants for various speeds (0.5 - 4m/s), slopes (−10 −20%), treadmill and overground terrain, loaded (13.6 kg) and unloaded, Exo On and Exo Off conditions, and different shoe types. Results from an evaluation outdoors overground on the energetics of eight subjects demonstrated a significant reduction for running when comparing Exo On to No Exo (3.9%) and for walking and running when comparing Exo On to Exo Off (12.2% and 8.2% respectively). This study represents the first demonstration of an autonomous wearable robot reducing the energy cost of running. Significant variation in response across subjects was observed, highlighting further improvements may be possible via assistance profile individualization with human-in-the-Ioop optimization. |
Databáze: | OpenAIRE |
Externí odkaz: |