Machines · 2022 · 17 citations · 20 references
MedicineRehabilitation MedicineRobotics EngineeringRehabilitationRehabilitation EngineeringStroke RehabilitationLower Extremity RehabilitationLower Limb RehabilitationRehabilitation BiomechanicsRehabilitation RoboticsRobotic RehabilitationUpper Limb RehabilitationHybrid Robot ArchitecturesLower Limb Rehabilitation RoboticsMuscle ActivationRehabilitation RobotsRehabilitation TrainingScrew TheorySurface ElectromyographyTrajectory Planning
Conventional lower-limb rehabilitation robots cannot provide in-time rehabilitation training for stroke patients in the acute stage due to their large size and mass as well as their complex wearing process. Aiming to solve the problems, first, a novel hybrid end-traction lower-limb rehabilitation robot (HE-LRR) was designed as the lower-limb rehabilitation requirement of patients in the acute stage, in this paper. The usage of (2-UPS + U)&(R + RPS)&(2-RR) hybrid mechanism and a mirror motion actuator had the advantages of compact structure, large working space and short wearing time to the HE-LRR. Then, the mobility of the HE-LRR was calculated and the motion property was analyzed based on screw theory. Meanwhile, the trajectory planning of the HE-LRR was carried out based on MOTOmed® motion training. Finally, the motion capture and surface electromyography (sEMG) signal acquisition experiments in the MOTOmed motion training were performed. The foot trajectory experimental effect and the lower-limb muscle groups activation rules were studied ulteriorly. The experimental results showed that the HE-LRR achieved good kinematic accuracy and lower limb muscle groups training effect, illustrating that the HE-LRR possessed good application prospects for the lower-limb rehabilitation of patients in the acute stage. This research could also provide a theoretical basis for improving the standardization and compliance of lower-limb robot rehabilitation training.
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Huei‐Ching Yang, Chia‐Ling Lee, Miao‐Ju Hsu et al. · The Kaohsiung Journal of Medical Sciences · 2013 · 83 citations · Full text
Anna Lára Ármannsdóttir, Philipp Beckerle, Juan C. Moreno et al. · Human Factors The Journal of the Human Factors and Ergonomics Society · 2020 · 72 citations · Full text