A Configuration-Space Approach to Controlling a Rehabilitation Arm Exoskeleton

Carignan, Craig R.; Tang, Jonathan; Roderick, Stephen; Naylor, Mike

doi:10.1109/icorr.2007.4428425

Cited by 43 publications

(34 citation statements)

References 11 publications

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“…Furthermore, multijoint movements may be learned as joint coordination ratios or relative joint patterns [48][49]. Motivated by these results, researchers have focused on developing exoskeleton robots that directly control limb degrees of freedom (DOFs) [50][51][52][53][54][55][56].…”

Section: Introductionmentioning

confidence: 99%

Retraining of interjoint arm coordination after stroke using robot-assisted time-independent functional training

Brokaw¹,

Murray²,

Nef³

et al. 2011

JRRD

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Abstract-We have developed a haptic-based approach for retraining of interjoint coordination following stroke called time-independent functional training (TIFT) and implemented this mode in the ARMin III robotic exoskeleton. The ARMin III robot was developed by Drs. Robert Riener and Tobias Nef at the Swiss Federal Institute of Technology Zurich (Eidgenossische Technische Hochschule Zurich, or ETH Zurich), in Zurich, Switzerland. In the TIFT mode, the robot maintains arm movements within the proper kinematic trajectory via haptic walls at each joint. These arm movements focus training of interjoint coordination with highly intuitive real-time feedback of performance; arm movements advance within the trajectory only if their movement coordination is correct. In initial testing, 37 nondisabled subjects received a single session of learning of a complex pattern. Subjects were randomized to TIFT or visual demonstration or moved along with the robot as it moved though the pattern (time-dependent [TD] training). We examined visual demonstration to separate the effects of action observation on motor learning from the effects of the two haptic guidance methods. During these training trials, TIFT subjects reduced error and interaction forces between the robot and arm, while TD subject performance did not change. All groups showed significant learning of the trajectory during unassisted recall trials, but we observed no difference in learning between groups, possibly because this learning task is dominated by vision. Further testing in stroke populations is warranted.

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Section: Introductionmentioning

confidence: 99%

Retraining of interjoint arm coordination after stroke using robot-assisted time-independent functional training

Brokaw¹,

Murray²,

Nef³

et al. 2011

JRRD

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“…This makes the device heavier, more costly, and more likely to fail. Then again, the linkages aren't much more complex than the additional mechanics used for shoulder translations in the ARMin [143], the cable guiding mechanisms in the CADEN-7 [154], or the additional clavicula-limb in the MGA-Exoskeleton [27]. For reasons of minimal space usage, low impedance and easy inclusion of weight support, the double 3D parallelogram is our preferred linkage.…”

Section: Discussionmentioning

confidence: 99%

“…3.1). For instance, some exoskeletons use cable suspensions for the weight support [143,202]; others use powerful actuators in a mechatronic control loop [27]. Overall, weightsupporting forces can be generated and applied in many different ways, with some mechanisms more suitable than others.…”

Section: Introductionmentioning

confidence: 99%

“…For most of these, patients hold onto a handle while making movements in virtual environments. Exoskeletons are external skeletons placed over the arm and mostly powered by actuators on the joints [140,179,61,143,27,154]. They control not only a single endpoint position, but also (a subset of) the joints of the shoulder, elbow, and wrist directly, at the cost of more complex mechanics.…”

Section: Introductionmentioning

confidence: 99%

“…The ARMin [143] uses an vertical four-link mechanisms which couples the shoulder elevation rotation of the exoskeleton to its vertical shoulder translation with a single degree of freedom. Finally, the MGA-Exoskeleton [27] adds a rotational degree of freedom to the shoulder, mimicking clavicula rotations to produce the vertical translations for the exoskeleton shoulder.…”

Section: Introductionmentioning

confidence: 99%

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Development of novel devices for upper-extremity rehabilitation

Stienen¹

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S U M M A R YThe goal of this dissertation was to improve rehabilitation robots by developing new patient-friendly devices which can assist therapists in the rehabilitation of neurological movement disorders of the upper extremities, such as hemiparetic stroke. In all, three novel rehabilitation devices were developed. Given the changing demographics of developed nations, over the next two decades fewer therapists will be available to treat an increasing number of stroke patients. With patient-friendly robots assisting therapists, proven therapeutic exercises can be automated and new and better targeted interventions developed and tested. In addition to facilitating therapy sessions, robots can provide objective measurement of impairment. Overall, robots can make therapy more productive for patients and less labor-intensive for therapists, and provide physicians, therapists and the scientific community with more objective data.To handle the wide range of impairments found in hemiparetic stroke patients, multiple devices are needed. Mildly impaired patients may have a near-normal range of motion, but have problems with fine motor control or moving heavier objects. Severely affected patients may not be able to even lift the weight of their own arm. Despite these differences, certain general strategies appear to work best. First and foremost, rehabilitation therapy works best when the patient is actively and intensively involved. Exercises should use repetitive movements that closely resemble those used in daily living for best results in reshaping the recovering brain.Studying motor learning in healthy subjects supported the need for active patient involvement. Given the artificial motor relearning task of moving in a visuomotor-rotated field, the healthy subject fully adapted when he could freely make, and correct, errors in their movement execution. On the other hand, active delivery of a passive hand to the targets resulted in much less and much slower adaptation. In between lay the adaptation achieved with hard and soft guidance of the hand over virtual tracks. The conclusion is that both minimization of execution errors and control effort drive kinematical adaptation in a novel visuomotor task, but the latter occurs at a much slower rate.Should the patient not be assisted at all? Perhaps the type of assistance is important. For instance, weight support of the arm facilitates movement, but movement initialization and control are left unchanged. Most rehabilitation devices for upper extremities include some form of weight support. An analysis of these devices concluded that weight support is most easily realized through a cablesuspension system that supports the arm via slings. However, the best possible solution for weight support depends on the primary design of the device. Careful upfront consideration of various design options will lead to better choices.The first rehabilitation device was designed using this knowledge. The Freebal is a dedicated weight-support system that is less complex and has less movem...

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