Use of Robotic Tools in Neurorehabilitation

Alex Nastaskin, MS, ORT/L, Katherine Scheponik, MS, ORT/L, Joe Padova, MS, ORT/L, Mike Tobin, BS

 Brain injury often results in upper extremity impairment, including weakness, spasticity, impaired range of motion, impaired sensation and impaired motor coordination. Muscle, tendon, and joint capsules may stiffen when held in a shortened position for an extended time. Since spastic or flaccid hemiparetic patients often have difficulty moving an arm, functionality declines in the impaired arm due to learned non-use in favor of the intact arm.

Research suggests that task-oriented training focusing on the practice of skilled and meaningful motor performance is a critical link to facilitating neural reorganization and “rewiring” in the central nervous system (Takahashi, et al., 2008). Robotics can provide an opportunity for a person to engage in a task-oriented, structured, multisensory experience.  For example, the patient may be required to move a virtual object on a screen to a virtual shelf. As the machine detects the patient’s physical movements, a visualization of the moved object appears on a screen, illustrating the accuracy and results of the patient’s efforts in real time. The patient can adjust the effort accordingly and perfect the desired motor pattern, supporting neural reorganization that may allow restoration of movement and functionality in the affected arm. These reliable, measurable robotics programs provide repetition, and the customization options make this intervention available to patients with varied motor impairments.

An increasing number of studies indicate that functional motor improvements largely occur through compensatory strategies rather than actual neurological recovery, particularly within the first few weeks following injury (Kwakkel, Kollen and Lindeman, 2004). For example, according to many upper limb robotics studies over the last decade, subjects typically show substantial improvements when performing functional tasks, while demonstrating little change in impairment measures (Hidler, et al., 2005). Thus, rather than demonstrating actual impairment reduction, patients learn to use their impaired systems more effectively. This is an area where motor control and learning principles may provide a basis for developing more effective treatments. Motor control principles dictate repetition of desired movements with kinesthetic and proprioceptive feedback. Robotic neurorehabilitation allows motor learning through practice of a diverse set of repeated tasks with the addition of visual feedback on the individual’s performance.

Following injury onset and during the subacute treatment stage, patients frequently develop maladaptive movement and/or positioning patterns that provide comfort, but impede function as neurological recovery progresses. Robotic neurorehabilitation can promote un-learning of these maladaptive movements, which is particularly important, as sub-optimal positioning may cause soft tissue shortening or stiffening—another obstacle to recovery. If a desired movement can be attained with practice, robotic intervention can provide a platform to help patients replace adverse positioning and non-functional movement with goal-directed movement. One evidence-supported example of this process is constrained-induced movement therapy (CIMT) (Peurala, et al., 2011).  In CIMT, the intact arm is constrained and patient must complete tasks with his or her affected arm. Robotic neurorehabilitation provides a similar approach with the additional application of resistive, assistive and gravity-eliminating forces. This promotes isolated and purposeful movement patterns, customized to the patient’s level of impairment.

A distinct advantage of robotic therapy is the ability to customize task demands, track progress, and make adjustments according to the patient’s improvement. The amount of assistance provided by the robotic orthosis can be modified as patient strength or mobility improves, to facilitate enduring gains. A spring-activated arm exoskeleton orthosis can partially relieve the upper limb’s weight, enabling the patient to initiate goal-directed movement while engaged in a virtual task or doing other tasks designed to incorporate elements of functional arm motion (Gijbels, et al., 2011). For some patients with perceptual deficits, visual scanning may impact how far they can move the affected arm. By enlarging objects and making the work space smaller (or less visually busy), patients with perceptual impairments associated with brain injury may more easily initiate active, goal-directed movement. Working in an environment with minimized distraction, patients can sustain their attention towards a task for longer periods of time, which can lead to more active participation.

A body of evidence demonstrates that following brain injury people retain the ability to generate accurate motor images of actions they cannot perform (Decety and Ingvar, 1990) and that mental practice of motor skills can improve actual performance (Jackson, et al., 2001). Common cerebral motor representations are activated when imaging and planning voluntary movements (Sirigu, et al., 1995). Combining robotic and mental imaging techniques integrates sensorimotor and cognitive stimulation. Thus, robotic orthoses can move a patient’s arm passively and/or provide assistance for active movement, creating an opportunity for kinesthetic and proprioceptive activation. Simultaneously, mental imagery applied during the robotic-assisted motion focuses the patient’s conscious attention on the desired motion. For example, reaching for a cup is an automated – mainly subcortical – activity for people without impairment. Focusing the patient’s conscious attention on the movements involved in reaching and grasping is crucial in order to help reacquire motor representations. 

Case Study 1:
Mrs. P., a 66-year-old female with status post left CVA and right hemiparesis was admitted to outpatient occupational therapy. She presented with a variation of flaccidity and low muscle tone throughout the right upper extremity.  Tactile sensations were intact and there was moderate-intensity pain of the right rotator cuff musculature. During her initial evaluation, Mrs. P. displayed no signs of active motion with her right upper extremity and demonstrated severe difficulty completing upper extremity dressing due to right shoulder pain.  Mrs. P. began twice weekly, 30-minute sessions of robotic arm training using a full-Mrs. P., arm spring-assisted exoskeleton orthosis. After two weeks of robotic training, Mrs. P. began to initiate active isolated motion with right shoulder horizontal abduction, adduction and elbow flexion. This increased active motion allowed Mrs. P. to recruit shoulder stabilizers, position her right arm with less risk of injury and decrease right shoulder pain. Mrs. P. also began actively using her right arm as a gross stabilizer during daily routine tasks.  

Case Study 2:
Mr. R., a 58-year-old male with status post left CVA and right hemiparesis was admitted to outpatient occupational therapy and presented with moderate spasticity and flexion synergy of the right upper extremity.  Mr. R. also demonstrated poor proprioceptive sensation and poor fine and gross motor coordination with minimal, non-functional active movement of the right hand. His therapy plan consisted of robotic intervention twice weekly for at least 30 minutes per session. Robotic training involved the use of a hand exoskeleton that performed continuous passive and active flexion and extension for digits 1 through 5. During robotic training, the therapist asked him to attend to the details of the task, feeling proprioceptive and kinesthetic inputs from the motion, and visualizing the mental actions needed to physically reproduce the movement. After four weeks of combined robotic and mental imagery training, Mr. R. began to display active motion with digits 1-3 and increased grip strength. This gain in active motion and grip strength allowed him to hold grooming articles and use his right hand as an assist to complete self-care routine tasks.

Summary
The use of robotics in upper limb neurorehabilitation is transforming the delivery of therapy for people with both acute and chronic challenges.  It also opens the door to new functional gains, preservation of range of motion and increased motor control. Robots are not equipped or intended to replace therapists but can facilitate therapy delivery and increase patient engagement and motivation. As electronic orthoses evolve, the next phase of robotic neurorehabilitation may feature personal exoskeleton devices that allow daily, self-directed practice at home or possibly other primary settings of productive activity. Autonomous practice may improve recovery through higher intensity and repetition of desired motor patterns and overall facilitate more efficient and effective care.

References
Takahashi, C. D., Der-Yeghiaian, L., Le, V., Motiwala, R. R., & Cramer, S. C. (2008). Robot-based hand motor therapy after stroke. Brain, 131(2), 425-437.
Kwakkel, G., Kollen, B., & Lindeman, E. (2004). Understanding the pattern of functional recovery after stroke: facts and theories. Restorative neurology and neuroscience, 22(3-5), 281-300.
Hidler, J., Nichols, D., Pelliccio, M., & Brady, K. (2015). Advances in the understanding and treatment of stroke impairment using robotic devices.
Peurala, S. H., Kantanen, M. P., Sjögren, T., Paltamaa, J., Karhula, M., & Heinonen, A. (2012). Effectiveness of constraint-induced movement therapy on activity and participation after stroke: a systematic review and meta-analysis of randomized controlled trials. Clinical rehabilitation, 26(3), 209-223.
Gijbels, D., Lamers, I., Kerkhofs, L., Alders, G., Knippenberg, E., & Feys, P. (2011). The Armeo Spring as training tool to improve upper limb functionality in multiple sclerosis: a pilot study. Journal of neuroengineering and rehabilitation, 8(5), 5.
Decety, J., & Ingvar, D. H. (1990). Brain structures participating in mental simulation of motor behavior: a neuropsychological interpretation. Acta Psychologica, 73(1), 13-34.
Jackson, P. L., Lafleur, M. F., Malouin, F., Richards, C., & Doyon, J. (2001). Potential role of mental practice using motor imagery in neurologic rehabilitation. Archives of physical medicine and rehabilitation, 82(8), 1133-1141.
Sirigu, A., Cohen, L., Duhamel, J. R., Pillon, B., Dubois, B., Agid, Y., & Pierrot-Deseilligny, C. (1995). Congruent unilateral impairments for real and imagined hand movements. Neuroreport, 6(7), 997-1001.

About the Authors
Alex Nastaskin, MS OTR/L has over 11 years of experience in both inpatient and outpatient neurological rehabilitation. His specialties include intervention models for right hemisphere stroke population and upper extremity robotic rehabilitation.  He is also certified in Kinesiotaping. 

Katherine Scheponik, MS, OTR/L is an outpatient occupational therapist and has also been a yoga instructor for 10 years with an interest in complementary and alternative therapies for neurological disorders.  

Joe Padova, OTR/L is the long-standing clinical specialist for outpatient neurological rehabilitation at MossRehab regarding upper limb amputee retraining, neurological rehabilitation, kinesiology, orthopedics, splinting, adaptive equipment design in integration of upper extremity robotic trainers for neurologic rehabilitations.

Mike Tobin, BS is an occupational therapy aide with an interest in upper limb robotics and assistive technology.