Posts Tagged Upper limb rehabilitation

[ARTICLE] Brain–computer interface and assist-as-needed model for upper limb robotic arm – Full Text

Post-stroke paralysis, whereby subjects loose voluntary control over muscle actuation, is one of the main causes of disability. Repetitive physical therapy can reinstate lost motions and strengths through neuroplasticity. However, manually delivered therapies are becoming ineffective due to scarcity of therapists, subjectivity in the treatment, and lack of patient motivation. Robot-assisted physical therapy is being researched these days to impart an evidence-based systematic treatment. Recently, intelligent controllers and brain–computer interface are proposed for rehabilitation robots to encourage patient participation which is the key to quick recovery. In the present work, a brain–computer interface and assist-as-needed training paradigm have been proposed for an upper limb rehabilitation robot. The brain–computer interface system is implemented with the use of electroencephalography sensor; moreover, backdrivability in the actuator has been achieved with the use of assist-as-needed control approach, which allows subjects to move the robot actively using their limited motions and strengths. The robot only assists for the remaining course of trajectory which subjects are unable to perform themselves. The robot intervention point is obtained from the patient’s intent which is captured through brain–computer interface. Problems encountered during the practical implementation of brain–computer interface and achievement of backdrivability in the actuator have been discussed and resolved.

The recovery of upper limb motions and strengths in patients with damaged neuromuscular system via robotic rehabilitation devices is a promising way of enhancing existing treatments and their efficacies. Various reasons may cause limb dysfunctions, including stroke, spinal cord injuries, or even ligament rupture. According to the World Health Organization, about 15 million people globally suffer from Cerebro-Vascular Accidents (CVAs) each year and up to 65% of these need limb recovery procedures.1 Only in the last 15 years, the number of CVA or stroke patients is increased by 40%, which is the result of a more intense pace of living, deterioration of ecology, and increased aging population.2 Considering these statistics, development of new and efficient ways of rehabilitation is just as important as implementation of improved prevention strategies.

For the last 20 years, robotics-based therapy was steadily paving its way for becoming an essential practice in rehabilitation medicine.3,4 According to the systematic review of Kwakkel et al.5 on the upper limb recovery using robot-aided therapy, repetitive, meaningful, labor-intensive treatment programs implemented with robotic devices provide positive impact for the restoration of functional abilities in human limbs. In medical terminology, a device that provides support, and aligns or improves the function of movable limbs is known as orthosis, and robotic devices intended to provide such treatment are called robotic orthoses.6 Particularly, two key directions gained major attention in the medical engineering research: robot-assisted therapy and functional electrical simulation (FES) therapy. The FES therapy describes a technique that stimulates weakened or paralyzed muscles on a human limb by applying electric charges externally. The goal of FES therapy is to reactivate the neural connections between a muscle and human’s sensorimotor system to enable patients’ ability to control their limbs without assistance.7 In the study by Popovic and others, the functional electrical therapy (FET) was applied with the use of surface electrodes and it was used to stimulate arm fingers of patients, this therapy has demonstrated positive therapeutic effects.8 It was revealed that daily 30-min therapy for 1-month period allowed improvement in movement range, speed, and increased strength in muscles. There are also side effects of FES-based treatment such as pain and irritation on the affected area, autonomic dysreflexia, increased spasticity, broken bones, and mild electric shocks from faulty equipment. However, the robot-assisted rehabilitation is non-invasive and free from above risks, and it is preferred for the rehabilitation of stroke survivors.

The important advantage of robotic devices is that they can reduce the burden on health care workers who traditionally had to conduct labor-intensive training sessions for patients. Equipped with sensors, intelligent controllers, and haptic and visual interfaces, robotic orthosis can have a potential to put the recovery process to a new level by collecting relevant data about various health parameters (pulse rate, body temperature, etc.) and adjusting the training modes accordingly. Besides the positive impacts of robot-based rehabilitation, the reliability of robot-based assistance is still questionable and adversely it may worsen the recovery progress made before, and that depends on the type of assistance control robot employs.9 Assist-as-needed (AAN) control type has become one of the prominent strategies recently which has been recommended positively from clinical trials.10 In order to stabilize the system, AAN-based approach has become subject to be researched by scientists. In the work done by Wolbrecht, AAN control is obtained from the adaptive control by incorporating novel force to address and decrease the system’s parametric errors.11 There are also other works which propose AAN type of control for their systems;1214 however, there are no works which have incorporated both BCI (brain–computer interface)- and AAN-based control approach into the system.

Owing to the recent advances in biosensors, especially in their robustness and signal processing, robot controllers equipped with bio-sensing are able to achieve intelligence with less complex algorithms. One of the most recent applications of BCI is in the domain of orthoses.1517 Newer instances of orthoses combine latest advances in control theory and brain activity. Berlin Technical University in cooperation with Korean University created an exoskeleton to maneuver lower limbs. A feature of this work is the use of non-invasive electroencephalography (EEG). The study involved 11 healthy men aged 25 to 32 years.18 First upper limb exoskeleton controlled by BCI was proposed by AA Frolov et al.19 Authors concluded that BCI inclusion improves the movements of the paretic hand in post-stroke patients irrespective of severity and localization of the disease. In addition, it was shown that duration of the training also increases effectiveness of rehabilitation.

Based on the letters on the screen, it was possible to determine native language of the patient in the work done by Vasileva.20 In this work, non-invasive EEG had been used. However, it was noted that non-invasive devices have less accuracy than professional medical EEG equipment. To improve signal detection, Agapov et al.21 have developed advanced algorithm of processing visually evoked potentials. To visualize stimuli, “eSpeller” software was developed.

Motivated by the above-mentioned successes and advances, in the present work, possible use of BCI is investigated in the rehabilitation robots for the treatment of stroke survivors. The aim of this work is to develop EEG-based mechatronic system that can receive electrical brain signals, detect emotions and gestures of the patient, and intelligently control robotic arm. In addition, to ensure smooth and compliant movement of the rehabilitation robot and improve treatment efficacy, AAN control paradigm is also considered. This research used EEG package and a controller to develop BCI system and realize AAN-based control. Developed system can help patients to control robot with their thoughts and enhance their participation in the rehabilitation process. Methodology of the current work is explained in the “Methodology” section, and in the subsequent sections, results are discussed before drawing conclusions from this research work.

EEG sensor

In order to register the brain activity, 16 EEG electrodes distributed around the patient’s head have been used. To provide more information which is related to motor imaginary signals, the frequency characteristics were extracted from the data by converting them from the time domain to the frequency domain. Furthermore, to distinguish between movement intentions and rest positions, bandpass filter in the range of 5 to 40 Hz was used.22,23 Since EEG data set recording can be very large, the powerful surface Laplacian technique was applied to lower the risk of influence from the neighboring neurons on the crucial cerebral cortex neurons.24 Finally, only dominant frequency of 13 to 30 Hz, also known as beta wave frequency, was featured according to Gropper et al.25 This band distinction was benchmarker as a sensible area of resting brain activity.

Abiding by the previous works associated with EEG signal processing in Iáñez et al.26 and Hortal et al.,27 the feature selection was reduced to the group of 29 features, which later were used for the further classification and predictive model construction.

After receiving data using an EEG, algorithm needs to determine the desired effect for the user. Input data for this algorithm are EEG signals recorded during the demonstration of stimuli. In most of the currently existing studies on this subject, the problem of classifying signals is divided into three large subtasks:

  • Preprocessing the signal (in order to remove noise components);
  • Formation of a feature space;
  • Classification of objects in the constructed feature space.

It should be noted that the greatest influence on the final quality of the classification is made by the extent to which the task of forming the feature space was successfully accomplished. The general scheme of operation of BCI is depicted in Figure 1.


                        figure

Figure 1. Block diagram of BCI interface.

 

[…]

Continue —>  Brain–computer interface and assist-as-needed model for upper limb robotic arm – Akim Kapsalyamov, Shahid Hussain, Askhat Sharipov, Prashant Jamwal, 2019

                        figure

Figure 4. (a) ELA actuated upper limb rehabilitation robot, (b) upper limb rehabilitation robot in use, and (c) robotic orthosis in use with EEG sensor.

 

, , , , , , , ,

Leave a comment

[Abstract + References] Design and Development of a Robotic Platform Based on Virtual Reality Scenarios and Wearable Sensors for Upper Limb Rehabilitation and Visuomotor Coordination – Conference paper

Abstract

The work reintegration following shoulder biomechanical overload illness is a multidimensional process, especially for those tasks requiring strength, movement control and arm dexterity. Currently different robotic devices used for upper limb rehabilitation are available on the market, but these devices are not based on activities focused on the work reintegration. Furthermore, the rehabilitation programmes aimed to the work reintegration are insufficiently focused on the recovery of the necessary skills for the re-employment.

In this study the details of the design of an innovative robotic platform integrated with wearable sensors and virtual reality scenarios for upper limbs motor rehabilitation and visuomotor coordination is presented. The design of control strategy will also be introduced. The robotic platform is based on a robotic arm characterized by seven degrees of freedom and by an adaptive control, wearable sensorized insoles, virtual reality (VR) scenarios and the Leap Motion device to track the hand gestures during the rehabilitation training. Future works will address the application of deep learning techniques for the analysis of the acquired big amount of data in order to automatically adapt both the difficulty level of the VR serious games and amount of motor assistance provided by the robot.

References

  1. 1.
    MacEachen, E., et al.: Systematic review of the qualitative literature on return to work after injury. Scand. J. Work Environ. Health 32(4), 257–269 (2006)CrossRefGoogle Scholar
  2. 2.
    Franche, R.-L., Krause, N.: Readiness for return to work following injury or illness: conceptualizing the interpersonal impact of healthcare, workplace, and insurance factor. J. Occup. Rehabil. 12(4), 233–256 (2002)CrossRefGoogle Scholar
  3. 3.
    Hou, W.H., Chi, C.C., Lo, H.L.D., Kuo, K.N., Chuang, H.Y.: Vocational rehabilitation for enhancing return-to-work in workers with traumatic upper limb injuries (2013)Google Scholar
  4. 4.
    Shi, Q., Sinden, K., Macdermid, J.C., Walton, D., Grewal, R.: A systematic review of prognostic factors for return to work following work-related traumatic hand injury. J. Hand Ther. 27(1), 55–62 (2014)CrossRefGoogle Scholar
  5. 5.
    Fadyl, J., McPherson, K.: Return to work after injury: a review of evidence regarding expectations and injury perceptions, and their influence on outcome. J. Occup. Rehabil. 18(4), 362–374 (2008)CrossRefGoogle Scholar
  6. 6.
    Krebs, H.I.: Twenty + years of robotics for upper-extremity rehabilitation following a stroke. In: Rehabilitation Robotics (2018)CrossRefGoogle Scholar
  7. 7.
    Buongiorno, D., Sotgiu, E., Leonardis, D., Marcheschi, S., Solazzi, M., Frisoli, A.: WRES: a novel 3 DoF WRist exoskeleton with tendon-driven differential transmission for neuro-rehabilitation and teleoperation. IEEE Robot. Autom. Lett. 3(3), 2152–2159 (2018)CrossRefGoogle Scholar
  8. 8.
    Krebs, H.I., et al.: Robotic applications in neuromotor rehabilitation. Robotica 21(1), 3–11 (2003)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Lee, S.-S., Park, S.-A., Kwon, O.-Y., Song, J.-E., Son, K.-C.: Measuring range of motion and muscle activation of flower arrangement tasks and application for improving upper limb function. Korean J. Hortic. Sci. Technol. 30(4), 449–462 (2012)CrossRefGoogle Scholar
  10. 10.
    Spreeuwers, D., et al.: Work-related upper extremity disorders: one-year follow-up in an occupational diseases registry. Int. Arch. Occup. Environ. Health 84(7), 789–796 (2011)CrossRefGoogle Scholar
  11. 11.
    Mehrholz, J., Pohl, M., Platz, T., Kugler, J., Elsner, B.: Electromechanical and robot-assisted arm training for improving activities of daily living, arm function, and arm muscle strength after stroke (2018)Google Scholar
  12. 12.
    Lederer, V., Rivard, M., Mechakra-Tahiri, S.D.: Gender differences in personal and work-related determinants of return-to-work following long-term disability: a 5-year cohort study. J. Occup. Rehabil. 22(4), 522–531 (2012)CrossRefGoogle Scholar
  13. 13.
    Siciliano, B., Lorenzo, S., Villani, L., Orilo, G.: Robotics: Modelling, Planning and Control, 2nd edn. Springer, London (2010).  https://doi.org/10.1007/978-1-84628-642-1CrossRefGoogle Scholar
  14. 14.
    Balasubramanian, S., Melendez-Calderon, A., Roby-Brami, A., Burdet, E.: On the analysis of movement smoothness. J. Neuroeng. Rehabil. 12, 112 (2015).  https://doi.org/10.1186/s12984-015-0090-9CrossRefGoogle Scholar
  15. 15.
    Berger, D.J., d’Avella, A.: Effective force control by muscle synergies. Front. Comput. Neurosci. 8, 46 (2014).  https://doi.org/10.3389/fncom.2014.00046CrossRefGoogle Scholar
  16. 16.
    Holzbaur, K.R.S., Murray, W.M., Delp, S.L.: A model of the upper extremity for simulating musculoskeletal surgery and analyzing neuromuscular control. Ann. Biomed. Eng. 33(6), 829–840 (2005).  https://doi.org/10.1007/s10439-005-3320-7CrossRefGoogle Scholar
  17. 17.
    Delp, S.L., et al.: OpenSim: open-source software to create and analyze dynamic simulations of movement. IEEE Trans. Biomed. Eng. 54(11), 1940–1950 (2007)CrossRefGoogle Scholar
  18. 18.
    Buongiorno, D., et al.: Evaluation of a pose-shared synergy-based isometric model for hand force estimation: towards myocontrol. In: Biosystems and Biorobotics (2017)Google Scholar
  19. 19.
    Buongiorno, D., Barsotti, M., Barone, F., Bevilacqua, V., Frisoli, A.: A linear approach to optimize an EMG-driven neuromusculoskeletal model for movement intention detection in myo-control: a case study on shoulder and elbow joints. Front. Neurorobot. 12, 74 (2018)CrossRefGoogle Scholar

via Design and Development of a Robotic Platform Based on Virtual Reality Scenarios and Wearable Sensors for Upper Limb Rehabilitation and Visuomotor Coordination | SpringerLink

, , , , , , , , , ,

Leave a comment

[ARTICLE] Mobile Mechatronic/Robotic Orthotic Devices to Assist–Rehabilitate Neuromotor Impairments in the Upper Limb: A Systematic and Synthetic Review – Full Text

This paper overviews the state-of-the-art in upper limb robot-supported approaches, focusing on advancements in the related mechatronic devices for the patients’ rehabilitation and/or assistance. Dedicated to the technical, comprehensively methodological and global effectiveness and improvement in this inter-disciplinary field of research, it includes information beyond the therapy administrated in clinical settings-but with no diminished safety requirements. Our systematic review, based on PRISMA guidelines, searched articles published between January 2001 and November 2017 from the following databases: Cochrane, Medline/PubMed, PMC, Elsevier, PEDro, and ISI Web of Knowledge/Science. Then we have applied a new innovative PEDro-inspired technique to classify the relevant articles. The article focuses on the main indications, current technologies, categories of intervention and outcome assessment modalities. It includes also, in tabular form, the main characteristics of the most relevant mobile (wearable and/or portable) mechatronic/robotic orthoses/exoskeletons prototype devices used to assist-rehabilitate neuromotor impairments in the upper limb.

1. Introduction–General Perspective and Main Rationales

What differentiates human beings from animals is the superior psycho-cognitive activity, including the coordinated/complex, workable, actions of its highly correlated physical effecter: the upper limb, and especially the hand—as basis of our creative and modeler/draftsman kind interactions with the environment. This profound and subtle reality has been conceptualized during history by great thinkers, such as Aristotel (2005), Descartes, Newton and Kant (Lundborg, 2014).

Accordingly, finding solutions that address rehabilitation and/or functional assistance of neuromotor impairments at this level would have a remarkable positive impact: for the beneficiaries’ quality of life (Frisoli et al., 2016) and from a socio-economical perspective, as well. The latter corresponds to the temporary regain/re-insertion of the productive resources lost because of the disabilities in their upper limbs. Moreover, it is to be considered, within the general context/trend of offering a reliable alternative for prolonged hospitalizations, the need for top of the range assistive/rehabilitative orthotic mobile devices. These should be capable to provide safe and of continuity rehabilitation (Loureiro et al., 2011) and/or functional assistance for the above mentioned topography, too, of neuromotor deficits including in the patient’s daily life context. Such endeavors are often necessary on long term, mainly imposed, in the morbidity domain we approach, by the required duration of neuroplasticity to install/act (Muresanu et al., 2012Basteris et al., 2014Xiao et al., 2014Proietti et al., 2016Mazzoleni et al., 2017), to be (re)settled in adequate engrams for the function(s) aimed at restoring, and/or of peripheral nerves’ re-growth (Guyton and Hall, 2006).

The necessity for such devices that can operate without fatigue in both clinical settings, at home and in the community is growing high (Stewart et al., 2017). This is despite of the fact that people with upper limb pathology—who do not necessarily suffer from functional issues in the lower limbs—can commonly reach clinical units (in order to receive ambulatory rehabilitative specific procedures). Another aspect is that, at the moment, there is already a “shortage” of professionals handy to deliver domiciliary physiotherapy/rehabilitation and nursing, for persons with physical impairments. This is a worrying situation, especially as it is foreseen to become more and more frequent in the years to come (Maciejasz et al., 2014).

An important related development direction consists of consolidating their wearable profile. This practically entails—subsumed to a rightful beneficiary’s desire: “several hours” per day of working performance (Allotta et al., 2015)—availability for autonomous powered duty (as for easily/rapidly rechargeable facilities, too) and respectively comfortable bearing by the consumer in the daily life (Giberti et al., 2014), limitation of encumbrances, lightweight (Rocon et al., 2007Martinez et al., 2008Song et al., 20132014Chen et al., 2014Giberti et al., 2014Andrikopoulos et al., 2015Allotta et al., 2015Polygerinos et al., 2015Guo et al., 2016Nycz et al., 2016Alavi et al., 2017Stewart et al., 2017) and modularity (Lo et al., 2010Pearce et al., 2012Noveanu et al., 2013Xiao et al., 2014Nycz et al., 2016) and/or, in some cases, “reconfigurability” (Maciejasz et al., 2014).

Considering all the necessary technical assets for such advanced devices to be mobile (Kiguchi et al., 2008aLee, 2014Nycz et al., 2016), thereby available for individual more extended use, an additional, non-technical, but derivative and decisive condition is, as well, mandatory: their cost-effectiveness (Noveanu et al., 2013).

We consider it only appropriate to iterate here a summarized idea of a previous work of ours (Onose et al., 2016) that currently there is still no such thing as an optimal, fully functional assistive-rehabilitative device (in the common sense of the term). This regards mainly: don/doff issues (Nimawat and Jailiya, 2015)–for severely disabled potential beneficiaries–, psychological acceptance (of self image/esteem kind, referring to the ensemble look of the consumer: enough miniaturization and cosmetics– thus either reaching a satisfactory clothes-like aspect or even becoming as thin as to evolve to underwear dimensions), extended power autonomy, easy and fast set-up-for professionals (Dijkers et al., 1991). Another important feature for the customers/their kin is the appropriateness for long time duty in various real life situations. One should consider also the consistent related safety, producing very low/practically imperceptible noise when in service and truly affordable/cost effective.

 

Continue —->Frontiers | Mobile Mechatronic/Robotic Orthotic Devices to Assist–Rehabilitate Neuromotor Impairments in the Upper Limb: A Systematic and Synthetic Review | Neuroscience

, , , , , , , ,

Leave a comment

[Abstract] Peripheral plus central repetitive transcranial magnetic stimulation (rTMS) for upper limb motor rehabilitation in chronic stroke – A case report

Introduction/Background

Motor dysfunction of the hand and upper limb is a major cause of physical disability for patients with chronic stroke. Our aim was to investigate the effectiveness of a peripheral plus central repetitive transcranial magnetic stimulation (rTMS) treatment for upper limb motor rehabilitation in chronic stroke patients.

Material and method

We reported the case of a patient WLX, who had one ischemic stroke more than 3 years ago, and had underwent intermittent rehabilitation since then. He still had profound right upper limb paralysis and moderate spasm, accompanied with non-fluent aphasia when came to our department; and complained that his recovery had been rather slow for about two years. In addition to the custom rehabilitation, we applied a peripheral plus central rTMS paradigm to him, which included 3 sessions of peripheral magnetic stimulation to his paralyzed right forearm, followed by a session of high frequency rTMS to the bilateral sensorimotor cortex region. The total magnetic stimulation therapy lasted about 30 min a day, and was applied 5 days/week for 4 weeks.

Results

After 4 weeks’ treatment, the patient’s Fulg–Meyer upper limb assessment (FMA) score was obviously improved (from 27 to 37 points), and the spasm was largely relieved in his right hand and arm.

Conclusion

Peripheral plus central rTMS might be an effective treatment for motor dysfunction of chronic stroke patients.

via Peripheral plus central repetitive transcranial magnetic stimulation (rTMS) for upper limb motor rehabilitation in chronic stroke – A case report – ScienceDirect

, , , , , , , , ,

Leave a comment

[Case Report] Case report on the use of a functional electrical orthosis in rehabilitation of upper limb function in a chronic stroke patient – Full Text PDF

Abstract

Introduction. The increasing incidence of strokes and their occurrence in younger active people require the development of solutions that allow participation, despite the debilitating deficit that is not always solved by rehabilitation. The present report shows
such a potential solution.
Objective. In this presentation we will show the effects of using a functional electric orthosis, the high number of repetitions and daily electrostimulation in a young stroke patient with motor deficit in the upper limb, the difficulties encountered in attempting to
use orthosis, the results and the course of its recovery over the years.
Materials and Methods. The present report shows the evolution of a 31-year-old female patient with hemiplegia, resulting from a hemorrhagic stroke, from the moment of surgery to the moment of purchasing a functional electrical orthosis and a few months
later, highlighting a 3-week period when the training method focused on performing a large number of repetitions of a single exercise helped by the orthosis – 3 weekly physical therapy sessions, with a duration of one hour and 15 minutes, plus 2 electrostimulation sessions lasting 20 minutes each and 100 elbow extension, daily, 6 times a week. The patient was evaluated and filmed at the beginning and end of the 3 week period. The patient’s consent was obtained for the use of the data and images presented.
Results. Invalidating motor deficiency and problems specific to the use of upper limb functional electrostimulation in patients with stroke sequelae (flexion synergy, exaggeration of reflex response, wrist position during stimulation, etc.) made it impossible to use orthosis in functional activities within ADL although it allowed the achievement of a single task. Evaluation on the FuglMayer assessment does not show any quantifiable progress, although it is possible to have slightly improved the control of the
shoulder and elbow and increased the speed of task execution.
Conclusions. The use of functional orthoses of this type may be useful in patients who still have a significant functional rest in the shoulder, elbow and hand, and where the orthosis can produce an effective grasp. However for some patients, perhaps those who
would have been desirable to benefit most from this treatment, the benefit of using this orthosis is minimal.[…]

Full Text PDF

, , , , , , , , ,

Leave a comment

[Abstract] Efficacy and safety of NABOTA in post-stroke upper limb spasticity: A phase 3 multicenter, double-blinded, randomized controlled trial

Highlights

A phase III clinical trial was performed for a novel botulinum toxin A, NABOTA, on post-stroke upper limb spasticity.

NABOTA demonstrated non-inferiority on efficacy and safety compared to onabotulinum toxin A (Botox).

NABOTA may serve as an alternative for treatment of post-stroke upper limb spasticity using botulinum toxin A.

Abstract

Botulinum toxin A is widely used in the clinics to reduce spasticity and improve upper limb function for post-stroke patients. Efficacy and safety of a new botulinum toxin type A, NABOTA (DWP450) in post-stroke upper limb spasticity was evaluated in comparison with Botox (onabotulinum toxin A). A total of 197 patients with post-stroke upper limb spasticity were included in this study and randomly assigned to NABOTA group (n = 99) or Botox group (n = 98). Wrist flexors with modified Ashworth Scale (MAS) grade 2 or greater, and elbow flexors, thumb flexors and finger flexors with MAS 1 or greater were injected with either drug. The primary outcome was the change of wrist flexor MAS between baseline and 4 weeks post-injection. MAS of each injected muscle, Disability Assessment Scale (DAS), and Caregiver Burden Scale were also assessed at baseline and 4, 8, and 12 weeks after the injection. Global Assessment Scale (GAS) was evaluated on the last visit at 12 weeks. The change of MAS for wrist flexor between baseline and 4 weeks post-injection was − 1.44 ± 0.72 in the NABOTA group and − 1.46 ± 0.77 in the Botox group. The difference of change between both groups was 0.0129 (95% confidence interval − 0.2062–0.2319), within the non-inferiority margin of 0.45. Both groups showed significant improvements regarding MAS of all injected muscles, DAS, and Caregiver Burden Scale at all follow-up periods. There were no significant differences in all secondary outcome measures between the two groups. NABOTA demonstrated non-inferior efficacy and safety for improving upper limb spasticity in stroke patients compared to Botox.

 

via Efficacy and safety of NABOTA in post-stroke upper limb spasticity: A phase 3 multicenter, double-blinded, randomized controlled trial – ScienceDirect

, , , , , , , , , , ,

Leave a comment

[Abstract] Hybrid impedance control of a robot manipulator for wrist and forearm rehabilitation: Performance analysis and clinical results

Abstract

Therapeutic exercises play an important role in the physical therapy and the rehabilitation. The exercises that can be assisted by a physiotherapist are increasingly being performed by the rehabilitation robots partially or fully due to their various merits. This study aims to develop a complete rehabilitation system, which consists of a rehabilitation robot, an HMI and a hybrid impedance controller that can model all the therapeutic exercises for an upper limb rehabilitation. The 3-DOF upper limb rehabilitation robot is able to perform the movements of flexion–extension and ulnar–radial deviation for the wrist, and the movement of pronation–supination for the forearm. The experimental studies were conducted with healthy subjects and patients. First, the experiments were done with the healthy subjects to prove the control performance of the robotic system. The results showed that the hybrid impedance controlled robot can perform the therapeutic exercises very successfully. Then, the experimental studies were carried out with the real patients in a clinical environment. At the end of the treatment process, remarkable improvements were observed in terms of the limb force in all of the patients.

 

via Hybrid impedance control of a robot manipulator for wrist and forearm rehabilitation: Performance analysis and clinical results

, , , , , , , ,

Leave a comment

[ARTICLE] Adaptive hybrid robotic system for rehabilitation of reaching movement after a brain injury: a usability study – Full Text

Abstract

Background

Brain injury survivors often present upper-limb motor impairment affecting the execution of functional activities such as reaching. A currently active research line seeking to maximize upper-limb motor recovery after a brain injury, deals with the combined use of functional electrical stimulation (FES) and mechanical supporting devices, in what has been previously termed hybrid robotic systems. This study evaluates from the technical and clinical perspectives the usability of an integrated hybrid robotic system for the rehabilitation of upper-limb reaching movements after a brain lesion affecting the motor function.

Methods

The presented system is comprised of four main components. The hybrid assistance is given by a passive exoskeleton to support the arm weight against gravity and a functional electrical stimulation device to assist the execution of the reaching task. The feedback error learning (FEL) controller was implemented to adjust the intensity of the electrical stimuli delivered on target muscles according to the performance of the users. This control strategy is based on a proportional-integral-derivative feedback controller and an artificial neural network as the feedforward controller. Two experiments were carried out in this evaluation. First, the technical viability and the performance of the implemented FEL controller was evaluated in healthy subjects (N = 12). Second, a small cohort of patients with a brain injury (N = 4) participated in two experimental session to evaluate the system performance. Also, the overall satisfaction and emotional response of the users after they used the system was assessed.

Results

In the experiment with healthy subjects, a significant reduction of the tracking error was found during the execution of reaching movements. In the experiment with patients, a decreasing trend of the error trajectory was found together with an increasing trend in the task performance as the movement was repeated. Brain injury patients expressed a great acceptance in using the system as a rehabilitation tool.

Conclusions

The study demonstrates the technical feasibility of using the hybrid robotic system for reaching rehabilitation. Patients’ reports on the received intervention reveal a great satisfaction and acceptance of the hybrid robotic system.

Background

Upper limb hemiparesis is one of the most common consequences after a brain injury accident [1]. This motor impairment has an adverse impact on the quality of life of survivors since it hinders the execution of activities of daily living. From the rehabilitation perspective, it is widely accepted that high-intensity and repetitive task-specific practice is the most effective principle to promote motor recovery after a brain injury [12]. However, traditional rehabilitation treatment offers a dose of movement repetition that is in most cases insufficient to facilitate neural reorganization [3]. In response to these current clinical shortcomings, there is a clear interest in alternative rehabilitation methods that improve the arm motor functionality of brain injury survivors.

Hybrid robotic systems for motor rehabilitation are a promising approach that combine the advantages of robotic support or assistive devices and functional electrical stimulation (FES) technologies to overcome their individual limitations and to offer more robust rehabilitation interventions [4]. Despite the potential benefits of using hybrid robotic systems for arm rehabilitation, a recent published review shows that only a few hybrid systems presented in the literature were tested with stroke patients [4]. Possible reasons could be the difficulties arising from the integration of both assistive technologies or the lack of integrated platforms that can be easily setup and used.

End-effector robotic devices combined with FES represent the most typical hybrid systems used to train reaching tasks under constrained conditions [567]. With these systems, patients’ forearms are typically restricted to the horizontal plane to isolate the training of the elbow extension movement. The main advantage of this approach is the simplicity of the setup, with only 1 Degree of Freedom (DoF). However, to maximize the treatment’s outcomes and achieve functional improvement it is necessary to train actions with higher range of motion (> 1 DoF) and functional connotations [89]. Yet, the complexity for driving a successful movement execution in such scenarios requires the implementation of a robust and reliable FES controller.

The appropriate design and implementation of FES controllers play a key role to achieve stable and robust motion control in hybrid robotic systems. The control strategy must be able to drive all the necessary joints to realize the desired movement, and compensate any disturbances to the motion, i.e. muscle fatigue onset as well as the strong nonlinear and time-varying response of the musculoskeletal system to FES [1011]. Consequently, open-loop and simple feedback controllers (e.g. proportional-integral-derivative -PID-) are not robust enough to cope with these disturbances [812]. Meadmore et al. presented a more suitable hybrid robotic system for functional rehabilitation scenarios [13]. They implemented a model-based iterative learning controller (ILC) that adjusts the FES intensity based on the tracking error of the previously executed movement (see [1314] for a detail description of the system). This iterative adjustment allows compensating for disturbances caused by FES. Although this approach addresses some of the issues regarding motion control with FES, it requires a detailed mathematical description of the musculoskeletal system to work properly. In this context, unmodeled dynamics and the linearization of the model can reduce the robustness of the controller performance. Also, the identification of the model’s parameters is complex and time consuming, which limits its applicability in clinical settings [1112].

The Feedback Error Learning (FEL) scheme proposed by Kawato [15] can be considered as an alternative to ILC. This scheme was developed to describe how the central nervous system acquires an internal model of the body to improve the motor control. Under this scheme, the motor control command of a feedback controller is used to train a feedforward controller to learn implicitly the inverse dynamics of the controlled system on-line (i.e. the arm). Complementary, this on-line learning procedure also allows the controller to adapt and compensate for disturbances. In contrast with the ILC, the main advantage of this strategy is that the controller does not require an explicit model of the controlled system to work correctly and that it can directly learn the non-linear characteristic of the controlled system. Therefore, using the FEL control strategy to control a hybrid robotic system can simplify the setup of the system considerably, which makes easier to deploy it in clinical settings as well as personalize its response according to each patient’s musculoskeletal characteristics and movement capabilities. The FEL has been used previously to control the wrist [16] and the lower limb [17] motion with FES in healthy subjects; but it has not been tested on brain injury patients. In a previous pilot study, we partially showed the suitability of the FEL scheme in hybrid robotic systems for reaching rehabilitation with healthy subjects [18]. However, a rigorous and robust analysis has not been presented neither this concept has not been tested with motor impaired patients.

The main objective of this study is to verify the usability of a fully integrated hybrid robotic system based on an FEL scheme for rehabilitation of reaching movement in brain injury patients. To attain such objective two-step experimentation was followed. The first part consists of demonstrating the technical viability and learning capability of the developed FEL controller to drive the execution of a coordinated shoulder-elbow joint movement. The second part consists of testing the usability of the platform with brain injury patients in a more realistic rehabilitation scenario. For this purpose, we assessed the patients’ performance and overall satisfaction and emotional response after using the system.

Methods

In this section, we present the hybrid robotic system for the rehabilitation of reaching movement in patients with a brain injury. The system focuses on aiding users to move their paretic arm towards specific distal directions in the space. During the execution of the reaching task, the FEL controller adjusts the intensities of the electrical stimuli delivered to target muscles in order to aid the subjects in tracking accurately the target paths.

Description of the hybrid rehabilitation platform for reaching rehabilitation

Figure 1 shows the general overview of the developed platform. This rehabilitation platform is composed of four main components: the hybrid assistive device (upper limb exoskeleton + FES device); the high-level controller (HLC); the visual feedback and; the user interface. […]

Fig. 1 a General overview of the presented hybrid robotic platform for reaching rehabilitation. bVisual feedback provided to the users. The green ball represents the actual arm position, the blue cross is the reference trajectory, the initial and final position are represented by the gray ball and red square respectively. c Interface for system configuration

Source: Adaptive hybrid robotic system for rehabilitation of reaching movement after a brain injury: a usability study | Journal of NeuroEngineering and Rehabilitation | Full Text

, , , ,

Leave a comment

[ARTICLE] An Evaluation of the Design and Usability of a Novel Robotic Bilateral Arm Rehabilitation Device for Patients with Stroke – Full Text

Introduction: Robot-assisted therapy for upper limb rehabilitation is an emerging research topic and its design process must integrate engineering, neurological pathophysiology, and clinical needs.

Purpose of the study: This study developed/evaluated the usefulness of a novel rehabilitation device, the MirrorPath, designed for the upper limb rehabilitation of patients with hemiplegic stroke.

Methods: The process follows Tseng’s methodology for innovative product design and development, namely two stages, device development and usability assessment. During the development process, the design was guided by patients’ rehabilitation needs as defined by patients and their therapists. The design applied synchronic movement of the bilateral upper limbs, an approach that is compatible with the bilateral movement therapy and proprioceptive neuromuscular facilitation theories. MirrorPath consists of a robotic device that guides upper limb movement linked to a control module containing software controlling the robotic movement.

Results: Five healthy subjects were recruited in the pretest, and 4 patients, 4 caregivers, and 4 therapists were recruited in the formal test for usability. All recruited subjects were allocated to the test group, completed the evaluation, and their data were all analyzed. The total system usability scale score obtained from the patients, caregivers, and therapists was 71.8 ± 11.9, indicating a high level of usability and product acceptance.

Discussion and conclusion: Following a standard development process, we could yield a design that meets clinical needs. This low-cost device provides a feasible platform for carrying out robot-assisted bilateral movement therapy of patients with hemiplegic stroke.

Clinical Trial Registration: identifier NCT02698605.

Introduction

The World Health Organization (WHO) has reported that stroke is the third leading cause of death in developed countries and involves approximately 15 million stoke events annually. One-third of stroke patients die and a further one-third of events results in permanent disability. Depending on the location of the brain insult, stroke can lead to a wide range of functional impairments (Mackay et al., 2004); these include language, cognition, sensation, and motor functions. Motor impairment impacts the patient’s ability to perform activities of daily living. For the majority of patients, recovery of motor function involving an upper limb is slower than that of lower limb (Feys et al., 1998). Indeed, most activities of daily living rely the functioning of the upper limb, thus emphasizing the need for effective upper limb rehabilitation.

With an attempt to enhance the effectiveness of upper limb rehabilitation among stroke patients, a series of rehabilitation techniques have been developed and refined in recent decades; these include task-oriented motor training, constraint-induced movement therapy, mirror therapy, and bilateral movement training. Each of these methods has a number of theoretical advocates and each has been shown to be effective clinically. For instance, bilateral movement therapy, which involves coordinated movement of the bilateral upper limbs, has been shown to enhance upper limb recovery and coordination between the hands. Stoykov et al. (2009) found that bilateral arm training is more effective than unilateral training when restoring proximal upper limb function because it seems to improve the functional linkages between the bilateral hemispheres.

Even after receiving a full course of conventional rehabilitation, 60% of stroke patients still have difficulties when using their affected upper limb (Kwakkel et al., 1999). As a result, it has become the upmost importance to develop novel rehabilitation strategies that are able to help patients reach a higher level of recovery. One such approach is robot-assisted rehabilitation, which incorporates robotic technologies into the rehabilitation processes. Several well-known robot-assisted movement therapies for the upper limb has been implemented clinically, including MIT-Manus (Krebs et al., 1998), Bi-Manu-Track (Hesse et al., 2003), BATRAC (Cauraugh et al., 2010), and MIME (Burgar et al., 2000), each of which follows different movement therapy theories. Regarding the body parts that are mainly involved in therapy, Bi-Manu-Track focuses on the bilateral forearms and wrists, while BATRAC and MIME focus on the shoulder and elbow of the affected limb. Regarding the movement dimension, BATRAC involves movement in one-dimension, while MIME allows three-dimensional movement. In fact, the higher the degrees of freedom adopted during the movement therapy, the more complex is the design of the robotic device. As a result, it has become important to come up with a feasible design that fulfills the patient’s rehabilitation needs while avoiding the high costs that can be associated with instrument acquirement and maintenance. Furthermore, the effectiveness of the system needs to be comparable to that provided by conventional therapies so that a motivation to pursue this therapeutic option can be established (Kwakkel et al., 2008; Lo et al., 2010).

As an approach to the development of mechanical rehabilitation devices for hemiplegic upper limbs, Timmermans et al. (2009) proposed that three design domains are required; these were the therapy techniques used, the motivation of the patient, and resulting performance rewards. An online survey of physical therapists, 233 in total, indicated that a preferred upper limb robotic device needs to accommodate different hand movements, to be able to be used while in a seated position, to be able to provide the user with feedback, to focus on the restoration of activities of daily living, to able to be used at home, to have adjustable resistance levels and to cost less than US$6,000 (Lu et al., 2011).

In terms of usability, the interaction between the user and the machine tends to be overlooked during the development stage. Although a variety of upper limb rehabilitation machines have been proposed, only a few have been commercialized. This low market acceptance can be attributed to the high cost of these devices, safety concerns, and poor usability (Lee et al., 2005). To this end, the aim of this study was to design a bilateral upper limb rehabilitation device called MirrorPath for the rehabilitation of stroke patients that follows the theories of bilateral movement therapy and proprioceptive neuromuscular facilitation (PNF). These two theories were initially developed by Knott and Kabat and have been shown to have a positive effect on the range of active and passive motions needed by stroke patients (Sharman et al., 2006). Our device will guide the patient’s upper limbs, each of which moves along a diagonal motion path on the horizontal plane. The position and velocity of motion of the bilateral limbs are perfectly mirrored across the midline on the table. Finally, usability testing was conducted on the completed prototype.

Continue —>  Frontiers | An Evaluation of the Design and Usability of a Novel Robotic Bilateral Arm Rehabilitation Device for Patients with Stroke | Frontiers in Neurorobotics

Figure 2. (A) A patient performed bilateral diagonal movements using the device; (B) due to weakness of right upper limb, the patient’s grip was assisted with an elastic bandage, and the patient’s elbow was support by a sling; (C) the application scenario.

, , , , , , , , ,

Leave a comment

[ARTICLE] Compensating the effects of FES-induced muscle fatigue by rehabilitation robotics during arm weight support – Full Text

Abstract

Motor functions can be hindered in consequence to a stroke or a spinal cord injury. This often results in partial paralyses of the upper limb. The effectiveness of rehabilitation therapy can be improved by the use of rehabilitation robotics and Functional Electrical Stimulation (FES). We consider a hybrid arm weight support combining both.

In order to compensate the effect of FES-induced muscle fatigue, we introduce a method to substitute the decreasing level of FES support by cable-driven robotics. We evaluated the approach in a trial with one healthy subject performing repetitive arm lifting. The controller automatically adapted the support and thus no increase in user generated volitional effort was observed when FES induced muscle fatigue occured.

Continue —> Compensating the effects of FES-induced muscle fatigue by rehabilitation robotics during arm weight support : Current Directions in Biomedical Engineering

, , , , , , , , ,

1 Comment

%d bloggers like this: