Published: 31 March 2016
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(Journal of Neurologic Physical Therapy, January, 2020)
A new clinical practice guideline (CPG) supported by APTA and developed by the APTA Academy of Neurologic Physical Therapy concludes that when it comes to working with individuals who experienced an acute-onset central nervous system (CNS) injury 6 months ago or more, aerobic walking training and virtual reality (VR) treadmill training are the interventions most strongly tied to improvements in walking distance and speed. Other interventions such as strength training, circuit training, and cycling training also may be considered, authors write, but providers should avoid robotic-assisted walking training, body-weight supported treadmill training, and sitting/standing balance that doesn’t employ augmented visual inputs.
The final recommendations in the CPG are the result of an extensive process that began with a scan of nearly 4,000 research abstracts and subsequent full-text review of 234 articles, further narrowed to 111 randomized controlled trials (RCTs), all focused on interventions related to CNS injuries, with outcome data that included measures of walking distance and speed. CPG panelists evaluated the data and developed recommendations, which were informed by data on patient preferences and submitted for expert and stakeholder review.
Development of the CPG was supported through an APTA-sponsored program that assists APTA sections — in the case, the Academy of Neurologic Physical Therapy — in the development stages such as drafting, appraisal, planning, and external review (for more detail on the program, visit APTA’s CPG Development webpage).
Why it matters
Authors note that “the implementation of evidence-based interventions in the field of rehabilitation has been a challenge,” and they believe that the new CPG offers a real opportunity for clinicians to “integrate available research into their practice patterns.” Further, they believe that the CPG has arrived at an important moment in the evolution of health care, with its greater emphasis on evidence for the cost-effectiveness and outcomes of various interventions.
More from the study
The CPG also offers tips for clinicians to implement its recommendations, including acquiring equipment to help providers monitor vital signs, implementing “automatic prompts in electronic medical records that will facilitate obtaining orders to attempt higher-intensity training strategies,” providing training sessions for clinicians, establishing organizational policies to promote use and documentation of the recommended interventions, and simply keeping a few copies of the study on hand for easy reference.
Keep in mind …
Authors acknowledged that the CPG has a few limitations. While the review of RCTs only is a strength, they write, some of those studies involved small sample sizes, and many lacked details on intervention dosage. Additionally, the CPG does not fully address the potential costs associated with its recommendations — specifically VR — which could impact a clinic’s ability to implement a particular intervention. Authors also acknowledge that walking speed and distance are not the only important outcomes related to mobility among individuals with CNS injury, and that other factors such as dynamic stability while walking, peak walking capacity, and community mobility may be incorporated in an assessment of walking function.
High-dosage rehabilitation therapy enhances neuroplasticity and motor recovery after neurologic injuries such as stroke and spinal cord injury. The optimal exercise dosage necessary to promote upper extremity (UE) recovery is unknown. However, occupational and physical therapy sessions are currently orders of magnitude too low to optimally drive recovery. Taking therapy outside of the clinic and into the living environment using sensing and computer technologies is attractive because it could result in a more cost efficient and effective way to extend therapy dosage. This dissertation developed innovative wearable sensing algorithms and a novel robotic system to enhance hand rehabilitation. We used these technologies to provide on-demand exercise in the living environment in ways not previously achieved, as well as to gain new insights into UE use and recovery after neurologic injuries.
Currently, the standard-of-practice for wearable sensing of UE movement after stroke is bimanual wrist accelerometry. While this approach has been validated as a way to monitor amount of UE activity, and has been shown to be correlated with clinical assessments, it is unclear what new information can be obtained with it. We developed two new kinematic metrics of movement quality obtainable from bimanual wrist accelerometry. Using data from stroke survivors, we applied principal component analysis to show that these metrics encode unique information compared to that typically carried by conventional clinical assessments. We presented these results in a new graphical format that facilitates the identification of limb use asymmetries.
Wrist accelerometry has the limitation that it cannot isolate functional use of the hand. Previously, we had developed a sensing system, the Manumeter, that quantifies finger movement by sensing magnetic field changes induced by movement of a ring worn on the finger, using a magnetometer array worn at the wrist. We developed, optimized, and validated a calibration-free algorithm, the “HAND” algorithm, for real-time counting of isolated, functional hand movements with the Manumeter. Using data from a robotic wrist simulator, unimpaired volunteers and stroke survivors, we showed that HAND counted movements with ~85% accuracy, missing mainly smaller, slower movements. We also showed that HAND counts correlated strongly with clinical assessments of hand function, indicating validity across a range of hand impairment levels.
To date, there have been few attempts to increase hand use and recovery of individuals with a stroke by providing real-time feedback from wearable sensors. We used HAND and the Manumeter to perform a first-of-its-kind randomized controlled trial of the effect of real-time hand movement feedback on hand use and recovery after chronic stroke. We found that real-time feedback on hand movement was ineffective in increasing hand use intensity and improving hand function. We also showed for the first time the non-linear relationship between hand capacity, measured in the laboratory, and actual hand use, measured at-home. Even people with a moderate level of clinical hand function exhibit very low hand use at home.
Finally, the challenge of improving hand function for people with moderate to severe injuries highlights the need for novel approaches to rehabilitation. One emerging technique is regenerative rehabilitation, in which regenerative therapies, such as stem cell engraftment, are coupled with intensive rehabilitation. In collaboration with the Department of Veteran Affairs Gordon Mansfield Spinal Cord Injury Translational Collaborative Consortium, we developed a robot for promoting on-demand, hand rehabilitation in a non-human primate model of hemiparetic spinal cord injury that is being used to synergize hand rehabilitation with novel regenerative therapies. Using an innovative bimanual manipulation paradigm, we show that subjects engaged with the device at a similar rate before and after injury across a range of hand impairment severity. We also demonstrate that we could shape relative use of the arm and increase the number of exercise repetitions per reward by changing parameters of the robot. We then evaluated how the peak grip force that the subjects applied to the robot decreased after SCI, demonstrating that it can serve as a potential marker of recovery.
These developments provide a foundation for future work in technologies for therapeutic movement rehabilitation in the living environment by establishing: 1) new metrics of upper extremity movement quality; 2) a validated algorithm for achieving a “pedometer for the hand” using wearable magnetometry; 3) a negative clinical trial result on the therapeutic effect of real-time hand feedback after stroke, which begs the question of what can be improved in future trials; 4) the nonlinear relationship between hand movement ability and at-home use, supporting the concept of learned non-use; and 5) the first example of robotic regenerative rehabilitation.
Summary: Experts raise awareness of neurosexuality challenges faced by patients with neurodisabilities, including members of the LGBTQIA+ community, and provide guidance for healthcare providers and caregivers.
For people with brain disorders, whether from injury or disease, rehabilitation is a complex process. Neurosexuality is an emerging area of study and practice that focuses on the relationships between brain and sexual function in individuals with and without neurological disorders. Experts on the subject, reporting in NeuroRehabilitation, discuss how sexuality can affect neurorehabilitation in patients suffering from a range of conditions, from stroke and spinal cord injuries to sexual behavior in patients with dementia.
Research addressing the relationship between sexuality and the brain has a long history in neurological and behavioral sciences. This increased awareness has led to a better understanding within the scientific community regarding the importance of sexuality as a health outcome to promote the quality of life of individuals with neurodisabilities.
“This thematic issue of NeuroRehabilitation emphasizes that neurosexuality care should be driven by a transdisciplinary approach to appraise the evidence base of the potential negative consequences of different neurodisabilities on sexuality and to build upon sound treatment strategies to address these complexities,” explained guest editors Alexander Moreno, PhD, Caron Gan, RN, MScN, RP, AAMFT, and Nathan D. Zasler, MD.
An important contribution to this issue advocates for changing the culture of neurodisability through language and sensitivity of providers in order to create a safe place for lesbian, gay, bisexual, transgender, queer, intersex, asexual, and people with other sexual orientations and forms of gender expression (LGBTQIA+). “The particular needs of LGBTQIA+ individuals living with a neurological disorder are neglected in clinical practice and research. The invisibility of LGBTQIA+ individuals with neurological disorders reflects the historical exclusion of marginalized identities and creates disparities of access to healthcare,” explained Alexander Moreno, PhD, Faculty of Human Sciences, Department of Sexology, Université du Québec à Montréal (UQÀM) and the Center for Interdisciplinary Research in Rehabilitation of Greater Montreal, Ari Laoch, MS, Virginia Commonwealth University, and Nathan D. Zasler, MD, Concussion Care Centre of Virginia, Ltd. and Tree of Life Services, Inc. (VA).
The invisibility of LGBTQIA+ individuals with neurological disorders translates into diminished quality of care or inappropriate care, lack of recognition of all family configurations, exclusion of family caregivers, and violations of human rights (e.g., the right to be treated with dignity). Shedding light on the diversity of individuals with neurological disorders has the potential to improve healthcare by helping rehabilitation professionals to be sensitive to the particular needs of LGBTQIA+ individuals. In addition, the results of this study help promote the inclusion of sexual and gender diversity in the curricula of future practitioners and delineate future directions for research. Most importantly, the current study provides concrete clinical recommendations aiming to orient healthcare professionals wanting to improve their practice.
The authors surveyed the literature concerning neurological disorders affecting LGBTQIA+ individuals. They found that the relative neglect of LGBTQIA+ individuals with neurological disorders in clinical practice and research is striking. Healthcare professionals working with individuals with neurological disorders have the responsibility to create safer spaces in their clinical practice, including the use of inclusive language, the modification of admission forms to reflect diverse realities, the inclusion of sexual orientation and gender identity in their institutional policies, and participate in continuing education to challenge misconceptions, stereotypes, and negative attitudes. The authors provide 20 recommendations to guide clinicians, researchers, and policy professionals about the care of the LGBTQIA+ community.
Moreno, Laoch, and Zasler emphasized that “being part of a positive change in the rehabilitation of LGBTQIA+ people with neurodisabilities is part of our obligation as healthcare providers who are self-reflective, critical, and willing to improve the quality of the services provided in an ethical framework.”
Additional contributions to the issue cover a variety of important topics.
The authors reviewed over 2000 studies and found that literature about sexuality in children and adolescents with ABI has mainly addressed physical issues (e.g., precocious puberty), with positive sexual health needing further development in topics such as body image, sexual orientation, and social competence including flirting, dating, and romance.
Sexual health after traumatic brain injury (TBI) in younger and older adults Sexual problems were more likely for older (average mid-40s) patients with TBI than for younger (average 30s) patients. Older patients showed lower sexual desire and suffered more from anxiety and depression. Younger patients did not exhibit these symptoms to the same degree, suggesting that clinicians should be aware of age differences when treating their patients.
A literature review of post-stroke sexual functioning describes how various dysfunctions are related to stroke location, laterality, and physical and psychological changes. Three programs are presented to address post-stroke rehabilitation.
For patients with MS, assessment and treatment of sexual dysfunctions are described, including sexual assessment tools especially for MS. The authors also explore related topics including relationships, fertility, pregnancy, and parenting issues. They emphasize that, like other neurological disorders, there is a need for more collaboration among providers in addressing sexual concerns in MS.
Surveys of both patients with ALS, also known as Lou Gehrig’s disease, and ALS care providers revealed uncomfortable feelings when the subject of sexuality was raised. The authors call for more education among ALS specialists in sexuality and a policy change that guarantees the inclusion of sexuality in their guidelines.
SCI can impact sexual response, male infertility and its treatments, as well as pregnancy issues. The authors emphasize the importance of providing education and specific sexual recommendations based on the individual’s remaining sexual potential, and to include their partners, when available. They also present basic and advanced treatments for sexual dysfunctions and discuss other challenges in the management of sexual dysfunction of individuals with SCI.
Obtaining consent to study individuals with cognitive impairment is a controversial topic. In the environment of a residential care facility, the authors propose a multi-step approach involving authorized representatives (e.g., family caregivers), professional caregivers working in the facility, a pre-consent phase, a consent presentation phase, and a final consent before data collection. Their reflections and suggestions illuminate the ethical challenges involved in the study of sexuality and intimacy in individuals with severe cognitive impairment.
In summary, the guest editors write, “We hope that this thematic issue provides an impetus for rehabilitation and other health professionals, students in the health sciences, and researchers to develop their competence and awareness of the importance of sexual neurorehabilitation in persons with neurodisabilities.”
In the United States, there are approximately 17,000 new cases of spinal cord injury (SCI) every year. Of these, 20 percent result in complete paraplegia (paralysis of the legs and lower half of body) and over 13 percent result in tetraplegia (paralysis of all four limbs).
But SCI is not the only reason that people experience this type of disability. Stroke, multiple sclerosis, cerebral palsy, and a range of other neurological disorders can all lead to paralysis. In fact, a recent survey estimated that in the U.S., almost 5.4 million people live with paralysis, with stroke being the leading cause of this disability.
Now, researchers from the National Centre of Competence in Research Robotics at École Polytechnique Fédérale de Lausanne (EPFL), and at the Lausanne University Hospital in Switzerland, have come up with a groundbreaking technology that may help these patients to regain their locomotor skills.
The scientists came up with an algorithm that helps a robotic harness to facilitate the movements of the patients, thus enabling them to move naturally.
The new research has been published in the journal Science Translational Medicine, and the first author of the study is Jean-Baptiste Mignardot.
Current rehabilitation technologies for people with motor disabilities as a result of SCI or stroke involve walking on a treadmill, with the upper torso being supported by an apparatus. But existing technologies are either too rigid or do not allow the patients to move naturally in all directions.
As the authors of the new study explain, the challenge of locomotor rehabilitation resides in helping the nervous system to “relearn” the right movements. This is difficult due to the loss of muscle mass in the patients, as well as to the neurological wiring that has “forgotten” correct posture.
In order to overcome these obstacles and promote natural walking, Mignardot and colleagues designed an algorithm that coordinates with a robotic rehabilitation harness. The team tested the algorithm in more than 30 patients. The “smart walk assist” markedly and immediately improved the patients’ locomotor abilities.
This mobile harness, which is attached to the ceiling, enables patients to walk. This video shows how it works:
Additionally, after only 1 hour of training with the harness and algorithm, the “unsupported walking ability” of five of the patients improved considerably. By contrast, 1 hour on a conventional treadmill did not improve gait.
The researchers developed the so-called gravity-assist algorithm after carefully monitoring the movements of the patients and considering parameters such as “leg movement, length of stride, and muscle activity.”
As the authors explain, based on these measurements, the algorithm identifies the forces that must be applied to the upper half of the body in order to allow for natural walking.
The smart walk assist is an innovative body-weight support system because it manages to resist the force of gravity and push the patient back and forth, to the left and to the right, or in more of these directions at once, which recreates a natural gait and movement that the patients need in their day to day lives.
Grégoire Courtine, a neuroscientist at EPFL and the Lausanne University Hospital, comments on the significance of the findings, saying, “I expect that this platform will play a critical role in the rehabilitation of walking for people with neurological disorders.”
“This is a smart, discreet, and efficient assistance that will aid rehabilitation of many persons with neurological disorders.”
Prof. Jocelyne Bloch, Department of Neurosurgery, Lausanne University Hospital
For these people, neuroprosthetic devices can offer some much-needed hope.
Brain-computer interfaces (BCI) usually involve electrodes – placed on the human skull, on the brain’s surface, or in the brain’s tissue – that monitor and measure the brain activity that occurs when the brain “thinks” a thought. The pattern of this brain activity is then “translated” into a code, or algorithm, which is “fed” into a computer. The computer, in turn, transforms the code into commands that produce movement.
Neuroprosthetics are not just useful for people who cannot move their arms and legs; they also help those with sensory disabilities. The World Health Organization (WHO) estimate that approximately 360 million people across the globe have a disabling form of hearing loss, while another 39 million people are blind.
For some of these people, neuroprosthetics such as cochlear implants and bionic eyes have given them back their senses and, in some cases, they have enabled them to hear or see for the very first time.
Here, we review five of the most significant developments in neuroprosthetic technology, looking at how they work, why they are helpful, and how some of them will develop in the future.
Probably the “oldest” neuroprosthetic device out there, cochlear implants (or ear implants) have been around for a few decades and are the epitome of successful neuroprosthetics.
The U.S. Food and Drug Administration (FDA) approved cochlear implants as early as 1980, and by 2012, almost 60,000 U.S. individuals had had the implant. Worldwide, more than 320,000 people have had the device implanted.
A cochlear implant works by bypassing the damaged parts of the ear and stimulating the auditory nerve with signals obtained using electrodes. The signals relayed through the auditory nerve to the brain are perceived as sounds, although hearing through an ear implant is quite different from regular hearing.
Although imperfect, cochlear implants allow users to distinguish speech in person or over the phone, with the media abound with emotional accounts of people who were able to hear themselves for the first time using this sensory neuroprosthetic device.
Here, you can watch a video of a 29-year-old woman who hears herself for the first time using a cochlear implant:
The first artificial retina – called the Argus II – is made entirely from electrodes implanted in the eye and was approved by the FDA in February 2013. In much the same way as the cochlear implant, this neuroprosthetic bypasses the damaged part of the retina and transmits signals, captured by an attached camera, to the brain.
This is done by transforming the images into light and dark pixels that get turned into electrical signals. The electrical signals are then sent to the electrodes, which, in turn, send the signal to the brain’s optic nerve.
While Argus II does not restore vision completely, it does enable patients with retinitis pigmentosa – a condition that damages the eye’s photoreceptors – to distinguish contours and shapes, which, many patients report, makes a significant difference in their lives.
Retinitis pigmentosa is a neurodegenerative disease that affects around 100,000 people in the U.S. Since its approval, more than 200 patients with retinitis pigmentosa have had the Argus II implant, and the company that designed it is currently working to make color detection possible as well as improve the resolution of the device.
Almost 350,000 people in the U.S. are estimated to live with SCI, and 45 percent of those who had an SCI since 2010 are considered tetraplegic – that is, paralyzed from the neck down.
Bill Kochevar had electrodes surgically fitted into his brain. After training the BCI to “learn” the brain activity that matched the movements he thought about, this activity was turned into electrical pulses that were then transmitted back to the electrodes in his brain.
In much the same way that the cochlear and visual implants bypass the damaged area, so too does this BCI area avoid the “short circuit” between the brain and the patient’s muscles created by SCI.
With the help of this neuroprosthetic, the patient was able to successfully drink and feed himself. “It was amazing,” Kochevar says, “because I thought about moving my arm and it did.” Kochevar was the first patient in the world to test the neuroprosthetic device, which is currently only available for research purposes.
You can learn more about this neuroprosthetic from the video below:
However, this is not where SCI neuroprosthetics stop. The Courtine Lab – which is led by neuroscientist Gregoire Courtine in Lausanne, Switzerland – is tirelessly working to help injured people to regain control of their legs. Their research efforts with rats have enabled paralyzed rodents to walk, achieved by using electrical signals and making them stimulate nerves in the severed spinal cord.
“We believe that this technology could one day significantly improve the quality of life of people confronted with neurological disorders,” says Silvestro Micera, co-author of the experiment and neuroengineer at Courtine Labs.
Recently, Prof. Courtine has also led an international team of researchers to successfully create voluntary leg movement in rhesus monkeys. This was the first time that a neuroprosthetic was used to enable walking in nonhuman primates.
However, “it may take several years before all the components of this intervention can be tested in people,” Prof. Courtine says.
Silvestro Micera has also led other projects on neuroprosthetics, among which is the arm that “feels.” In 2014, MNT reportedon the first artificial hand that was enhanced with sensors.
Researchers measured the tension in the tendons of the artificial hand that control grasping movements and turned it into electric current. In turn, using an algorithm, this was translated into impulses that were then sent to the nerves in the arm, producing a sense of touch.
Since then, the prosthetic arm that “feels” has been improved even more. Researchers from the University of Pittsburgh and the University of Pittsburgh Medical Center, both in Pennsylvania, tested the BCI on a single patient with quadriplegia: Nathan Copeland.
The scientists implanted a sheath of microelectrodes below the surface of Copeland’s brain – namely, in his primary somatosensory cortex – and connected them to a prosthetic arm that was fitted with sensors. This enabled the patient to feel sensations of touch, which felt, to him, as though they belonged to his own paralyzed hand.
While blindfolded, Copeland was able to identify which finger on his prosthetic arm was being touched. The sensations he perceived varied in intensity and were felt as differing in pressure.
We have seen that brain-controlled prosthetics can restore patients’ sense of touch, hearing, sight, and movement, but could we build prosthetics for the brain itself?
Researchers from the Australian National University (ANU) in Canberra managed to artificially grow brain cells and create functional brain circuits, paving the way for neuroprosthetics for the brain.
By applying nanowire geometry to a semiconductor wafer, Dr. Vini Gautam, of ANU’s Research School of Engineering, and colleagues came up with a scaffolding that allows brain cells to grow and connect synaptically.
Project group leader Dr. Vincent Daria, from the John Curtin School of Medical Research in Australia, explains the success of their research:
“We were able to make predictive connections between the neurons and demonstrated them to be functional with neurons firing synchronously. This work could open up a new research model that builds up a stronger connection between materials nanotechnology with neuroscience.”
Neuroprosthetics for the brain might one day help patients who have experienced a stroke or who live with neurodegenerative diseases to recover neurologically.
Every year in the U.S., almost 800,000 people have had a stroke, and more than 130,000 people die from it. Neurodegenerative diseases are also widespread, with 5 million U.S. adults estimated to live with Alzheimer’s disease, 1 million to have Parkinson’s, and 400,000 to experience multiple sclerosis.
Live To Roll – This is my personal knowledge and experience about having sex after a SCI as well as how to best achieve ejaculation during sex and masturbation.
To date, rehabilitation robotics has come a long way effectively aiding the rehabilitation process of the patients suffering from paraplegia or hemiplegia due to spinal cord injury (SCI) or stroke respectively, through partial or even full functional recovery of the affected limb. The increased therapeutic outcome primarily results from a combination of increased patient independence and as well as reduced physical burden on the therapist. Especially for the case of gait rehabilitation following SCI or stroke, the rehab robots have the potential to significantly increase the independence of the patient during the rehabilitation process without the patient’s safety being compromised. An intensive gait-oriented rehabilitation therapy is often effective irrespective of the type of rehabilitation paradigm. However, eventually overground gait training, in comparison with body-weight supported treadmill training (BWSTT), has the potential of higher therapeutic outcome due its associated biomechanics being very close to that of the natural gait. Recognizing the apparent superiority of the overground gait training paradigms, a through literature survey on all the major overground robotic gait rehabilitation approaches was carried out and is presented in this paper. The survey includes an in-depth comparative study amongst these robotic approaches in terms of gait rehabilitation efficacy.
Published: 31 March 2016
Clinical scores for evaluating walking skills with lower limb exoskeletons are often based on a single variable, such as distance walked or speed, even in cases where a host of features are measured. We investigated how to combine multiple features such that the resulting score has high discriminatory power, in particular with few patients. A new score is introduced that allows quantifying the walking ability of patients with spinal cord injury when using a powered exoskeleton.
Four spinal cord injury patients were trained to walk over ground with the ReWalk™ exoskeleton. Body accelerations during use of the device were recorded by a wearable accelerometer and 4 features to evaluate walking skills were computed. The new score is the Gaussian naïve Bayes surprise, which evaluates patients relative to the features’ distribution measured in 7 expert users of the ReWalk™. We compared our score based on all the features with a standard outcome measure, which is based on number of steps only.
All 4 patients improved over the course of training, as their scores trended towards the expert users’ scores. The combined score (Gaussian naïve surprise) was considerably more discriminative than the one using only walked distance (steps). At the end of training, 3 out of 4 patients were significantly different from the experts, according to the combined score (p < .001, Wilcoxon Signed-Rank Test). In contrast, all but one patient were scored as experts when number of steps was the only feature.
Integrating multiple features could provide a more robust metric to measure patients’ skills while they learn to walk with a robotic exoskeleton. Testing this approach with other features and more subjects remains as future work.
Clinical scores of walking ability are crucial in many areas of physical rehabilitation to assess the efficacy of a therapeutic intervention or an assistive device, as well as to discriminate the ability between different patients [1, 2]. One domain of interest is evaluating functional ambulation in individuals who suffered a spinal cord injury (SCI). Even though many outcome measures target the SCI population [3, 4], currently there exist no specific measures targeting the ability of a patient to use a lower limb robotic exoskeleton to walk overground and achieve functional ambulation.
Lower limb exoskeletons are bilateral powered orthoses designed to provide assistance for sit-to-stand and for walking and, in some cases, to assist lower extremity function in individuals with incomplete or complete SCI [5–8]. Currently, several exoskeletons are transitioning from purely research and rehabilitation devices to personal mobility systems that individuals with SCI could use to walk inside their home and in their communities [9, 10]. A paradigmatic case is the ReWalk™, which has been approved by the Food and Drug Administration to be sold to individuals with SCI as a take-home personal mobility device.
Quantitative clinical assessment of exoskeletons is fundamental to evaluate their safety and effectiveness when used by individuals with disabilities. Specifically, individuals with complete SCI, who aim at taking an exoskeleton home as a personal mobility device, require an intensive training protocol to become independent users. Such training is typically delivered in a clinical setting and therefore clinicians need a robust metric to evaluate if a patient has reached a level of ability and expertise to independently use the device at home and in the community. Obtaining a robust index of the patients’ walking skills with an exoskeleton could also be used to inform health insurance companies about the actual improvements in functional mobility for potential reimbursement. This point is crucial as the cost of these devices is extremely high and therefore any support funding has to be justified.
The primary clinical outcome measures currently used to assess functional ambulation with exoskeletons are the 6-Minute-Walk-Test (6MWT) and the Ten-Meter-Walk-Test (10mWT) [11, 12]. These two tests measure, respectively, the distance walked in six minutes and the time to walk over a distance of 10 m, while walking at a constant speed. Despite being validated in spinal cord injury populations , it is questionable whether these measures are sufficient to fully evaluate a patient skill and the device efficiency. Indeed, other studies have measured additional features to characterize walking skills with robotic exoskeletons.
Specifically, amongst the features quantified there are: the kinematics of the hip, knee and ankle joints in patients trained to use the ReWalk™ , as recorded via a motion capture system; the exertion level based on the heart rate normalized to the walking speed (i.e. physiological cost index)  and the oxygen uptake [16, 17]. Other metrics used include the variation in vertical and lateral amplitude of the head motion , ground reaction forces analysis  and the ability to maintain eye contact to assess cognitive effort . Even when multiple features were measured, each study reports the values of each feature individually to characterize functional ambulation with exoskeletons. Therefore it is unclear how each feature contributes to the overall expertise of a subject. Furthermore, some of the captured features require complex and expensive lab equipment, commonly seen only in large hospitals and university settings.
In the current study, we propose to combine multiple features of walking performance by estimating their probability distribution over a set of expert users who have been previously trained extensively to use the exoskeleton. New participants are then scored based on how well their features fit the experts’ probability distribution. Building on this principle, we define a new score to quantify walking ability with exoskeletons: the Gaussian Naïve Bayes surprise. The term surprise is derived from information theory and represents the amount of unexpected information provided by an event . We apply our score to quantify the walking skills of four individuals with complete SCI, as they are trained to use the ReWalk™ exoskeleton. Four features are computed from the trunk accelerations, which are recorded using a commercial wearable accelerometer while subjects perform a 6MWT with the exoskeleton. We estimate the parameters of the features probability distribution from seven expert subjects (1 SCI and 6 able-bodied) that received extensive prior training with the device, and compute the Gaussian naïve Bayes surprise of the four SCI participants with respect to the experts. The score based on all four features is compared with one based only on number of steps (an equivalent of distance walked), in terms of the separation between experts and patients that is yielded by the two indices.
Recent neural science research suggests that a robotic device can be an effective tool to deliver the repetitive movement training that is needed to trigger neuroplasticity in the brain following neurologic injuries such as stroke and spinal cord injury (SCI).
In such scenario, adaptive control of the robotic device to provide assistance as needed along the intended motion trajectory with exact amount of force intensity, though complex, is a more effective approach. A critic-actor based reinforcement learning neural network (RLNN) control method is explored to provide adaptive control during post-stroke fine hand motion rehabilitation training.
The effectiveness of the method is verified through computer simulation and implementation on a hand rehabilitation robotic device.
Results suggest that the control system can fulfil the assist-as-needed (AAN) control with high performance and reliability. The method demonstrates potential to encourage active participation of the patient in the rehabilitation process and to improve the efficiency of the process.