Posts Tagged robot-assisted

[Abstract] Robot-Assisted Arm Training in Chronic Stroke: Addition of Transition-to-Task Practice

Background. Robot-assisted therapy provides high-intensity arm rehabilitation that can significantly reduce stroke-related upper extremity (UE) deficits. Motor improvement has been shown at the joints trained, but generalization to real-world function has not been profound.

Objective. To investigate the efficacy of robot-assisted therapy combined with therapist-assisted task training versus robot-assisted therapy alone on motor outcomes and use in participants with moderate to severe chronic stroke-related arm disability.

Methods. This was a single-blind randomized controlled trial of two 12-week robot-assisted interventions; 45 participants were stratified by Fugl-Meyer (FMA) impairment (mean 21 ± 1.36) to 60 minutes of robot therapy (RT; n = 22) or 45 minutes of RT combined with 15 minutes therapist-assisted transition-to-task training (TTT; n = 23). The primary outcome was the mean FMA change at week 12 using a linear mixed-model analysis. A subanalysis included the Wolf Motor Function Test (WMFT) and Stroke Impact Scale (SIS), with significance P<.05.

Results. There was no significant 12-week difference in FMA change between groups, and mean FMA gains were 2.87 ± 0.70 and 4.81 ± 0.68 for RT and TTT, respectively. TTT had greater 12-week secondary outcome improvements in the log WMFT (−0.52 ± 0.06 vs −0.18 ± 0.06; P = .01) and SIS hand (20.52 ± 2.94 vs 8.27 ± 3.03; P = .03).

Conclusion. Chronic UE motor deficits are responsive to intensive robot-assisted therapy of 45 or 60 minutes per session duration. The replacement of part of the robotic training with nonrobotic tasks did not reduce treatment effect and may benefit stroke-affected hand use and motor task performance.

 

via Robot-Assisted Arm Training in Chronic Stroke: Addition of Transition-to-Task Practice – Susan S. Conroy, George F. Wittenberg, Hermano I. Krebs, Min Zhan, Christopher T. Bever, Jill Whitall,

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[ARTICLE] Effectiveness of Robot-Assisted Upper Limb Training on Spasticity, Function and Muscle Activity in Chronic Stroke Patients Treated With Botulinum Toxin: A Randomized Single-Blinded Controlled Trial – Full Text

Background: The combined use of Robot-assisted UL training and Botulinum toxin (BoNT) appear to be a promising therapeutic synergism to improve UL function in chronic stroke patients.

Objective: To evaluate the effects of Robot-assisted UL training on UL spasticity, function, muscle strength and the electromyographic UL muscles activity in chronic stroke patients treated with Botulinum toxin.

Methods: This single-blind, randomized, controlled trial involved 32 chronic stroke outpatients with UL spastic hemiparesis. The experimental group (n = 16) received robot-assisted UL training and BoNT treatment. The control group (n = 16) received conventional treatment combined with BoNT treatment. Training protocols lasted for 5 weeks (45 min/session, two sessions/week). Before and after rehabilitation, a blinded rater evaluated patients. The primary outcome was the Modified Ashworth Scale (MAS). Secondary outcomes were the Fugl-Meyer Assessment Scale (FMA) and the Medical Research Council Scale (MRC). The electromyographic activity of 5 UL muscles during the “hand-to-mouth” task was explored only in the experimental group and 14 healthy age-matched controls using a surface Electromyography (EMGs).

Results: No significant between-group differences on the MAS and FMA were measured. The experimental group reported significantly greater improvements on UL muscle strength (p = 0.004; Cohen’s d = 0.49), shoulder abduction (p = 0.039; Cohen’s d = 0.42), external rotation (p = 0.019; Cohen’s d = 0.72), and elbow flexion (p = 0.043; Cohen’s d = 1.15) than the control group. Preliminary observation of muscular activity showed a different enhancement of the biceps brachii activation after the robot-assisted training.

Conclusions: Robot-assisted training is as effective as conventional training on muscle tone reduction when combined with Botulinum toxin in chronic stroke patients with UL spasticity. However, only the robot-assisted UL training contributed to improving muscle strength. The single-group analysis and the qualitative inspection of sEMG data performed in the experimental group showed improvement in the agonist muscles activity during the hand-to-mouth task.

Introduction

Upper limb (UL) sensorimotor impairments are one of the major determinants of long-term disability in stroke survivors (1). Several disturbances are the manifestation of UL impairments after stroke (i.e., muscle weakness, changes in muscle tone, joint disturbances, impaired motor control). However, spasticity and weakness are the primary reason for rehabilitative intervention in the chronic stages (13). Historically, spasticity refers to a velocity-dependent increase in tonic stretch reflexes with exaggerated tendon jerks resulting from hyperexcitability of the stretch reflex (4) while weakness is the loss of the ability to generate the normal amount of force.

From 7 to 38% of post-stroke patients complain of UL spasticity in the first year (5). The pathophysiology of spasticity is complicated, and new knowledge has progressively challenged this definition. Processes involving central and peripheral mechanisms contribute to the spastic movement disorder resulting in abnormal regulation of tonic stretch reflex and increased muscle resistance of the passively stretched muscle and deficits in agonist and antagonist coactivation (67). The resulting immobilization of the muscle at a fixed length for a prolonged time induces secondary biomechanical and viscoelastic properties changes in muscles and soft tissues, and pain (811). These peripheral mechanisms, in turn, leads to further stiffness, and viscoelastic muscle changes (28). Whether the muscular properties changes may be adaptive and secondary to paresis are uncertain. However, the management of UL spasticity should combine treatment of both the neurogenic and peripheral components of spasticity (910).

UL weakness after stroke is prevalent in both acute and chronic phases of recovery (3). It is a determinant of UL function in ADLs and other negative consequences such as bone mineral content (3), atrophy and altered muscle pattern of activation. Literature supports UL strengthening training effectiveness for all levels of impairment and in all stages of recovery (3). However, a small number of trials have been performed in chronic subgroup patients, and there is still controversy in including this procedure in UL rehabilitation (3).

Botulinum toxin (BoNT) injection in carefully selected muscles is a valuable treatment for spastic muscles in stroke patients improving deficits in agonist and antagonist coactivation, facilitating agonist recruitment and increasing active range of motion (681214). However, improvements in UL activity or performance is modest (13). With a view of improving UL function after stroke, moderate to high-quality evidence support combining BoNT treatment with other rehabilitation procedures (1915). Specifically, the integration of robotics in the UL rehabilitation holds promise for developing high-intensity, repetitive, task-specific, interactive treatment of upper limb (15). The combined use of these procedures to compensate for their limitations has been studied in only one pilot RCT reporting positive results in UL function (Fugl-Meyer UL Assessment scale) and muscular activation pattern (16). With the limits of the small sample, the results support the value of combining high-intensity UL training by robotics and BoNT treatment in patients with UL spastic paresis.

Clinical scales are currently used to assess the rehabilitation treatment effects, but these outcome measures may suffer from some drawbacks that can be overcome by instrumental assessment as subjectivity, limited sensitivity, and the lack of information on the underlying training effects on motor control (17). Instrumental assessment, such as surface electromyography (sEMG) during a functional task execution allows assessing abnormal activation of spastic muscles and deficits of voluntary movements in patients with stroke.

Moreover, the hand-to-mouth task is representative of Activities of Daily Life (ADL) such as eating and drinking. Kinematic analysis of the hand-to-mouth task has been widely used to assess UL functions in individuals affected by neurological diseases showing adequate to more than adequate test-retest reliability in healthy subjects (1819). The task involves flexing the elbow a slightly flexing the shoulder against gravity, and it is considered to be a paradigmatic functional task for the assessment of spasticity and strength deficits on the elbow muscles (1720). Although sEMG has been reported to be a useful assessment procedure to detect muscle activity improvement after rehabilitation, limited results have been reported (1621).

The primary aim of this study was to explore the therapeutic synergisms of combined robot-assisted upper limb training and BoNT treatment on upper limb spasticity. The secondary aim was to evaluate the treatment effects on UL function, muscle strength, and the electromyographic activity of UL muscles during a functional task.

The combined treatment would contribute to decrease UL spasticity and improve function through a combination of training effects between BoNT neurolysis and the robotic treatment. A reduction of muscle tone would parallel improvement in muscle strength ought to the high-intensity, repetitive and task-specific robotic training. Since spasticity is associated with abnormal activation of shortening muscles and deficits in voluntary movement of the UL, the sEMG assessment would target these impairments (281115).

Materials and Methods

Trial Design

A single-blind RCT with two parallel group is reported. The primary endpoint was the changes in UL spasticity while the secondary endpoints were changes in UL function, muscle strength and the electromyographic activity of UL muscles during a functional task. The study was conducted according to the tenets of the Declaration of Helsinki, the guidelines for Good Clinical Practice, and the Consolidated Standards of Reporting Trials (CONSORT), approved by the local Ethics Committee “Nucleo ricerca clinica–Research and Biostatistic Support Unit” (prog n.2366), and registered at clinical trial (NCT03590314).

Patients

Chronic post-stroke patients with upper-limb spasticity referred to the Neurorehabilitation Unit (AOUI Verona) and the Physical Medicine and Rehabilitation Section, “OORR” Hospital (University of Foggia) were assessed for eligibility.

Inclusion criteria were: age > 18 years, diagnosis of ischemic or hemorrhagic first-ever stroke as documented by a computerized tomography scan or magnetic resonance imaging, at least 6 months since stroke, Modified Ashworth Scale (MAS) score (shoulder and elbow) ≤ 3 and ≥1+ (22), BoNT injection within the previous 12 weeks of at least one of muscles of the affected upper limb, Mini-Mental State Examination (MMSE) score ≥24 (23) and Trunk Control Test score = 100/100 (24).

Exclusion criteria were: any rehabilitation intervention in the 3 months before recruitment, bilateral cerebrovascular lesion, severe neuropsychologic impairment (global aphasia, severe attention deficit or neglect), joint orthopedic disorders.

All participants were informed regarding the experimental nature of the study. Informed consent was obtained from all subjects. The local ethics committee approved the study.

Interventions

Each patient underwent a BoNT injection in the paretic limb. The dose of BoNT injected into the target muscle was based on the severity of spasticity in each case. Different commercial formulations of BoNT were used according to the pharmaceutical portfolio contracts of our Hospitals (Onabotulinumtoxin A, Abobotulinumtoxin A, and Incobotulinumtoxin A). The dose, volume and number of injection sites were set accordingly. A Logiq ® Book XP portable ultrasound system (GE Healthcare; Chalfont St. Giles, UK) was used to inject BoNT into the target muscle.

Before the start of the study authors designed the experimental (EG) and the control group (CG) protocols. Two physiotherapists, one for each group, carried out the rehabilitation procedures. Patients of both groups received ten individual sessions (45 min/session, two sessions/week, five consecutive weeks). Treatments were performed in the rehabilitative gym of the G. B. Rossi University Hospital Neurological Rehabilitation Unit, or “OORR” Hospital.

Robot-Assisted UL Training

The Robot-assisted UL Training group was treated using the electromechanical device Armotion (Reha Technology, Olten, Switzerland). It is an end-effector device that allows goal-directed arm movements in a bi-dimensional space with visual feedback. It offers different training modalities such as passive, active, passive-active, perturbative, and assistive modes. The robot can move, drive or oppose the patient’s movement and allows creating a personalized treatment, varying parameters such as some repetitions, execution speed, resistance degree of motion. The exercises available from the software are supported by games that facilitate the functional use of the paretic arm (25). The robot is equipped with a control system called “impedance control” that modulates the robot movements for adapting to the motor behavior of the patient’s upper limb. The joints involved in the exercises were the shoulder and the elbow, is the wrist fixed to the device.

The Robot-assisted UL Training consisted of passive mobilization and stretching exercises for affected UL (10 min) followed by robot-assisted exercises (35 min). Four types of exercises contained within the Armotion software and amount of repetitions were selected as follows: (i) “Collect the coins” (45–75 coins/10 min), (ii) “Drive the car” (15–25 laps/10 min), (iii) “Wash the dishes” (40–60 repetitions/10 min), and (iv) “Burst the balloons” (100–150 balloons/5 min) (Figure 1). All exercises were oriented to achieving several goals in various directions, emphasizing the elbow flexion-extension and reaching movement. The robot allows participants to execute the exercises through an “assisted as needed” control strategy. For increment the difficulty, we have varied the assisted and non-assisted modality, increasing the number of repetitions over the study period.[…]

 

Figure 1. The upper limb robot-assisted training setting.

Continue —> Frontiers | Effectiveness of Robot-Assisted Upper Limb Training on Spasticity, Function and Muscle Activity in Chronic Stroke Patients Treated With Botulinum Toxin: A Randomized Single-Blinded Controlled Trial | Neurology

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[ARTICLE] Patient-Active Control of a Powered Exoskeleton Targeting Upper Limb Rehabilitation Training – Full Text

Robot-assisted therapy affords effective advantages to the rehabilitation training of patients with motion impairment problems. To meet the challenge of integrating the active participation of a patient in robotic training, this study presents an admittance-based patient-active control scheme for real-time intention-driven control of a powered upper limb exoskeleton. A comprehensive overview is proposed to introduce the major mechanical structure and the real-time control system of the developed therapeutic robot, which provides seven actuated degrees of freedom and achieves the natural ranges of human arm movement. Moreover, the dynamic characteristics of the human-exoskeleton system are studied via a Lagrangian method. The patient-active control strategy consisting of an admittance module and a virtual environment module is developed to regulate the robot configurations and interaction forces during rehabilitation training. An audiovisual game-like interface is integrated into the therapeutic system to encourage the voluntary efforts of the patient and recover the neural plasticity of the brain. Further experimental investigation, involving a position tracking experiment, a free arm training experiment, and a virtual airplane-game operation experiment, is conducted with three healthy subjects and eight hemiplegic patients with different motor abilities. Experimental results validate the feasibility of the proposed scheme in providing patient-active rehabilitation training.

Introduction

Stroke is a severe neurological disease caused by the blockages or rupture of cerebral blood vessels, leading to significant physical disability and cognitive impairment (12). The recent statistics from the World Health Organization indicate that worldwide 15 million people annually suffer from the effect of stroke, and more than 5 million stroke patients survive and, however, require a prolonged physical therapy to recover motor function. Recent trends predict increased stroke incidence at younger ages in the upcoming years (34). Approximately four-fifths of all survived stroke patients suffer from the problems of hemiparesis or hemiplegia and, as a result, have difficulties in performing activities of daily living (ADL). Stroke causes tremendous mental and economic pressure on the patients and their families (5). Medical research has proved that, owing to the neural plasticity of the human brain, appropriate rehabilitation trainings are beneficial for stroke survivors to recover musculoskeletal motor abilities. Repetitive and task-oriented functional activities have substantial positive effects on improving motor coordination and avoiding muscle atrophy (67). Traditional stroke rehabilitation therapy involves many medical disciplines, such as orthopedics, physical medicine, and neurophysiology (89). Physiotherapists and medical personnel are required to provide for months one-on-one interactions to patients that are labor intensive, time consuming, patient-passive, and costly. Besides, the effectiveness of traditional therapeutic trainings is limited by the personal experiences and skills of therapists (1011).

In recent decades, robot-assisted rehabilitation therapies have attracted increasing attention because of their unique advantages and promising applications (1213). Compared with the traditional manual repetitive therapy, the use of robotic technologies helps improve the performance and efficiency of therapeutic training (14). Robot-assisted therapy can deliver high-intensive, long-endurance, and goal-directed rehabilitation treatments and reduce expense. Besides, the physical parameters and the training performance of patients can be monitored and evaluated via built-in sensing systems that facilitate the improvement of the rehabilitation strategy (1516). Many therapeutic robots have been developed to improve the motor functions of the upper extremity of disabled stroke patients exhibiting permanent sensorimotor arm impairments (17). The existing robots used for upper limb training can be basically classified into two types: end-point robots and exoskeleton robots. End-point robots work by applying external forces to the distal end of impaired limbs, and some examples are MIME (18), HipBot (19), GENTLE/s (20), and TA-WREX (21). Comparatively, exoskeleton robots have complex structures similar to anatomy of the human skeleton; some examples of such robots are NMES (22), HES (23), NEUROExos (24), CAREX-7 (25), IntelliArm (26), BONES (27), and RUPERT (28). The joints of the exoskeleton need to be aligned with the human anatomical joints for effective transfer of interactive forces.

The control strategies applied in therapeutic robots are important to ensure the effectiveness of rehabilitation training. So far, according to the training requirement of patients with different impairment severities, many control schemes have been developed to perform therapy and accelerate recovery. Early rehabilitation robot systems implemented patient-passive control algorithms to imitate the manual therapeutic actions of therapists. These training schemes are suitable for patients with severe paralysis to passively execute repetitive reaching tasks along predefined trajectories. Primary clinical results indicate that patient-passive training contributes to motivating muscle contraction and preventing deterioration of arm functions. The control of the human–robot interaction system is a great challenge due to its highly nonlinear characteristics. Many control algorithms have been proposed to enhance the tracking accuracy of passive training, such as the robust adaptive neural controller (29), fuzzy adaptive backstepping controller (30), neural proportional–integral–derivative (PID) controller (31), fuzzy sliding mode controller (32), and neuron PI controller (33).

The major disadvantage of patient-passive training is that the active participation of patients is neglected during therapeutic treatment (34). Several studies suggest that, for the patients who have regained parts of motor functions, the rehabilitation treatment integrated with the voluntary efforts of patients facilitates the recovery of lost motor ability (35). The patient-active control, normally referred as patient-cooperative control and assist-as-needed control, is capable of regulating the human–robot interaction depending on the motion intention and the disability level of patients. Keller et al. proposed an exoskeleton for pediatric arm rehabilitation. A multimodal patient-cooperative control strategy was developed to assist upper limb movements with an audiovisual game-like interface (36). Duschauwicke et al. proposed an impedance-based control approach for patient-cooperative robot-aided gait rehabilitation. The affected limb was constrained with a virtual tunnel around the desired spatial path (37). Ye et al. proposed an adaptive electromyography (EMG) signals-based control strategy for an exoskeleton to provide efficient motion guidance and training assistance (38). Oldewurtel et al. developed a hybrid admittance–impedance controller to maximize the contribution of patients during rehabilitation training (39). Banala et al. developed a force-field assist-as-need controller for intensive gait rehabilitation training (40). However, there are two limitations in the existing patient-cooperative control strategies. Firstly, the rehabilitation training process is not completely patient-active, as the patient needs to perform training tasks along a certain predefined trajectory. Secondly, existing control strategies are executed in self-designed virtual scenarios that are generally too simple, rough, and uninteresting. Besides, applying a certain control strategy to different virtual reality scenarios is difficult.

Taking the above issues into consideration, the main contribution of this paper is to develop a control strategy for an upper limb exoskeleton to assist disabled patients in performing active rehabilitation training in a virtual scenario based on their own active motion intentions. Firstly, the overall structure design and the real-time control system of the exoskeleton system are briefly introduced. A dynamic model of the human–robot interaction system is then established using the Lagrangian approach. After that, an admittance-based patient-active controller combined with an audiovisual therapy interface is proposed to induce the active participation of patients during training. Existing commercial virtual games without a specific predetermined training trajectory can be integrated into the controller via a virtual keyboard unit. Finally, three types of experiments, namely the position tracking experiment without interaction force, the free arm movement experiment, and the virtual airplane-game operation experiment, are conducted with healthy and disabled subjects. The experimental results demonstrate the feasibility of the proposed exoskeleton and control strategy.

Exoskeleton Robot Design

The architecture of the proposed exoskeleton is shown in Figure 1. This wearable force-feedback exoskeleton robot has seven actuated degrees of freedom (DOFs) and two passive DOFs covering the natural range of movement (ROM) of humans in ADL. The robot has been designed with an open-chain structure to mimic the anatomy of the human right arm and provide controllable assistance torque to each robot joint. There are three actuated DOFs at the shoulder for internal/external rotation, abduction/adduction, and flexion/extension; two DOFs at the elbow for flexion/extension and pronation/supination; and two DOFs at the wrist for flexion/extension and ulnal/radial deviation. Besides, since the center of rotation of the glenohumeral joint varies with the shoulder girdle movement, the robot is mounted on a self-aligning platform with two passive translational DOFs to compensate the human–robot misalignment and to guarantee interaction comfort. […]

Figure 1. Architecture of upper limb rehabilitation exoskeleton (1-Self-aligning platform; 2-AC servo motor; 3-Bowden cable components; 4-Support frame; 5-Wheelchair; 6-Elbow flexion/extension; 7-Proximal force/torque sensor; 8-Wrist flexion/extension; 9-Wrist ulnal/radial deviation; 10-Distal force/torque sensor; 11-Forearm pronation/supination; 12-Auxiliary links; 13-Shoulder flexion/extension; 14-Shoulder abduction/adduction; 15-Shoulder internal/external; 16-Free-length spring).

 

Continue —>  Frontiers | Patient-Active Control of a Powered Exoskeleton Targeting Upper Limb Rehabilitation Training | Neurology

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[ARTICLE] Quantification of Upper Limb Motor Recovery and EEG Power Changes after Robot-Assisted Bilateral Arm Training in Chronic Stroke Patients: A Prospective Pilot Study – Full Text PDF

Background. Bilateral arm training (BAT) has shown promise in expediting progress toward upper limb recovery in chronic stroke patients, but its neural correlates are poorly understood.

Objective. To evaluate changes in upper limb function and EEG power after
a robot-assisted BAT in chronic stroke patients.

Methods. In a within-subject design, seven right-handed chronic stroke patients with upper limb paresis received 21 sessions (3 days/week) of the robot-assisted BAT. The outcomes were changes in score on the upper limb section of the Fugl-Meyer assessment (FM), Motricity Index (MI), and Modified Ashworth Scale (MAS) evaluated at the baseline (T0), posttraining (T1), and 1-month follow-up (T2). Event-related desynchronization/synchronization were calculated in the upper alpha and the beta frequency ranges.

Results. Significant improvement in all outcomes was measured over the course of the study. Changes in FM were significant at T2, and in MAS at T1 and T2. After training,
desynchronization on the ipsilesional sensorimotor areas increased during passive and active movement, as compared with T0.

Conclusions. A repetitive robotic-assisted BAT program may improve upper limb motor function and reduce spasticity in the chronically impaired paretic arm. Effects on spasticity were associated with EEG changes over the ipsilesional sensorimotor network.

1. Introduction

Poststroke upper limb impairment strongly influences
disability and patients’ quality of life [1, 2]. Considering that
up to two-thirds of stroke survivors suffer from upper limb
dysfunctions, one of the main goals of rehabilitation is to
improve recovery of upper limb functioning. Many
rehabilitation approaches have been put forward [3–5].
However, there is strong evidence that the conceptual evolution
of stroke rehabilitation promotes high-intensity, taskspecific,
and repetitive training [3, 5, 6]. To this end, the
application of robot-assisted therapy has steadily gained
acceptance since the 1990s [7, 8]. Robotic devices, in fact,
allow repetitive, interactive, high-intensity, and task-specific

upper limb training across all stages of recovery and neurological
severity as well [6].
A meta-analysis has shown significant, homogeneous
positive summary effect sizes (SESs) for upper limb motor
function improvements and muscle strength with the use of
elbow-wrist robots in a bilateral mode [5]. Although subgroup
analysis revealed no significant differences between
phases post stroke [5], bilateral arm training (BAT) has
shown great promise in expediting progress toward poststroke
recovery of upper limb functioning even in the chronic
phase [6, 9–11].
BAT is a form of training in which both upper limbs perform
the same movements simultaneously and independently
of each other [12]. It can be undertaken in different
modes (in-phase, antiphase) and training modalities (i.e.,
active, passive, and active-passive) [13]. The beneficial effects
of BAT are thought to arise from a coupling effect in which
both limbs adopt similar spatio-temporal movement parameters
leading to a sort of coordination [14]. Active-passive
BAT of the wrist has been investigated in behavioral and neurophysiological
studies [11, 15]. It consists of rhythmic, continuous
bimanual mirror symmetrical movements during
which the patient actively flexes and extends the “unaffected”
wrist, while the device assists the movement of the “affected”
wrist in a mirrored, symmetrical pattern via mechanical coupling
[15–19]; that is, movement of the affected upper limb is
facilitated by the unaffected one [12]. Previous studies have
reported that this pattern of coordinated movement leads
to improvements in upper limb function [11, 16, 19, 20] associated
with an increase in ipsilesional corticomotor excitability
[11]. In addition, passive BAT of the forearm and the wrist
has been shown to lead to a sustained reduction of muscle
tone in hemiparetic patients with upper limb spasticity [20].
Current evidence indicates that the neural correlates of
BAT are poorly understood [13]. The limitations of previous
studies are threefold. First, patient characteristics such as
type and site of stroke lesion were not consistently reported
[21], precluding full understanding of motor and neural
responses to BAT. Second, different BAT modalities (i.e.,
in-phase, antiphase, active, and active-passive) combined or
not with other interventions (i.e., functional tasks or free
movements with rhythmic auditory cues) have been
reported. As different training modalities are thought to
exploit different clinical effects and neural mechanisms
[22], the relationship between each of these specific modes
(delivered as a single intervention) and brain activity patterns
needs to be more precisely explored [13]. Finally, a wide
range and variation of neurophysiological and neuroimaging
measures have been used among studies.
Essentially, transcranial magnetic stimulation (TMS)
and functional magnetic resonance imaging (fMRI) studies
have been used to investigate the neural correlates of BAT.
Strength and weakness might be acknowledged for both
techniques when applied in a neurorehabilitation setting
[23]. TMS is an important tool that fits in the middle of
the functional biology continuum for assessment in stroke
recovery. However, it has the disadvantage of not being as
relevant as other biologic measures in gathering information
on brain activity during different states (or tasks) [23],
unless electroencephalography (EEG) is recorded simultaneously
[24].
Functional imaging and related techniques ((fMRI),
positron emission tomography (PET), EEG, magnetoencephalography
(MEG), and near-infrared spectroscopy (NIRS))
are important tools to determine the effects of brain injury
and how rehabilitation can change brain systems [23].
fMRI is the most widely used technique for studying brain
function. Several fMRI studies have described movementrelated
changes in motor cortical activation during partial
recovery of the affected limb in stroke patients [25], and
many studies have described the effects of various rehabilitative
treatments on motor activation.
fMRI shows difficulties when exploring brain functions
during robot-assisted sensorimotor tasks because only a few
devices are MRI compatible [26–28] and their use in the clinical
setting is limited by regulation (i.e., CE marking).
The EEG technique, conversely, has considerable
advantages over other methods in the rehabilitation setting
[17, 18, 29] being portable and readily operable with different
robotic devices. Finally, the higher temporal resolution of
EEG than fMRI signals allows monitoring brain activity during
movement execution [30–32]. EEG alpha and beta band
powers decrease during motor execution over the premotor
and primary sensorimotor cortex; at the end of the movement,
a rebound of beta activity is observed over the ipsilesional
side. These power changes are termed, respectively,
event-related desynchronization (ERD)—that is, power band
decrease—and event-related synchronization (ERS)—that is,
power band increase [33].
To the best of our knowledge, no study has addressed
changes in EEG power alongside changes in upper limb
motor function after passive robot-assisted BAT (RBAT).
Therefore, the aim of this pilot study was to evaluate
changes in both EEG power by investigating the
topographical distribution of event ERD/ERS, and upper
limb recovery of function after passive R-BAT in chronic
stroke patients. Conducting a small-scale pilot study
before the main study can enhance the likelihood of success
of the main study. Moreover, information gathered
in this pilot study would be used to refine or modify
the research methodology and to develop large-scale studies
[34]. The work hypothesis was that R-BAT would
improve recovery of upper limb function and that these
effects would be associated with an increase in activation of
the ipsilesional hemisphere.[…]

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[Abstract] Efficacy of Short-Term Robot-Assisted Rehabilitation in Patients With Hand Paralysis After Stroke: A Randomized Clinical Trial

Background: We evaluated the effectiveness of robot-assisted motion and activity in additional to physiotherapy (PT) and occupational therapy (OT) on stroke patients with hand paralysis.

Methods:A randomized controlled trial was conducted. Thirty-two patients, 34.4% female (mean ± SD age: 68.9 ± 11.6 years), with hand paralysis after stroke participated. The experimental group received 30 minutes of passive mobilization of the hand through the robotic device Gloreha (Brescia, Italy), and the control group received an additional 30 minutes of PT and OT for 3 consecutive weeks (3 d/wk) in addition to traditional rehabilitation. Outcomes included the National Institutes of Health Stroke Scale (NIHSS), Modified Ashworth Scale, Barthel Index (BI), Motricity Index (MI), short version of the Disabilities of the Arm, Shoulder and Hand (QuickDASH), and the visual analog scale (VAS) measurements. All measures were collected at baseline and end of the intervention (3 weeks).

Results: A significant effect of time interaction existed for NIHSS, BI, MI, and QuickDASH, after stroke immediately after the interventions (all, P < .001). The experimental group had a greater reduction in pain compared with the control group at the end of the intervention, a reduction of 11.3 mm compared with 3.7 mm, using the 100-mm VAS scale.

Conclusions: In the treatment of pain and spasticity in hand paralysis after stroke, robot-assisted mobilization performed in conjunction with traditional PT and OT is as effective as traditional rehabilitation.

via Efficacy of Short-Term Robot-Assisted Rehabilitation in Patients With Hand Paralysis After Stroke: A Randomized Clinical Trial – Jorge H. Villafañe, Giovanni Taveggia, Silvia Galeri, Luciano Bissolotti, Chiara Mullè, Grace Imperio, Kristin Valdes, Alberto Borboni, Stefano Negrini, 2018

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[Review] Robot-Assisted and Device-Based Rehabilitation of the Upper Extremity – Full Text

Abstract

Neurorehabilitation of patients with upper limb motor dysfunction due to central nervous system damage still lacks adequate standardization. During the last decade, robot- and device-assisted rehabilitation has become more feasible for the treatment of functional disorders of the upper limb after stroke. Here we present an overview of technological aspects and differential use of devices for upper limb rehabilitation as well as a review of relevant clinical studies. We also discuss the potential for standardized evaluation in the context of limited health care resources. The effectiveness of device-assisted therapy, in comparison to conventional approaches, remains a matter of debate, largely due to the heterogeneous design of the available clinical studies. However, we believe that a better understanding of the timing, intensity, and quality of upper limb rehabilitation, as well as technological progress, will lead to the establishment of a central role for robot- and device-assisted rehabilitation in the next decade.

Introduction

Improvement of the functionality of the upper limb after an injury to the central nervous system (CNS) is one of the most important tasks of neurorehabilitation. Stroke is the leading cause of upper limb disability, with a range of complex functional upper limb impairments occurring in approximately 50 to 70 percent of cases [1]. In addition, these patients commonly exhibit sensory-motor deficits of the lower extremity, speech impairment, visual defects, and cognitive deficits during the acute phase. Even limited dysfunction of the upper extremity can result in significant limitations of daily activities and quality of life [2]. The probability of regaining sufficient hand function, i. e., grasping adequate for performance of everyday activities, in the presence of a pronounced functional disorder due to a distal paresis or hand paralysis, is at most 20 percent [3]. Effective therapy of the upper limb is therefore a crucial component of neurorehabilitation.

In recent years, neurorehabilitative therapy for motor deficits has focused on task-specific training, comprising repetitive, context-specific exercises. In addition, introduction of “shaping” exercises at the individual patient’s limits of motion, as well as active or passive repetitive activities to reinforce motor learning, should be considered essential foundations of rehabilitative therapy.

A uniform standard of therapy for upper extremity sensorimotor deficits is not currently in place, and individual variation in deficits renders such a standardization unlikely. Based on 109 publications, the guidelines of the German Society for Neurorehabilitation (Deutsche Gesellschaft für Neurorehabilitation), “Rehabilitative Therapy of Arm Paresis after Stroke” published in 2009 [4] provide recommendations regarding the timing, duration, and intensity of therapy. The highest levels (A and B) of recommended therapy contain subgroups of repetitive exercises for gripping and releasing to treat paresis of the hand with partially retained proximal motor function. These include damage-oriented training for arm capacity, basic arm trainingconstraint-induced movement therapymirror therapy, and mental training, as well as neuromuscular electrostimulation (NMES)Robotics-supported upper limb therapy provides a potential adjunct, particularly for those unable to perform the therapeutic motions independently, and is classified as recommendation level B (therapy that should be carried out), i. e., offering average efficacy with a medium to high degree of supporting evidence, based on studies of device-supported therapy focusing on stereotypical movements, without specific task-oriented exercises.

Despite considerable growth in recent years in the number of studies investigating the efficacy of robot-assisted interventions in improving arm function and daily activity performance, the methodological heterogeneity of the studies has led to the conclusion in recent Cochrane meta-analyses that the evidence remains limited [5] [6]. Nonetheless, a systematic review and meta-analysis this year suggested there may be improvement in motor control and muscle strength [7].

In the next sections, we provide an overview of the current state of technological developments as well as clinical applications. […]

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[Abstract] Cognitive motor interference on upper extremity motor performance in a robot-assisted planar reaching task among patients with stroke

Abstract

Objective

To explore motor performance on two different cognitive tasks during robotic rehabilitation in which motor performance was longitudinally assessed.

Design

Prospective study

Setting

Rehabilitation hospital

Participants

Patients with chronic stroke and upper extremity impairment (N=22)

Intervention

A total of 640 repetitions of robot-assisted planar reaching, five times a week for 4 weeks

Main Outcome Measures

Longitudinal robotic evaluations regarding motor performance included smoothness, mean velocity, path error, and reach error by the type of cognitive task. Dual-task effects (DTE) of motor performance were computed in order to analyze the effect of the cognitive task on dual-task interference.

Results

Cognitive task type influenced smoothness (p = 0.006), the DTE of smoothness (p = 0.002), and the DTE of reach error (p = 0.052). Robotic rehabilitation improved smoothness (p = 0.007) and reach error (p = 0.078), while stroke severity affected smoothness (p = 0.01), reach error (p < 0.001), and path error (p = 0.01). Robotic rehabilitation or severity did not affect the DTE of motor performance.

Conclusions

The present results provide evidence for the effect of cognitive-motor interference on upper extremity performance among participants with stroke using a robotic-guided rehabilitation system.

Source: Cognitive motor interference on upper extremity motor performance in a robot-assisted planar reaching task among patients with stroke – Archives of Physical Medicine and Rehabilitation

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[Abstract] Efficacy of robot-assisted rehabilitation to functional recovery upper limb in post stroke patients: a randomized controlled study. – Eur J Phys Rehabil Med.

Abstract

BACKGROUND:

We evaluated the effectiveness of robotic-assisted motion and activity in additional to Physical and Rehabilitation Medicine (PRM), of the upper limb in post stroke inpatients.

METHODS:

A randomized controlled trial. Fifty-four patients, 57% female (mean ± SD age: 71 ±12 years), with upper limb function defecit post stroke. The experimental group received a passive mobilization of the upper limb through the robotic device ARMEO Spring and the control group received PRM for 6 consecutive weeks (5 days/week) in addition to traditional PRM. We assessed the impact on functional recovery (Functional Independence Measure-FIM scale), strength (ARM Motricity Index-MI), spasticity (Modified Ashworth Scale-MAS) and pain (Numeric Rating Pain Scale -NRPS). All patients were evaluated by a blinded observer using the outcomes tests at enrollment (T0), after the treatment (T1) and at follow up 6 weeks later (T2).

RESULTS:

Both control and experimental groups evidenced an improvement of the outcomes after the treatment (Motricity Index, Ashworth and NRPS with p<0.05). The experimental group showed further improvements after the follow up (all outcomes with p<0.01).

CONCLUSIONS:

In the treatment of pain, disability and spasticity in upper limb after stroke, robot-assisted mobilization associated to PRM is as effective as traditional rehabilitation.

Source: Efficacy of robot-assisted rehabilitation to functional recovery upper limb in post stroke patients: a randomized controlled study. – PubMed – NCBI

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[Abstract] Combined effects of robot-assisted gait training and botulinum toxin type A effect on spastic equinus foot in patients with chronic stroke: a pilot, single blind, randomized controlled trial

Abstract

BACKGROUND:

Despite the growing evidence about the use of robotic gait training in neurorehabilitation, there is a scant literature about the combined effects of this innovative technological approach and a first-line treatment for focal spasticity as botulinum toxin type A. In particular, to the best of our knowledge, no previous study evaluated if robotic gait training may enhance the antispastic effect of botulinum toxin type A.

AIM:

To evaluate the combined effects of robot-assisted gait training and botulinum toxin type A on spastic equinus foot in patients with chronic stroke.

DESIGN:

Pilot, single blind, randomized controlled trial.

SETTING:

University hospital.

POPULATION:

Twenty-two adult outpatients with spastic equinus due to chronic stroke.

METHODS:

Participants were randomly assigned to two groups: patients allocated to the Group 1 received robot-assisted gait training (30 minutes a day for five consecutive days) after AbobotulinumtoxinA injection into the spastic calf muscles as well as patients allocated to the Group 2 were only injected with AbobotulinumtoxinA into the same muscles. All patients were evaluated immediately before and one month after injection. The following outcome measures were considered: the modified Ashworth scale, the Tardieu scale and the 6-minute walking test.

RESULTS:

No difference was found between groups as to the modified Ashworth scale and the Tardieu scale measured at the affected ankle one month after botulinum toxin injection. A significant difference in the 6- minute walking test was noted between groups at the post-treatment evaluation (P=0.045).

CONCLUSIONS:

Our preliminary findings support the hypothesis that robot-assisted gait training does not enhance the effect of botulinum toxin type A on spastic equinus foot in patients with chronic stroke.

CLINICAL REHABILITATION IMPACT:

Our observations should be taken into account in daily clinical rehabilitation practice in order to develop effective treatment protocols based on the enhancement of antispastic drugs effect.

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Source: Combined effects of robot-assisted gait training and botulinum toxin type A effect on spastic equinus foot in patients with chronic stroke: a pilot… – PubMed – NCBI

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[ARTICLE] SYSTEM IDENTIFICATION MODELING OF ARM REHABILITATION DEVICES – Full Text PDF

ABSTRACT

In this paper, modeling of the arm rehabilitation device using system identification technique is presented.

Patients who have post-stroke may lose control of their upper limb. If they are treated with effective rehabilitation training, the patients can restore their upper limb motion functions and working abilities. These rehabilitation devices are used to recover the movement of arm after stroke. Robot assisted therapy systems need three elements which are algorithms, robot hardware and computer system. An accurate system modelling is crucially important to represent the system well. Inaccurate model could diminish the overall control system later on.

The objective of this work is to development mathematical modeling of the arm rehabilitation device by using System Identification from experimental data. Several transfer functions are evaluated in order to choose the best performances that represent the system. It must show a good criteria based on the best fitness percentage, stability of the location of poles and zero and also the frequency response characteristics. The derived model is validated via simulation for stability analysis. It is expected that a stable model with an acceptable level of accuracy would be developed for further control system design.

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