Robot-assisted movement training for the stroke-impaired arm: Does it matter what the robot does?

What was the answer to this 14 years ago?

“Could similar benefits be achieved with simpler, less expensive, nonrobotic technology that facilitates movement practice?”

Has the answer changed in 14 years?  Why the fuck doesn't your doctor and stroke hospital know that answer?  Simple, they are fuckingly incompetent and out-of-date.  

 

Robot-assisted movement training for the stroke-impaired arm: Does it matter what the robot does?

2006, The Journal of Rehabilitation Research and Development

 Leonard E. Kahn, PhD;
1–2
 Peter S. Lum, PhD;
3–4
 W. Zev Rymer, MD, PhD;
1–2
 David J. Reinkensmeyer, PhD
5
*
1
Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL;
2
 Departments of Biomedical  Engineering and Physical Medicine and Rehabilitation, Northwestern University, Evanston, IL;
3
 Hunter Holmes  McGuire Department of Veterans Affairs Medical Center, Richmond, VA;
4
 Biomedical Engineering, The Catholic

University of America, Washington, DC;
5
 Departments of Mechanical and Aerospace Engineering and Biomedical  Engineering, University of California, Irvine, CA

Abstract—

Robot-assisted movement training improves arm movement ability following acute and chronic stroke. Such training involves two interacting processes: the patient trying to move and the robot applying forces to the patient’s arm. A fundamental principle of motor learning is that movement practice improves motor function; the role of applied robotic forces in improving motor function is still unclear. This article reviews our work addressing this question. Our pilot study using the Assisted Rehabilitation and Measurement (ARM) Guide, a linear robotic trainer, found that mechanically assisted reaching improved motor recovery similar to unassisted reaching practice. This finding is inconclusive because of the small sample size (n = 19), but suggest that future studies should carefully control the amount of voluntary movement practice delivered to  justify the use of robotic forces. We are optimistic that robotic forces will ultimately show additional therapeutic benefits when coupled with movement practice. We justify this optimism here by comparing results from the ARM Guide and the Mirror Image Movement Enabler robotic trainer. This comparison suggests that requiring a patient to generate specific patterns of force before allowing movement is more effective than mechanically completing movements for the patient. We describe the engineering implementation of this “guided-force training” algorithm.
Key words:
arm movement, control strategies, motor control, motor learning, movement training, reaching, rehabilitation, rehabilitation therapy, robotics, stroke.

INTRODUCTION: CRITIQUE OF ROBOT-ASSISTED THERAPY

Robotic technology could partially automate movement training following injury to the central nervous sys-tem (CNS). Rehabilitation therapists spend significant time using hands-on therapy during stroke rehabilitation. Hands-on techniques, such as active assist exercise, are advocated in practice guidelines and standard texts [1–3]. Robotic devices, because of their programmable force-producing ability, can replicate some features of a therapist’s manual assistance, allowing patients to semiautonomously practice their movement training. However, robotic devices can also implement novel forms of mechanical manipulation impossible for therapists to emulate because of limited speed, sensing, strength, and repeatability of the therapist’s neuromuscular system.
ovel forms of manipulation may ultimately enhance movement recovery beyond current possibilities.Since the 1997 pioneering study of Massachusetts Institute of Technology (MIT)-Manus [4], the number of research groups developing robotic therapy devices has rapidly increased. As reviewed in this issue and elsewhere [5–9], devices have been developed for automating training for arm movement following stroke, gait and posture following stroke and spinal cord injury, and wrist and fin-ger movement following stroke. Initial results are promising: patients who receive more therapy with a robotic device recover more movement ability [9–10]. The benefits of robot-assisted therapy are comparable with or better than that of conventional therapy [11–12]. This article, however, offers an interim, yet critical, analysis of our early experiences with robot-assisted therapy. We argue that a substantial gap exists in the rationale for widespread implementation of robot assisted therapy in rehabilitation clinics because a key question remains unanswered: “Is the expense of an actuated device needed to achieve therapeutic benefit?” Put another way, “Could similar benefits be achieved with simpler, less expensive, nonrobotic technology that facilitates movement practice?” Nonrobotic technology includes exercise machines such as hand cycles, low-cost movement moni-toring, and virtual reality systems, and passive antigravity devices such as mobile arm supports and overhead slings. Clearly, a mechanical device that measures movement for directing rehabilitation is only made more expensive and less safe by adding robotic actuators. Thus, this question of the benefits of robotic actuators is practically and economically important for rehabilitation technologists and the clinicians and patients they serve. This question is also scientifically interesting, because answering it requires understanding how sensory motor activity influences CNS recovery. The answer will refine rehabilitation therapists’ actions during conventional, one-on-one therapy, as well as help determine the fate of robot-assisted therapy.We first explain why we think that this question remains unanswered, then we review two studies from our laboratories that provide clues to its answer. We focus our discussion on movement training of the arm following stroke, although similar issues are likely relevant for gait and hand training and for other CNS disorders. More comprehensive reviews of robotic therapy have been published elsewhere [5–9].

8 more pages at link.