Article

"Hybrid-PLEMO", Rehabilitation system for upper limbs with Active/Passive Force Feedback mode

ABSTRACT Several rehabilitation robots for upper limbs have been proposed so far, and clinical effectiveness was reported in several studies for the aged people or patients with stroke. However most of them have only 2-DOF for its active motion. It is important for designing a rehabilitation system which trains in the 3-DOF space because the upper limbs of humans works in 3-DOF space even expect for the wrist. We developed the quasi 3-DOF rehabilitation system which has 2-DOF force-feedback function in working plane but its working plane can be adjusted the inclination. And we named it Hybrid-PLEMO for it can be switched between active type and passive type. Hybrid-PLEMO is a compact, low-cost rehabilitation system for upper limbs with high safety by using ER brakes or ER actuators. Additionally, in Hybrid-PLEMO, we take direct-drive linkage mechanism by adding sub links. In this paper, we describe the mechanism and haptic control of Hybrid-PLEMO.

Download full-text

Full-text

Available from: Takehito Kikuchi, Sep 18, 2014
0 Followers
 · 
122 Views
  • Source
    • "part of post-stroke rehabilitative care. Several rehabilitation robots for the upper extremity have been proposed, including MIT-Manus [2], ARM Guide [3], MIME [4], and the more recently developed PLEMO [5], ARMin [6], and MEMOS [7]. Clinical effectiveness greater than sham robot-therapy or a matched amount of traditional therapy has been reported by several studies [4], [8]–[10], including the recent Veterans Administration multicenter, randomized, controlled clinical trials reported in the New England Journal of Medicine [11]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Following two decades of design and clinical research on robot-mediated therapy for the shoulder and elbow, therapeutic robotic devices for other joints are being proposed: several research groups including ours have designed robots for the wrist, either to be used as stand-alone devices or in conjunction with shoulder and elbow devices. However, in contrast with robots for the shoulder and elbow which were able to take advantage of descriptive kinematic models developed in neuroscience for the past 30 years, design of wrist robots controllers cannot rely on similar prior-art: wrist movement kinematics has been largely unexplored. This study aimed at examining speed profiles of fast, visuallyevoked, visually-guided, target-directed human wrist pointing movements. Thirteen hundred ninety-eight (1398) trials were recorded from seven unimpaired subjects who performed centerout flexion/extension and abduction/adduction wrist movements and fitted with nineteen models previously proposed for describing reaching speed profiles. A nonlinear, least-squares optimization procedure extracted parameters sets that minimized error between experimental and reconstructed data. Models performances were compared based on their ability to reconstruct experimental data. Results suggest that the support-bounded lognormal is the best model for speed profiles of fast, wrist pointing movements. Applications include design of control algorithms for therapeutic wrist robots and quantitative metrics of motor recovery.
    IEEE transactions on neural systems and rehabilitation engineering: a publication of the IEEE Engineering in Medicine and Biology Society 12/2012; 21(5). DOI:10.1109/TNSRE.2012.2231943 · 2.82 Impact Factor
  • Source
    • "Several rehabilitation robots for the upper extremity have been proposed. Examples include MIT-Manus [5], ARM Guide [12], MIME [13] and the more recently developed PLEMO [14], ARMin [15], and MEMOS [16]. Clinical effectiveness greater than sham robot-therapy or a matched amount of traditional occupational therapy was reported in several studies [4], [13], [17], [18], including the recent Veterans Administration (VA) multicenter, randomized, controlled clinical trial reported in the New England Journal of Medicine, which enrolled 127 patients six months or more after stroke and showed that robot-mediated therapy improved outcomes over 36 weeks as compared with usual care [19]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Both the American Heart Association and the VA/DoD endorse upper-extremity robot-mediated rehabilitation therapy for stroke care. However, we do not know yet how to optimize therapy for a particular patient's needs. Here, we explore whether we must train patients for each functional task that they must perform during their activities of daily living or alternatively capacitate patients to perform a class of tasks and have therapists assist them later in translating the observed gains into activities of daily living. The former implies that motor adaptation is a better model for motor recovery. The latter implies that motor learning (which allows for generalization) is a better model for motor recovery. We quantified trained and untrained movements performed by 158 recovering stroke patients via 13 metrics, including movement smoothness and submovements. Improvements were observed both in trained and untrained movements suggesting that generalization occurred. Our findings suggest that, as motor recovery progresses, an internal representation of the task is rebuilt by the brain in a process that better resembles motor learning than motor adaptation. Our findings highlight possible improvements for therapeutic algorithms design, suggesting sparse-activity-set training should suffice over exhaustive sets of task specific training.
    IEEE transactions on neural systems and rehabilitation engineering: a publication of the IEEE Engineering in Medicine and Biology Society 12/2011; 20(1):48-57. DOI:10.1109/TNSRE.2011.2175008 · 2.82 Impact Factor
  • Source
    • "Several rehabilitation robots for the upper extremity have been proposed. Examples include MIT-Manus [5], ARM Guide [12], MIME [13] and the more recently developed PLEMO [14], ARMin [15], and MEMOS [16]. Clinical effectiveness greater than sham robot-therapy or a matched amount of traditional occupational therapy was reported in several studies [4], [13], [17], [18], including the recent Veterans Administration (VA) multicenter, randomized, controlled clinical trial reported in the New England Journal of Medicine, which enrolled 127 patients six months or more after stroke and showed that robot-mediated therapy improved outcomes over 36 weeks as compared with usual care [19]. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Submovements are hypothesized to be discrete building blocks of human movement. Changes in their parameters appear to account for features observed in processes of motor learning and motor recovery from stroke. Our previous studies analyzed submovement changes in subjects recovering from stroke. Subjects were trained on point-to-point movements with the assistance of a rehabilitation robot as part of a stroke treatment protocol. Results suggested that recovery starts first by regaining the ability to generate submovements and then, over a longer time period, by reacquiring the means to combine submovements. Over recovery submovements became fewer, longer, and faster and such changes contributed to changes in movement smoothness. Taken together these results lent support to the theory that movement is produced via centrally generated submovements and that changes in submovements characterize recovery. More recently, we investigated generalization of training. We found that stroke subjects trained on point-to-point movements became progressively better able to draw circles, a task on which they had received no training. The goal of this paper was to further investigate the changes that occur in untrained movements during motor recovery from stroke. Specifically we wanted to test whether changes in smoothness and submovements also characterize untrained movements. We analyzed circle drawing movements performed by 47 chronic stroke subjects who underwent training on point-to-point movements over an 18-session robot-assisted therapy program. We found that during recovery the shapes drawn by subjects became not only closer to circles (a task not trained during therapy) but also smoother. Concurrently, submovements grew fewer, longer, and faster. These results are consistent with the theory that movement is produced via submovements and suggest that changes in smoothness and submovements might characterize and describe the process of motor recovery from stroke. Also, they are consistent with the idea that motor recovery after a stroke shares similar traits with motor learning.
    Cortex 03/2009; 45(3):318-24. DOI:10.1016/j.cortex.2008.02.008 · 6.04 Impact Factor
Show more