Name
Abstract | ||
|---|---|---|
In this paper, we deal with Markov Jump Linear Systems-based filtering applied to robotic rehabilitation. The angular positions of an impedance-controlled exoskeleton, designed to help stroke and spinal cord injured patients during walking rehabilitation, are estimated. Standard position estimate approaches adopt Kalman filters (KF) to improve the performance of inertial measurement units (IMUs) based on individual link configurations. Consequently, for a multi-body system, like a lower limb exoskeleton, the inertial measurements of one link (e.g., the shank) are not taken into account in other link position estimation (e.g., the foot). In this paper, we propose a collective modeling of all inertial sensors attached to the exoskeleton, combining them in a Markovian estimation model in order to get the best information from each sensor. In order to demonstrate the effectiveness of our approach, simulation results regarding a set of human footsteps, with four IMUs and three encoders attached to the lower limb exoskeleton, are presented. A comparative study between the Markovian estimation system and the standard one is performed considering a wide range of parametric uncertainties. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.3390/s140101835 | Sensors |
Keywords | Field | DocType |
medical robotics,inertial sensors,uncertain systems,inertial systems,measurement quality,parametric uncertainties,walking rehabilitation,kalman filters,stochastic systems,kalman filtering,human footsteps,markovian estimation model,markov jump linear systems-based position estimation,angular positions,individual link configurations,markov processes,kf,patient rehabilitation,biomedical,lower limbs exoskeletons,linear systems,encoders,multibody system,robotic rehabilitation,spinal cord injured patients,stroke patients,position control,imu,impedance-controlled exoskeleton,link position estimation,exoskeleton,markov chains,kalman filter,robotics,stroke,algorithms | Markov process,Simulation,Control theory,Markov chain,Filter (signal processing),Kalman filter,Parametric statistics,Artificial intelligence,Inertial measurement unit,Exoskeleton,Engineering,Robotics | Journal |
Volume | Issue | ISSN |
14 | 1 | 1424-8220 |
Citations | PageRank | References |
4 | 0.64 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Samuel L. Nogueira | 1 | 6 | 1.77 |
| Adriano a. g. Siqueira | 2 | 41 | 15.59 |
| Roberto s. Inoue | 3 | 5 | 2.01 |
| Marco h. Terra | 4 | 77 | 18.31 |