Advanced Rehabilitation Technologies and Robotics

A Clinician's Guide

Every year more than 795,000 people have a stroke in the united states making it one of the leading causes of long-term disability (CDC, 2017).

Rehabilitation robotics, a popularly researched treatment tool, is growing rapidly amongst a wave of new advanced rehabilitation technologies. This technology may be effective in matching current clinical research and providing a safe adjunct to therapy.

What we know

The healthcare market is growing rapidly in response to new demands for advanced rehabilitation technologies in clinical settings serving clinicians including occupational therapists (OTs), physical therapists (PTs) and speech-language pathologists (SLPs) specializing in neurological rehabilitation. Significant research in neuroplasticity, or the re-organization of the brain following acute stroke, points to evidence that factors in early clinical rehabilitation such as task-repetitive use of the affected upper extremity, specificity of treatment, repetition, intensity, time, and increased motor therapy dosing are critical in the early stages of cortical reorganization (Kleim & Jones, 2008). We know that in the early stages of stroke rehabilitation following stroke the brain is at its most plastic for regaining sensory and motor function. It is also becoming clear that that the typical daily dosage of task and motor repetitive training does not meet current research on intensity (Krakauer, Carmichael, Corbett, & Wittenberg, 2012). While current research has not validated a definitive number of upper-extremity (UE) motor repetitions for maximal cortical return, we can compare the average number of motor repetitions in a traditional patient session (an average of 32; according to Waddell et al., 2014) to current research averages in animal models and constraint-induced therapy (CIMT) treatments (300 and above) demonstrating optimal gains in UE function and motor control (Wolf et al., 2006; Krakauer et al., 2012).

UE motor learning perspectives are changing.

let’s look at some traditional upper extremity motor interventions. These might include neurodevelopmental treatments such as Bobath and Proprioceptive Neuromuscular Facilitation techniques, bilateral training, functional reach training, strength training, task-specific repetitive training, sensorimotor training, mental practice, and mirror therapy treatment (Teasell & Hussein, 2016). In the field of occupational therapy motor learning perspectives have seen a paradigm shift from early perspectives concentrating on impairment-based biomechanical frameworks (early Bobath models) to functional and client-based treatments. Treatments are getting more function-based and technology is playing a greater role in human occupation every day. New advanced technologies may be the next step to providing the early intensity needed to promote optimization of UE function and cortical plasticity in the brain.

Advanced technologies are making an appearance in rehabilitation settings today. 

Some advanced technologies you may have experienced in the clinic include:

  • Functional Electrical Stimulation (FES)—Electrical stimulation of task-associated muscle groups during an activity, such as functional reach.

  • Virtual Reality Programming—Advanced gaming technology involving a complex and realistic virtual environment that provides sensory feedback.

  • Electromyography (EMG)—Technologies that read EMG or electrical signals from the muscle belly to determine neuromuscular activation.

  • Sensor-based Technologies—Use sensor-based feedback to determine position, movement and motor performance. 

  • Brain Stimulation Therapy—Non-invasive brain stimulation therapies such as transcranial magnetic stimulation (TMS) seek to promote cortical plasticity following stroke (Kubis, 2016).

  • Robotic Therapy Platforms—Advanced active-assistive therapy platforms utilizing gravity elimination and robotic assistance.

What do these advanced technologies target? 

Advanced therapy platforms have a variety of rehabilitation applications often targeting outcomes in:

  • Motor control and performance

  • Cognition

  • Gross and fine motor coordination

  • Functional movement patterns

  • Sensory stimulation

Where can I find value as an occupational therapist?

Looking at traditional views in the OT Domain & Process (2017), value can be found traditionally in a holistic treatment plan that promotes occupational gains through functional or task-oriented training, training of client factors, performance skills and patterns, and environmental factors. In the physical rehabilitation setting therapists seek to achieve functional gains through improving or adapting motor and processing skills. These advanced technologies offer an innovative approach in treating motor and processing skills. One of the most critical driving factors for successful rehabilitation is facilitating patient engagement and excitement for every patient considering varying diagnoses and levels of impairment. A cutting-edge piece of rehabilitation technology must not only produce good data from a technical outcome perspective, but be inclusive, adaptable and embrace the most important values of rehabilitative therapists, physicians, and patients.

Getting to Know Rehabilitation Robotics

Active-assistive robotic therapies usually target the upper extremity (UE) or lower extremity (LE). Lower extremity systems include advanced foot orthoses, exoskeletons, and body weight support systems including: treadmill gait trainers, stationary gait trainers, foot-plate gait trainers, and overground gait trainers (Diaz et al., 2011). Upper extremity robots fall into the two main categories of in-clinic and portable devices. The two major in-clinic systems represent end-effector and exoskeleton systems. Exoskeletons provide greater precision as far as individual joint control, where end-effectors will have greater adaptability and a shorter setup time. Common features of in-clinic systems include active exercise, active robot-assisted exercise, passive exercise, coaching feedback such as auditory or visual cues, and haptic features such as resistance or vibration (Maciejasz et al., 2014). These devices support the motor learning rehabilitation continuum with a wide range of task-oriented games and activities with detailed task-grading features and adjustability to reach a level of optimal challenge for carryover of motor gains.

What do rehabilitation robots do well?

One of the major strengths of UE robotic systems is reducing therapist strain associated with mobilization of the upper extremity during traditional upper extremity interventions. Robotic therapy platforms can provide a higher number of movement repetitions and task-repetitive dosing without fatigue over long patient sessions. According to one study 54% of work related injuries across OT and PT disciplines are associated with manual therapy and transferring (Darragh, Camp, & King, 2012). Robotic devices can offer technical precision and accuracy while protecting against therapist burnout and injury. Another benefit of robotic devices is their ability to collect and store data relating to parameters of patient function which aid therapists in the patient evaluation process. Robotic technologies have the ability to track small changes in forces and movements to aid in treatment planning and patient goal setting. Robotics systems can offer a sense of autonomy and motivation early in the rehabilitation continuum and a sensory-rich environment difficult to find in a traditional hospital or skilled nursing setting. Advanced gravity elimination allows therapists to be more creative with early UE exercise for densely motor-impaired patients. The ability of some devices to provide gravity elimination across all anatomical planes of the shoulder, isolate normative movement patterns, and resist reflexive movement patterns mark a unique strength of robotic technologies.

Advanced rehabilitation technologies are becoming more and common in the world of rehabilitation.

And they are addressing targeted outcomes in motor control and performance, cognition, gross and fine motor coordination, functional movement patterns and sensory stimulation. Advanced robotic technologies offer a wide range of features and opportunities for improving patient outcomes through high repetition, patient engagement, precise evaluation features, and reduced therapist strain. Many different research-grade features target motor learning and patient engagement with added adaptability across varying levels of patient function. With new evidence and promising research in rehabilitation robotics and advanced technologies occurring each year, these devices may provide an answer to solving current dilemmas in stroke and neurological rehabilitation.

For more information on advanced technologies see the references and resources below!

Article by Holly Mitchell, MOT, OTR/L

REFERENCES

Smith, R. O. (2017). Technology and Occupation: Past, Present, and the Next 100 Years of Theory and Practice. American Journal of Occupational Therapy,71(6). doi:10.5014/ajot.2017.716003

Occupational Therapy Practice Framework: Domain and Process (3rd Edition). (2017). American Journal of Occupational Therapy,68(Supplement_1). doi:10.5014/ajot.2014.68s1

Díaz, I., Gil, J. J., & Sánchez, E. (2011). Lower-Limb Robotic Rehabilitation: Literature Review and Challenges. Journal of Robotics, 2011, 1-11. doi:10.1155/2011/759764

Teasell, R., & Hussein, N. (2016). Stroke rehabilitation clinician's handbook: Recovery for upper extremity. London: Department of Physical Medicine and Rehabilitation, St. Joseph Health Care.

Gillen, G. (2016). Stroke rehabilitation: a function-based approach. St. Louis (Missouri): Elsevier.

Lang, C. E., Lohse, K. R., & Birkenmeier, R. L. (2015). Dose and timing in neurorehabilitation. Current Opinion in Neurology,28(6), 549-555.

Stroke. (2017, September 06). Retrieved March 08, 2018, from https://www.cdc.gov/stroke/facts.htm

Krakauer, J. W., Carmichael, S. T., Corbett, D., & Wittenberg, G. F. (2012). Getting Neurorehabilitation Right - What Can We Learn From Animal Models? Neurorehabilitation and Neural Repair,26(8), 923-931. doi:10.1177/1545968312440745

Waddell, K. J., Birkenmeier, R. L., Moore, J. L., Hornby, T. G., & Lang, C. E. (2014). Feasibility of High-Repetition, Task-Specific Training for Individuals With Upper-Extremity Paresis. American Journal of Occupational Therapy,68(4), 444. doi:10.5014/ajot.2014.011619

Aarli, J., Dua, T., Janca, A., & Muscetta, A. (2006). Neurological Disorders: Public Health Challenges (Rep. No. 92 4 156336 2). Geneva, Switzerland: World Health Organization.

Kleim, J. A., & Jones, T. A. (2008). Principles of Experience-Dependent Neural Plasticity: Implications for Rehabilitation After Brain Damage. Journal of Speech Language and Hearing Research, 51(1). doi:10.1044/1092-4388(2008/018)

Wolf et al., (2006). The EXCITE Trial: Predicting a Clinically Meaningful Motor Activity Log Outcome. Neurorehabilitation and Neural Repair 22(5), 486 - 493.

Kimberley, T. J., Samargia, S., Moore, L. G., Shakya, J. K., & Lang, C. E. (2010). Comparison of amounts and types of practice during rehabilitation for traumatic brain injury and stroke.The Journal of Rehabilitation Research and Development,47(9), 851. doi:10.1682/jrrd.2010.02.0019

Kubis, N. (2016). Non-Invasive Brain Stimulation to Enhance Post-Stroke Recovery. Frontiers in Neural Circuits, 10, 56. http://doi.org/10.3389/fncir.2016.00056

Maciejasz, P., Eschweiler, J., Gerlach-Hahn, K., Jansen-Troy, A., & Leonhardt, S. (2014). A survey on robotic devices for upper limb rehabilitation. Journal of NeuroEngineering and Rehabilitation, 11(1), 3. doi:10.1186/1743-0003-11-3

Darragh, A. R., Campo, M., & King, P. (2012). Work-related activities associated with injury inoccupational and physical therapists. Medline, 42(3). doi:10.3233/WOR-2012-1430

Hannah Cox