ReWalk Robotics Ltd has finalized and moved to implement two separate agreements to distribute additional product lines in the United States market. These include telehealth-capable stroke rehabilitation devices as well as clinic and home use devices for persons with spinal cord injury.
Upon commencement of the effective periods of these agreements, the company will be the exclusive distributor of the MediTouch Tutor movement biofeedback systems in the United States, and will also have distribution rights for the MYOLYN MyoCycle Functional Electrical Stimulation (FES) cycles to US rehabilitation clinics and personal sales through the US Department of Veterans Affairs hospitals, the company notes in a media release.
“These impressive technologies serve similar clinician and patient profiles as our current products, which presents an opportunity to increase same-site sales, and offering a broader portfolio of solutions also potentially expands our access to new customers,” says Andy Dolan, Vice President of Marketing at ReWalk.
“The MediTouch Tutor devices will also give us an entry into the telehealth-capable products category to leverage recent COVID-19 related reimbursement changes and trends in rehabilitative care.”
The MediTouch Tutor movement biofeedback product line includes the Arm, Hand, 3D and Leg Tutor devices. These devices are used by physical and occupational therapists to evaluate functional tasks during rehabilitation of neurologic disorders, and can also be used by patients remotely at home. The system consists of sensors attached to textiles worn on the patient’s hand, arm or leg to detect motion and a web-based program which uses game play to provide instruction and motivation to the patient user. The program also captures and evaluates patient progress and provides feedback to the clinician.
“Entering the US physical rehabilitation clinic and home telehealth markets with our innovative wearable devices and web-based MediTutor app in order to provide the best clinical care and affordable cost effective treatment, while enabling social distancing specifically during this pandemic is a key goal for our company, and we believe that this partnership with ReWalk gives us the customer access we need,” states Giora Ein-ZVi, CEO of MediTouch, the release continues.
The MYOLYN MyoCycles use FES to facilitate therapeutic exercise for persons with muscle weakness or paralysis caused by disorders like spinal cord injury, multiple sclerosis, and stroke. Similar to the ReWalk exoskeleton, these devices can be used in a clinic for rehabilitation or training for an individual to eventually use their own at home. Both the MyoCycle Pro for clinic use and MyoCyle Home for patient home use have Federal Supply Schedule contracts to facilitate sales to VA hospitals and patients with VA benefits.
photo caption: Elizabeth Watson, PT, DPT, NCS, works with a client on gait training using a robot-assisted over-treadmill dynamic body weight support system.
by Elizabeth Watson, PT, DPT, NCS
Recovery following a neurological injury is a long, slow process and does not follow a set time frame. Recovery is about more than just walking; it is about regaining function and improving overall quality of life.
This article explores a specialized program at Magee Rehabilitation Hospital-Jefferson Health in Philadelphia called Gaining Ground. The goal of Gaining Ground is to extend Magee’s mission beyond traditional physical and cognitive therapy services and reduce the barriers to continued exercise and wellness. This article also highlights the different technologies used during this program and the impact on the quality of life of the participants.
Increased evidence supports the benefits of exercise and physical activity on the physiologic and psychosocial function of individuals following neurological injuries.1 In addition, physical inactivity following a neurological injury leads to increased vulnerability to secondary health complications, including cardiovascular disease and loss of bone density and muscle mass.1 Evidence-based physical activity guidelines have been established for the general population and those with disabilities. These guidelines highlight the importance of moderate-intensity aerobic exercise and strength training for individuals with spinal cord injuries and stroke survivors.2,3
Making Progress Accessible
Barriers to continued exercise following a neurological injury include lack of accessible fitness facilities, absence of personal assistants knowledgeable about exercise programs appropriate for those with neurological injuries, absence of specialized equipment, and fear of injury. Gaining Ground was developed to reduce these barriers.
Gaining Ground is an individualized exercise program, taking into account the goals and abilities of the client. The intensive, boot camp-style program takes place 3 days a week for 4 weeks. Clients vary in presentation from those at a power wheelchair level to ambulatory patients. Some are more recently injured, just finishing outpatient therapy and looking to be challenged further and establish a wellness program. Other clients have been injured for more than 20 years and are exploring newer technologies and treatment techniques that did not exist when they were first injured. These clients find that the program’s intense nature often encourages a continued wellness program after Gaining Ground ends.
Each day includes 4 hours of exercise. A one-on-one training session with an activity-based therapy specialist focuses on increasing cardiovascular endurance, muscle strength and flexibility, sitting or standing tolerance, and balance. Working with a physical therapist provides the opportunity to continue working toward goals not reached during traditional therapy, as well as a chance to trial different technologies and specialized equipment working toward more neurological recovery. Once a client’s program is established, he or she is set up on specialized equipment such as a locomotor device or FES cycle for an hour of activity-based exercise.
A daily group exercise class helps increase strength, improve cardiovascular endurance, and enhance overall well-being. Exercises emphasize the muscle groups of the upper extremity and core necessary to complete daily functional activities. Group sessions include a circuit using the multi-station wheelchair-accessible weight machine, a wheelchair-accessible upper extremity exerciser, a conventional weight machine, a free weight and therapy band circuit training program, and getting onto the floor to work on whole body exercises. This allows clients the opportunity to practice getting on and off the floor in a safe environment and reduce the negative association of being on the floor related to falls. The group environment fosters interaction with others working toward a common goal.
Cardiorespiratory and strength training presented in a group setting with peers provides not just physical but also emotional improvements.1,4 Depression scores and bodily pain scores decreased after participation in a group exercise program for individuals with spinal cord injuries. Past participants of Gaining Ground have commented on the motivating environment of the group sessions.
Equipment utilized during the program may include functional electrical stimulation systems, gait training devices such as the robot-assisted over-treadmill dynamic body weight support system, mobile robotic over-ground body weight support system, lower extremity robotic exoskeletons, vibration therapy plate, computerized balance system, wheelchair-accessible upper extremity exerciser, multi-station wheelchair accessible weight machine, resistance circuit trainer, rowing ergometer, recumbent trainer, and upper body ergometer. A few of the more advanced technologies are detailed below.
Body Weight Support Training
The robot-assisted over-treadmill dynamic body weight support system utilizes robotic-assisted gait training. A harness suspends the patient over a treadmill while the legs are guided through the walking pattern using a robotic orthosis. Speed, the amount of load through the legs, and the amount of guidance provided by the robotic orthosis, are all variables that can be adjusted to appropriately challenge the client. The robot-assisted over-treadmill body weight support system enables effective and intensive training promoting neuroplasticity and recovery potential.
This system can be used with various augmented performance feedback games. The level of difficulty can be chosen based on the client’s ability and therapy focus. Studies have shown that when using augmented performance feedback, muscle activation and cardiovascular exertion can be considerably increased.5 Most clients in the Gaining Ground Program utilize this device two to three times a week.
The mobile robotic over-ground body weight support system allows a therapist to work on overground balance and gait training, bridging the gap between treadmill-based activities and free walking. The system can provide body-weight support equally or asymmetrically depending on a client’s impairments. Therapists can steer this device or choose the mode that allows a patient to work on self-directed gait. Therapists can challenge the patient with various balance and functional activities by using a balance board, steps, or varied terrain within the width of the device’s frame.
Another type of equipment used for upright positioning and gait training are robotic exoskeletons designed for the lower limbs. These wearable bionic suits help patients with lower extremity weakness or paralysis to stand and walk overground using a reciprocal pattern with full weight bearing using a walker, crutches, or cane. Sensors in the device trigger a step once the patient shifts weight in the appropriate manner. Motors in the hip and knee joints power the movement in place of decreased leg function. During the Gaining Ground program, therapists use the exoskeletal devices in two ways. The robotic exoskeleton allows those with motor complete spinal cord injuries the opportunity to be upright and reap the benefits of dynamic weight bearing. These include maintenance of bone mass, improved balance and trunk activation, improved sleep, mental outlook, mood and motivation, improved bowel and bladder function with decreased incidence of UTIs, decreased pain, decreased incidence of pressure ulcers, reduction in fat mass, and increase in lean body mass.
These devices can also be used to retrain weight shifting and gait patterns of clients with incomplete spinal cord injuries, and post stroke or traumatic brain injury. As a client relearns the appropriate gait pattern, the amount of assistance provided by the motors is adjusted at each leg and each joint individually to challenge the client. Improved gait parameters and gait speed have been seen following gait retraining using exoskeletal devices with individuals who have incomplete paralysis.
Functional Electrical Stimulation
Functional electrical stimulation (FES) is used in various forms during the Gaining Ground program. Some clients are set up on the FES cycle or FES seated elliptical. Electrodes are placed on up to 12 muscles of the upper extremity, core, or lower extremities. The therapist can customize the stimulation settings to evoke the desired muscle contraction for each muscle group. The motor of the cycle provides the support necessary to complete the cycling motion in conjunction with the stimulation-producing muscle contractions for either upper extremity or lower extremity cycling.
Many patients with neurological injuries experience decreased mobility and physiological function. This more sedentary lifestyle caused by immobility contributes to secondary health complications and the chance of re-hospitalization. The benefits of the FES systems extend beyond reducing muscle atrophy and improving motor function. Studies have shown a positive therapeutic benefit affecting many health conditions including pneumonia, hypertension, heart disease, spasticity, bone density, pressure wounds, urinary tract infections, sepsis, diabetes, weight gain, depression, and quality of life.6
The task-specific integrated functional electrical stimulation systems are utilized by therapists in the Gaining Ground program to work on coordinated, dynamic movement patterns and functional skills with up to 12 channels of stimulation. Each activity has the correct sequenced stimulation pattern to perform the prescribed activity. Common programs worked on during the Gaining Ground program include seated postural correction, bridging, sit to stands, standing, and UE movement patterns. One client with a diagnosis of C4 AIS B tetraplegia demonstrated improved self-feeding and the ability to access the controls on his power wheelchair joystick versus switch options after using the forward reach and grasp program for two consecutive rounds of Gaining Ground.
Nicole suffered a T2 AIS B injury on August 18, 2018, after an auto accident. In addition to several broken vertebrae, she also suffered six broken ribs, a collapsed lung, and lacerations to her head, face, and hands. Doctors performed two surgeries on her spine, and she underwent intense respiratory therapy. Nicole attended Gaining Ground about 7 months after her injury. She “loved how it pushed [her] out of her comfort zone.” Nicole recognized the individualized nature of the program and how it could be customized to fit her goals. Nicole’s program incorporated use of the exoskeleton or the task-specific integrated FES system for postural retraining and standing during her therapy hours and the robotic over-treadmill dynamic body weight support system three times a week. The training sessions with the activity-based therapy specialist demonstrated what she could achieve independently to continue to challenge herself after the program. As a personal trainer prior to injury, Nicole found this especially valuable. Nicole demonstrated significant progress in her ability to get up and down off the floor each week and realized how important a skill this is.
Magee’s Gaining Ground Program offers clients the opportunity to improve their functional independence and emotional well-being, while setting goals for future wellness initiatives. The small group setting has proven beneficial in helping individuals achieve these goals and make new friends in the process. RM
Elizabeth Watson, PT, DPT, NCS, is clinical supervisor of the Locomotor Training Clinic at Magee Rehabilitation in Philadelphia. She also serves as adjunct professor for area physical therapy programs. In 2018, Dr Watson received the SCI Spinal Interest Group Award for Excellence. Watson earned her DPT from Temple University and is ABPTS certified in Neurologic Physical Therapy. She has presented nationally and published case studies on locomotor training. For more information, contact RehabEditor@medqor.com.
Crane DA, Hoffman JM, Reyes MR. Benefits of an exercise wellness program after spinal cord injury. J Spinal Cord Med. 2017;40(2):154-158.
Martin Ginis KA, van der Scheer JW, Latimer-Cheung AE, et al. Evidence-based scientific exercise guidelines for adults with spinal cord injury: an update and a new guideline. Spinal Cord. 2018;45:308-321.
Gordon NF, Gulanick M, Costa F, et al. Physical activity and exercise recommendations for stroke survivors: an American Heart Association scientific statement from the Council on Clinical Cardiology, Subcommittee on Exercise, Cardiac Rehabilitation, and Prevention; the Council on Cardiovascular Nursing; the Council on Nutrition, Physical Activity, and Metabolism; and the Stroke Council. Stroke. 2004;35(5):1230-1240.
Saunders DH, Greig CA, Mead GE. Physical activity and exercise after stroke, review of multiple meaningful benefits. Stroke. 2014;45: 3742–3747.
Zimmerli L, Jacky M, LÜnenburger L, Reiner R, Bolliger M. Increasing patient engagement during virtual reality-based motor rehabilitation. Arch Phys Med Rehabil. 2013;94(9):1737-1746.
Dolbow DR, Gorgey AS, Ketchum JM, Gater DR. Home-based functional electrical stimulation cycling enhances quality of life in individuals with spinal cord injury. Top Spinal Cord Inj Rehabil. 2013 Fall;19(4):324-329.
Post Acute Medical LLC, a system of inpatient rehabilitation hospitals, has acquired three additional EksoNR devices from Ekso Bionics to expand the availability of exoskeleton-assisted rehabilitation to seven of its facilities.
The new EksoNR devices will be placed in Kyle and Clear Lake, Texas and Tulsa, Oklahoma. Exoskeleton-assisted rehabilitation is now available at five PAM locations in Texas. The device is designed to help patients stand and walk during rehabilitation after a stroke or spinal cord injury.
“Using EksoNR exoskeletons to help our stroke and spinal cord injury patients learn to walk again has been transformative,” says Anthony Misitano, PAM’s President and Chief Executive Officer, in a media release.
“The technology has been an integral part of our patients’ recovery and our physical therapists are eager to integrate it into their care of more patients. We are pleased to respond to the needs of our patients and providers with three additional EksoNR devices.”
PAM provides inpatient rehabilitation services in 12 states through 41 inpatient rehabilitation hospitals and long-term acute care hospitals, as well as more than 32 outpatient physical therapy locations, per the release.
“We are excited to see the growth of exoskeleton-assisted rehabilitation in systems like PAM,” Jack Peurach, Chief Executive Officer and President of Ekso Bionics, comments in the release.
“Using our exoskeleton devices in rehabilitation can provide better patient outcomes by helping patients walk farther and faster, and have better balance outside of the device. We are thrilled that PAM is embracing our technology and making it available to more of their patients.”
Developed for neurorehabilitation, EksoNR is an intuitive exoskeleton device that empowers patients recovering from stroke or spinal cord injury to learn to walk again with a more natural gait.
If you have a disability and you’re interested in going on to study further education then have a look at the tips we’ve come up with. This isn’t just for wheelchair users – my good friend who’s a deafblind medical student was kind enough to give me her tips too.
1. Visit prospective universities well in advance of applying to check for access and suitability. Don’t just go to open days but make sure you sit down with the school and also the disability service to know support would be like, but also to get a feel for what attitudes towards disability are like. I know, for me, when I was applying for my PGCE I had to choose the university based on access. You only apply for two places and one had much better access than the other so I was really hopeful I’d get into the one that had better access and not a library only accessed via a field!
2. Make sure you apply for disabled students allowance with plenty of time before you start studying. The equipment and support can make the biggest difference in making your student life easier. I was able to get a new laptop, and enough other equipment to kit me out with a full office which meant, if I wasn’t going into uni, that I was able to do everything from home.
3. Travelling to university can be tricky. When I was doing my PGCE I was living at home with my parents initially I took advantage of the free taxis I got to and from uni and placement. After a while, I needed to be a little more flexible in the time I left uni or school each day. As many Londoners will tell you, public transport isn’t always very easy, or convenient for wheelchair users so it wasn’t long before I started driving everywhere. So I started driving to uni every day. If you are going to take taxis make sure you find a good company, as I found it quite tricky to find one which would accommodate
4. Make sure you know your rights and who to go to if you’re not getting the right support or if you’re being discriminated against. I know have friends who have been unfairly discriminated against whilst studying so be aware that you could be subject to similar treatment.
5. While you’re studying, enjoying student lifestyle, and all the opportunities university life can bring, make sure you take some time to rest. Getting a work-life balance is really important, especially if you have a disability, because studying with a disability means we have to work much harder than the rest of the able-bodied students. That could be getting to and from class, formatting work beforehand to make sure it’s accessible and managing our health and medical needs.
6. There are some organisations who are great at supporting or advocating for disabled students. My Plus Students Club are brilliant, especially for getting people into work. Also, for the spinal cord injured among you, Back Up have an education service where an advocate can come into your school, college or university and advise staff about supporting someone with a SCI and give a talk to your peers if you wish.
I really enjoyed studying after I sustained my spinal cord injury. It can be challenging but can also provide you with a lot of opportunities, both career-wise, but also in terms of fun activities to get involved with while you’re at university. If you’re intending on going to study – good luck and enjoy it!
If you’ve studied with a disability let us know any tips you have from your experience in the comments below to help others further!
Purpose: the primary focus of this review was to find out the effectiveness of robotics in improving upper extremity functions among people with neurological problems in the arena of physical rehabilitation.
Material and Methods: Two reviewers independently scrutinized the included studies. The selected studies underwent quality assessment by PEDro scale. Randomized Controlled Trial (RCT) having a score of 4 or more were included in the review. A search was conducted in PUBMED, MEDLINE, CINAHL, EMBASE, PROQUEST, science direct, Cochrane Library, Physiotherapy Evidence Database (PEDro) and Google Scholar.
Results: A total of 202 studies were identified. After removal of duplication, inclusion and exclusion criteria’s n = 23 studies were included in the review process. For analysis, only the primary outcome measures of the studies were taken into account. Studies finally included in analysis were n= 21. The included studies were 19 in stroke, 1 in cerebral palsy (CP), and 1 study in multiple sclerosis (MS). No RCTs were reportedly found in spinal cord injury, Parkinson and motor neuron disease.
Conclusion: Studies related to stroke showed a clear definiteness in the improvement of upper extremity functions. Whereas on the contrary there still remains a need for quality trials in cerebral palsy, multiple sclerosis to establish the efficacy of robotics in upper extremity rehabilitation.
Brain-computer interfaces, or BCIs, represent relatively recent advances in neurotechnology that allow computer systems to interact directly with human or animal brains. This technology is particularly promising for use in cases of spinal cord injury or paralysis. In these situations, patients may be able to use neural decoders that access part of their brain to operate a prosthetic limb or even to re-animate a paralyzed limb through functional electrical stimulation (FES).
Michael A. Schwemmer and colleagues, in a recent Nature Medicine article, detail their research on BCIs using deep neural network decoders with a participant with tetraplegia due to spinal cord injury. Their research focuses on addressing several key needs identified by end-users of BCI systems, namely: high accuracy, minimal daily setup, rapid response time, and multifunctionality—all of which are characteristics heavily influenced by a BCI’s particular neural decoding algorithm.
Schwemmer’s group describes several different approaches to training and testing three variations on neural network decoders (NN-BCI) in comparison with each other and a benchmark support vector machine (SVM) decoder. The four BCI decoder paradigms were developed and tested over the course of several years in association with a 27-year-old male participant with tetraplegia. The participant had a 96-channel microelectrode array implanted in the area of his left primary motor cortex corresponding to the hand and arm. Using intracortical data collected from 80 sessions over 865 days, the investigators trained and evaluated these BCI decoders. These sessions consisted of two 104-second blocks of a four-movement task: index extension, index flexion, wrist extension, and wrist flexion.
The initial neural network (NN) model was developed and calibrated using data from the first 40 sessions (80 blocks); it was not updated over the second half of the training/testing period, and is referred to here as the fixed neural network (fNN) model. From the fNN, two other neural network models were created: a supervised updating (sNN) model and an unsupervised updating (uNN) model. Both models used data from the first block of the second 40-session (updating/testing) period. The sNN model’s algorithm relies on explicit training labels, that is, known timing and type of movement, whereas the uNN model relies on undifferentiated or unknown direct input in relation to intended action of the limb. The second block of the second 40-session period was used for accuracy testing of all models—fNN, sNN, uNN, and SVM.
The purpose of using four separate models here was to test and demonstrate various aspects of the three neural network models in relation to each other and the benchmark SVM model. For instance, the supervised neural network (sNN) model was updated daily (during the first block of the second 40-session period) and compared directly with the daily-retrained SVM model. The fixed neural network (fNN) model was provided to demonstrate that a BCI could sustain accuracy for over a year with no updates.
The unsupervised neural network (uNN) was perhaps the most interesting comparator, as we shall see, because it attempted to combine the improved accuracy gained from daily updates but without the consequent daily setup time required by the sNN model. Accuracy was the key performance measure in all tests, defined here as a percentage of correctly predicted time-bins in the second block of the second 40 sessions; the criterion of greater than 90% accuracy was one of the four end-user requirements originally articulated at the outset of the study.
The sNN consistently outperformed the daily-retrained SVM: in 37 out of 40 sessions, its accuracy was > 90%, whereas the SVM only achieved > 90% accuracy in 12 sessions. The fNN also outperformed the SVM in 36 of 40 sessions; it achieved > 90% accuracy in 32 sessions. The fNN accuracy was, not surprisingly, lower than the accuracy of the sNN, and both fixed decoders, fNN and SVM, declined in accuracy over the course of the study period, in contrast to the daily-updated decoders.
Perhaps the most interesting finding of this research however, is the performance of the unsupervised neural network (uNN), which outperformed both fixed models in terms of accuracy, while also meeting the end-user requirement of minimal daily set-up. Where the sNN model required explicit daily training, the uNN incorporated data from general use in its update schema, which required no such daily set-up. In comparison with the fNN, a performance gap emerged over time, and the benefits of the uNN distinguished themselves. The uNN also outperformed the SVM in terms of response time, another key end-user requirement.
Another important aspect of this study with regard to NNs focused on transfer learning, whereby new movements can be added to the existing repertoire with minimal additional training and data. In this case, “hand open” and “hand close” were added to the previous four movements, and all decoders were rebuilt. Here too, unsupervised updating was used to build an unsupervised transfer neural network (utNN), which, after only one session of training oupterformed the SVM model.
Finally, the previous research—all of which was conducted in an “offline” setting—was applied, via the participant’s FES-controlled hand and forearm, to show that a transfer learning uNN trained on the original four-movement task could be used to quickly create a new decoder to control, in real time, an open hand and three grips (can, fork, and peg). In a test of the system, the participant was able to perform all three hand movement grip tasks, with no failures, in 45 attempts. Previously, he was only able to perform one grip task successfully.
In summarizing how the results of their study relate to the main end-user expectations previously described, the investigators cite the following achievements: “(i) using deep NNs to create robust neural decoders that sustain high fidelity BCI control for more than a year without retraining; (ii) introducing a new updating procedure that can improve performance using data obtained through regular system use; (iii) extension of functionality through transfer learning using minimal additional data; and (iv) introducing a decoding framework that simultaneously addresses these four competing aspects of BCI performance (accuracy, speed, longevity, and multifunctionality). In addition, we provide a clinical demonstration that a decoder calibrated using historical data of imagined hand movements with no feedback can be successfully used in real-time to control FES-evoked grasp function for object manipulation.”
Schwemmer and colleagues go on to offer a more in-depth discussion of their results amidst the broader landscape of BCI research, and offer commentary on some of the specific challenges and limitations of their experiment. While noting that the median response time for uNN decoders (0.9 s) is still faster than that of SVM decoders (1.1 s), they acknowledge that a target of 750 ms or less is probably closer to realistic end-user expectations.
Ultimately they conclude: “We have demonstrated that decoders based on NNs may be superior to other implementations because new functions can be easily added after the initial decoder calibration using transfer learning. Crucially, we show that this secondary update to add more movements requires a minimal amount of additional data.” And “insights gained from offline data and analyses can carry over to a realistic online BCI scenario with minimal additional data collection.”
More information: Michael A. Schwemmer et al. Meeting brain–computer interface user performance expectations using a deep neural network decoding framework, Nature Medicine(2018). DOI: 10.1038/s41591-018-0171-y
The EU FET Symbitron project gathered researchers from 5 European countries to build wearable exoskeletons to help people who have suffered a spinal cord injury to walk again. The next step is to prepare the robot to compete at the Cybathlon games in 2020 in Zurich.
One of human beings’ most interesting features is the interaction between the mind and the body, and hence the control that the brain exerts on the body and the continuous feedback received from it. Spinal cord injuries (SCI) interrupt the crucial bi-directional communication pathway between the brain and the rest of the body, and make it difficult or impossible for patients to walk.
At the moment, although scientific advances are being made, there is no way of regenerating and totally restoring a damaged spinal cord and the nerve pathways connected to it. Nonetheless, researchers in the field of assistive robotics are currently working to develop wearable devices that can compensate for lost motor functions. Over the past four years, scientists in the Symbitron project, supported by the EU FET programme, developed lower limb exoskeletons that people with SCI can use to walk again. The multidisciplinary team included mechanical, electronic and biomedical engineers, neurologists, psychologists and physical therapists.
Project researchers from 5 European countries (the Netherlands (University of Twente and Delft University of Technology), Italy (Fondazione Santa Lucia IRCCS), UK (Imperial College), Switzerland (EPFL) and Iceland (Össur), developed a versatile wearable robot adaptable for use by SCI patients with very different impairments. Their great ambition was to let patients walk autonomously, regain their mobility and independence, and overcome the psychological barriers created by their disability.
One of the main challenges to be faced was to overcome the traditional engineering design approach, which often focuses almost exclusively on technological issues and only partially takes into account the perspective and clinical needs of users. The Symbitron project put the patients at the center of the exoskeleton design paradigm, trying to tailor the technology around their body, their mind and the residual communication between them that is still possible. From the very beginning of the project, 13 patients with SCI, each one with unique clinical features related to specific spinal cord damage, were involved as part of the experimental team and considered as “test pilots” of the machine to be developed. Their precious feedback on performance and their experience of using the technology was successfully embedded in a user-centred optimisation loop, in which great attention was given to robotic adaptation and customization aspects, as these are key to ensuring that the human-machine interaction works as well as possible.
Form the hardware point of view, the exoskeletons were designed in an innovative modular format, making different robotic configurations possible: for example, to support the ankle or knee joints of patients who still have some ability to walk independently, or the entire legs of those with more severe SCI who cannot walk unaided. The control software was designed to be flexible to match. A biologically inspired control algorithm was developed to mirror muscular and reflex-like movements in the legs of the exoskeletons and to let the users control the machine and walk in a smooth, intuitive and natural way. Not only engineers and clinical experimenters, but also the “test pilot” patients, were actively involved in honing the software’s functions and its use to control the machines: their feedback was crucial.
The test pilots were involved throughout the project in several experiments to obtain neurophysiological information useful for the mechatronic design process, personal experiences needed to customize the behavior of the exoskeletons, and biomechanical data on human-robot performance to improve the hardware and software. A major project milestone was a “measurements marathon” organized at the University of Twente. Nine test pilots moved from the Italian clinical partner, Fondazione Santa Lucia IRCCS, to the Netherlands to take part to 5 full days of testing, including 11 different experiments (around 120 different tests), which involved 14 Symbitron researchers and 3 experimental setups.
The Symbitron project was successfully concluded in Rome with clinical approval of the modular exoskeleton it developed, demonstrating the possibility of improving the walking performance of the test pilots after a period of training performed in a clinical setting. The tests were proof of the feasibility of Symbitron’s unique approach. Moreover, a multi-factor psychological assessment showed that the users were not only highly motivated through the training but also very satisfied about the capacity of the exoskeleton to adapt to their personal walking and balance strategies. The Symbitron exoskeleton will be further developed in the years to come in order to compete in the Cybathlon games in 2020 in Zurich.
Introduction: A scoping review provides a means to synthesize and present a large body of literature on a broad topic, such as methods for various upper extremity activity-based therapy (ABT) interventions.
Objectives: To describe our scoping review protocol to evaluate peer-reviewed articles focused on ABT interventions for individuals with neurologically impaired upper extremities.
Methods: At Jefferson College of Health Professions and Sidney Kimmel Medical College at Jefferson, Philadelphia, the authors will follow this protocol to conduct a scoping review by establishing a research question and conducting a search of bibliographic databases to identify relevant studies. Using specific inclusion and exclusion criteria, abstracts will be screened and full-text articles will be reviewed for inclusion in charting, summarizing, and reporting results of appropriate studies.
Conclusion: This protocol will guide the scoping review process to develop a framework for establishing a noninvasive ABT intervention informed by evidence for individuals with neurologically impaired upper extremities.
The application of rehabilitation robots has grown during the last decade. While meta-analyses have shown beneficial effects of robotic interventions for some patient groups, the evidence is less in others. We established the Advanced Robotic Therapy Integrated Centers (ARTIC) network with the goal of advancing the science and clinical practice of rehabilitation robotics. The investigators hope to exploit variations in practice to learn about current clinical application and outcomes. The aim of this paper is to introduce the ARTIC network to the clinical and research community, present the initial data set and its characteristics and compare the outcome data collected so far with data from prior studies.
ARTIC is a pragmatic observational study of clinical care. The database includes patients with various neurological and gait deficits who used the driven gait orthosis Lokomat® as part of their treatment. Patient characteristics, diagnosis-specific information, and indicators of impairment severity are collected. Core clinical assessments include the 10-Meter Walk Test and the Goal Attainment Scaling. Data from each Lokomat® training session are automatically collected.
At time of analysis, the database contained data collected from 595 patients (cerebral palsy: n = 208; stroke: n = 129; spinal cord injury: n = 93; traumatic brain injury: n = 39; and various other diagnoses: n = 126). At onset, average walking speeds were slow. The training intensity increased from the first to the final therapy session and most patients achieved their goals.
The characteristics of the patients matched epidemiological data for the target populations. When patient characteristics differed from epidemiological data, this was mainly due to the selection criteria used to assess eligibility for Lokomat® training. While patients included in randomized controlled interventional trials have to fulfill many inclusion and exclusion criteria, the only selection criteria applying to patients in the ARTIC database are those required for use of the Lokomat®. We suggest that the ARTIC network offers an opportunity to investigate the clinical application and effectiveness of rehabilitation technologies for various diagnoses. Due to the standardization of assessments and the use of a common technology, this network could serve as a basis for researchers interested in specific interventional studies expanding beyond the Lokomat®.
The number of technological devices that therapists can utilize to treat people with neurological impairments has grown substantially during the last decade. Alongside this growth in clinical use, research involving robotic therapy has grown rapidly. A search in Pubmed with the terms “robot” OR “robotic*” AND “rehabilitation” revealed 2225 hits (March 2017) with research markedly increasing after 2010. Despite this increase in research activity and clinical use, the effectiveness of robot-assisted interventions in neurorehabilitation is still in debate. While in some patient populations, for example adults with stroke, meta-analyses have shown that robotic interventions for the lower and upper extremity can be beneficial [1, 2], current evidence is much less convincing in other patient groups, such as spinal cord injury (SCI), traumatic brain injury (TBI), multiple sclerosis (MS) and cerebral palsy (CP).
When comparing the effectiveness of robot-assisted gait training (RAGT) to conventional interventions of similar dosage in adult patients after SCI, it appears that neither intervention is superior [3, 4]. In other populations, such as MS, a small number of pilot studies have been conducted, and a review  concluded that the evidence for the effectiveness remained inconclusive. In adult patients with TBI, to our knowledge, there is only one randomized controlled trial that investigated the effectiveness of RAGT . While RAGT improved gait symmetry compared to manually assisted body-weight supported treadmill training, improvements in other gait parameters were not different between the interventions. In children with CP, the body of evidence is similarly small, as only two randomized trials were found [7, 8]. To the authors’ knowledge, there are no randomized controlled trials in children with other diagnoses. Studies comparing effectiveness between different patient groups are lacking.
One important factor leading to the lack of conclusive research is the relatively small number of available centers and participating patients and consequently the small statistical power of attempted studies. Multicenter collaborations are needed to achieve adequate number of participants. Several of the limitations in the evidence of the application of RAGT arise from patient selection criteria and use of different, poorly described and/or low-dosed training protocols. For example, when systematically reviewing the literature in children, we found no paper describing a training protocol on how to apply a robot for rehabilitation of gait . Most of the systematic reviews mentioned that it is extremely difficult to pool results from studies due to the large variability in treatment duration and frequency, contents of the training and inclusion criteria of the patients. For children with CP, an expert team was created to formulate goals, inclusion criteria, training parameters and recommendations on including RAGT in the clinical setting, to assist therapists who train children with CP with the Lokomat® (Hocoma AG, Volketswil, Switzerland) . Such information could be used as a first step in defining training protocols, but this information is missing for most other patient groups.
While randomized controlled trials are usually considered the “gold standard” in building solid evidence in the field of medicine, it is often difficult for rehabilitation specialists working in the clinical environment to interpret the findings with respect to the population of patients they treat on a daily basis. Randomized controlled trials require a specialized team, a controlled setting and a strict selection of patients according to well defined inclusion and exclusion criteria. These criteria often select individuals most likely to benefit based on specific parameters and lack of co-morbidities. These narrow criteria may impact the ecological validity, as results only apply to a minority of patients. This was recently investigated by Dörenkamp et al.  who reported that the majority of patients in primary care (40% at the age of 50 years and at least two-thirds of the octogenarian population ) simultaneously suffered from multiple medical problems. Further, improvements in function might be less comparable to results described in randomized controlled trials and the treatment regimens used may not be applicable to patients with multiple comorbidities.
To overcome these issues, we established the Advanced Robotic Therapy Integrated Centers (ARTIC) network to collect data from patients using RAGT in a wide variety of clinical settings. ARTIC hopes to develop guidelines for usage as well as to answer scientific questions concerning the use of RAGT. While the ARTIC network includes a general patient population, other research networks focus on a specific disorder or diagnostic group (see, for example [12, 13]). ARTIC focuses on a common technological intervention – currently the driven gait orthosis Lokomat® – and aims to gather evidence for the efficient and effective use of robotic therapy. Variation in practice among ARTIC members together with collection of common data and outcome measurements will enable the group to draw strong, generalizable conclusions. Further goals include establishing standardized treatment protocols and increasing medical and governmental acceptance of robotic therapy. The aims of this paper are to introduce the ARTIC network to the clinical and research community, present initial data on the characteristics of included patients and compare these to those known from existing epidemiological data and interventional studies.[…]
Fig. 1 Lokomat® system (of different generations) with (a) adult leg orthoses and (b) pediatric leg orthoses. Patients walk on a treadmill belt, are weight supported, and the exoskeleton device guides the legs through a physiological walking pattern
INTRODUCTION: Spasticity is associated with various diseases of the nervous system. Current treatments such as drug therapy, botulinum toxin injections, kinesitherapy, and physiotherapy are not sufficiently effective in a large number of patients. Transcranial magnetic stimulation (TMS) can be considered as an alternative method of treatment. The purpose of this article was to conduct a systematic review and meta-analysis of all available publications assessing the efficacy of repetitive TMS in treatment of spasticity.
EVIDENCE ACQUISITION: Search for articles was conducted in databases PubMed, Willey, and Google. Keywords included “TMS”, “spasticity”, “TMS and spasticity”, “non-invasive brain stimulation”, and “non-invasive spinal cord stimulation”. The difference in scores according to the Modified Ashworth Scale (MAS) for one joint before and after treatment was taken as the effect size.
EVIDENCE SYNTHESIS: We found 26 articles that examined the TMS efficacy in treatment of spasticity. Meta-analysis included 6 trials comprising 149 patients who underwent real stimulation or simulation. No statistically significant difference in the effect of real and simulated stimulation was found in stroke patients. In patients with spinal cord injury and spasticity, the mean effect size value and the 95% confidence interval were -0.80 and (-1.12, -0.49), respectively, in a group of real stimulation; in the case of simulated stimulation, these parameters were 0.15 and (-0.30, -0.00), respectively. Statistically significant differences between groups of real stimulation and simulation were demonstrated for using high-frequency repetitive TMS or iTBS mode for the M1 area of the spastic leg (P=0.0002).
CONCLUSIONS: According to the meta-analysis, the statistically significant effect of TMS in the form of reduced spasticity was demonstrated only for the developed due to lesions at the brain stem and spinal cord level. To clarify the amount of the antispasmodic effect of repetitive TMS at other lesion levels, in particular in patients with hemispheric stroke, further research is required.