Posts Tagged robot

[Abstract] Robot-assisted mirroring exercise as a physical therapy for hemiparesis rehabilitation


The paper suggests a therapeutic device for hemiparesis that combines robot-assisted rehabilitation and mirror therapy. The robot, which consists of a motor, a position sensor, and a torque sensor, is provided not only to the paralyzed wrist, but also to the unaffected wrist to induce a symmetric movement between the joints. As a user rotates his healthy wrist to the direction of either flexion or extension, the motor on the damaged side rotates and reflects the motion of the normal side to the symmetric angular position. To verify performance of the device, five stroke patients joined a clinical experiment to practice a 10-minute mirroring exercise. Subjects on Brunnstrom stage 3 had shown relatively high repulsive torques due to severe spasticity toward their neutral wrist positions with a maximum magnitude of 0.300kgfm, which was reduced to 0.161kgfm after the exercise. Subjects on stage 5 practiced active bilateral exercises using both wrists with a small repulsive torque of 0.052kgfm only at the extreme extensional angle. The range of motion of affected wrist increased as a result of decrease in spasticity. The therapeutic device not only guided a voluntary exercise to loose spasticity and increase ROM of affected wrist, but also helped distinguish patients with different Brunnstrom stages according to the size of repulsive torque and phase difference between the torque and the wrist position.

Source: Robot-assisted mirroring exercise as a physical therapy for hemiparesis rehabilitation – IEEE Conference Publication


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[Editorial] Robotics in Biomedical and Healthcare Engineering – Journal of Healthcare Engineering

The rapid progress of robotic technique provides new opportunities
for the biomedical and healthcare engineering. For
instance, a micro-nano robot allows us to study the fundamental
problems at cellular scale owing to its precise
positioning and manipulation ability; the medical robot
paves a new way for the low invasive and high efficient clinical
operation; and rehabilitation robot is able to improve the
rehabilitative efficacy of patients. This special issue aims at
exhibiting the latest research achievements, findings, and
ideas in the field of robotics in biomedical and healthcare
engineering, especially focusing on the upper/lower limb
rehabilitation, walking assistive robot, telerobotic surgery,
and radiosurgery.

Currently, there is an increasing population of patients
suffering from limb motor dysfunction, which can be caused
by nerve injuries associated with stroke, traumatic brain
injury, or multiple sclerosis. Past studies have demonstrated
that highly repetitive movement training can result in
improved recovery. The robotic-assisted technique is a novel
and rapidly expanding technology in upper/lower limb rehabilitation
that can enhance the recovery process and facilitate
the restoration of physical function by delivering high-dose
and high-intensity training. This special issue covers several
interesting papers addressing these challenges. X. Tu and
coworkers introduced an upper limb rehabilitation robot
powered by pneumatic artificial muscles which cooperates
with functional electrical stimulation arrays to realize active
reach-to-grasp training for stroke patients. The dynamic
models of a pneumatic muscle and functional electrical
stimulation-induced muscle are built for reaching training.
By using surface electromyography, the subject’s active intent
can be identified. Finally, grasping and releasing behaviors
can be realized by functional electrical stimulation array electrodes.
C. Guo and coworkers proposed an impedance-based
iterative learning control method to analyze the squatting
training of stroke patients in the iterative domain and time
domain. Patient’s training trajectory can be corrected by integrating
the iterative learning control scheme with the value of
impedance. In addition, the method can gradually improve
the performance of trajectory tracking by learning the past
trajectory tracking information and obtain specific training
condition of different individuals. The paper demonstrated
an effective control methodology in dealing with repeated
tracking control problems or periodic disturbance rejection
problems. Apart from these works, J. Li and coworkers
designed an open-structured treadmill gait trainer for lower
limb rehabilitation; T. Sun and coworkers proposed a
method for detecting the motion of human lower limbs
including all degrees of freedoms via the inertial sensors,
which permits analyzing the motion ability according to the
rehabilitation needs.

Other biomedical and healthcare robots included in this
special issue cover a range of interesting topics, such as walking
assistive robot, telerobotic surgery, and radiosurgery. To improve the walking ability of the elderly, the walker-type
rehabilitation robot has become a popular research topic over
the last decade. C. Tao and coworkers proposed a hierarchical
shared control method of the walking-aid robot for both
human motion intention recognition and the obstacle
emergency-avoidance method based on the artificial potential
field. In the implementation, the human motion intention
is obtained from the interaction force measurements of
the sensory system composed of force sensing registers and
a torque sensor. Meanwhile, a laser-range finder forward is
applied to detect the obstacles and try to guide the operator
based on the repulsion force calculated by artificial potential
field. The robot realizes obstacle avoidance while keeping
partially the operators’ original walking intention. X. Li and
coworkers demonstrated a general framework for robotassisted
surgical simulators for a more robust and resilient
robotic surgery. They created a hardware-in-the-loop simulator
platform and integrated the simulator with a physics
engine and a state-of-the-art path planning algorithm to help
surgeons acquire an optimal sense of manipulating the robot
instrumental arm. Eventually, they achieved autonomous
motion of the surgical robot. For coping with the workspace
issue during the application of Linac system during radiosurgery,
a specialized robotic system was presented by Y. Noh
et al. The design and implementation of the robotic system
were elaborated. All of these works showed comparative
advantages versus classical approaches and will hold great
potential for providing insights on the practical and systematic
design of robots that serve for broad applications in
biomedical and healthcare engineering.

The objectives of the special issue were reached in terms
of advancing the state of the art of robotic techniques and
addresing the challenging problems in biomedical and
healthcare engineering. Several critical problems in these
areas were addressed, and most of the proposed contributions
showed very promising results that outperform existing
studies. Some of the proposed approaches were also validated
from patients’ perspectives, which show the applicability of
these techniques in realistic environments.

We would like to express our thanks to all the authors who
submitted their work to this special issue and to all the
reviewers who helped us ensure the quality.

Chengzhi Hu
Qing Shi
Lianqing Liu
Uche Wejinya
Yasuhisa Hasegawa
Yajing Shen

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[ARTICLE] Neural Patterns of Reorganization after Intensive Robot-Assisted Virtual Reality Therapy and Repetitive Task Practice in Patients with Chronic Stroke – Full Text

Several approaches to rehabilitation of the hand following a stroke have emerged over the last two decades. These treatments, including repetitive task practice, robotically assisted rehabilitation and virtual rehabilitation activities, produce improvements in hand function, but have yet to reinstate function to pre-stroke levels— which likely depends on developing the therapies to impact cortical reorganization in a manner that favors or supports recovery. Understanding cortical reorganization that underlies the above interventions is therefore critical to inform how such therapies can be utilized and improved, and is the focus of the current investigation. Specifically, we compare neural reorganization elicited in stroke patients participating in two interventions: a hybrid of robot-assisted virtual reality rehabilitation training (RAVR), and a program of repetitive task practice training (RTP).
Ten chronic stroke subjects participated in eight, three-hour sessions of RAVR therapy. Another group of 9 stroke subjects participated in eight sessions of matched RTP therapy. Functional Magnetic Resonance Imagining (fMRI) data were acquired during paretic hand movement, before and after training. We compared the difference between groups and sessions (before and after training) in terms of BOLD intensity, laterality index of activation in sensorimotor areas, and the effective connectivity between ipsilesional motor cortex (iMC), contralesional motor cortex (cMC), ipsilesional primary somatosensory cortex (iS1), ventral premotor area (iPMv), and supplementary motor area (iSMA). Last, we analyzed the relationship between changes in fMRI data and functional improvement measured by the Jebsen Taylor Hand Function Test (JTHFT), in an attempt to identify how neurophysiological changes are related to motor improvement.
Subjects in both groups demonstrated motor recovery after training, but fMRI data revealed RAVR-specific changes in neural reorganization patterns. First, BOLD signal in multiple regions of interest was reduced and re-lateralized to the ipsilesional side. Second, these changes correlated with improvement in JTHFT scores. Our findings suggest that RAVR training may lead to different neurophysiological changes when compared to traditional therapy. This effect may be attributed to the influence that augmented visual and haptic feedback during RAVR training exerts over higher-order somatosensory and visuomotor areas.


Recovery of hand function is challenging after stroke. Empirical data suggest that treatment can be beneficial if it includes many repetitions of challenging and meaningful tasks (13). Several approaches to delivering high volume, intense, and salient rehabilitation activities have emerged over the last two decades. These treatments, which include repetitive task practice (RTP), robotically assisted rehabilitation, and virtual rehabilitation activities, produce improvements in hand function that exceed the standard of care in the US (45).

Although a strong case has been made that virtual reality (VR) and robotics can be useful technologies for delivering challenging, meaningful, and mass practice, outcome studies investigating the true benefits of VR/robotics as compared to dose-matched RTP remain mixed (67). For example, we have shown significant group-level improvement in hand and arm function of chronic stroke survivors in response to RTP and robot-assisted VR (RAVR) training to be similar for both groups (8), a finding that agrees with group-level effects in other clinical studies (910). However, whether the underlying neural patterns of reorganization that are induced by the different training regimes are also similar remains unknown. This becomes important to understand because it may inform researchers and clinicians whether RAVR versus RTP may preferentially facilitate distinct neural patterns of reorganization. If so, then perhaps the therapy choice can be tailored more appropriately to individuals to elicit optimal benefits.

The goal of this study was to compare the effect of RAVR- and RTP-based interventions on neural pattern reorganization. Because neural reorganization likely reflects complex processes that include the formation of new connections and/or re-weighting of existing connections, the patterns that emerge are unlikely to be reliably captured using one proxy of activation. For example, while numerous studies have shown training-induced changes in the extent of brain activity, the results of those studies conflict in terms of whether the changes reflect an increase or a decrease in brain activity (1115). Second, there seems to be a relationship between the pattern of reorganization (increase or decrease in ipsilesional somatosensory activation) and intactness of the hand knob area of M1 and its descending motor fibers (16), and a dependence on whether the lesion is cortical or subcortical (17). Connectivity measures may be a complementary way to understand neural reorganization patterns underlying stroke recovery (18) by providing additional information about dynamic network-level changes above and beyond what can be inferred from extent and laterality of activation (1920).

In this study, we therefore characterize the pattern of neural reorganization using multiple measures that included the magnitude of change in brain activation, the extent of activation, the re-lateralization of brain activation in a set of homologous interhemispheric regions of interest, and interactions between multiple regions of interest based on measures of functional and effective connectivity. To our knowledge, this is the first study to characterize brain reorganization at the ROI and network interaction level with multiple functional magnetic resonance imaging (fMRI) measures before and after RAVR and RTP training. In order to delineate the relevance of brain reorganization after training, we also correlated the brain activation outcomes with clinical outcome measures.

We hypothesized that both treatments might have similar effects on the magnitude and laterality of activation in a given region of interest. However, because RAVR training provides a training environment that is enriched and augmented with visual and haptic feedback, we expected that the functional and effective connectivity between motor/premotor cortices and visuomotor areas like the superior parietal lobule may show stronger effects in the RAVR group, as compared to the RTP-based training group (2125). We propose that identifying the neurophysiologic correlates of behavioral motor function improvement might allow strategic refinement of existing training approaches and the development of individually tailored interventions. […]


Continue —>  Frontiers | Neural Patterns of Reorganization after Intensive Robot-Assisted Virtual Reality Therapy and Repetitive Task Practice in Patients with Chronic Stroke | Neurology

Figure 1(A,B) The robotic arm, a data glove and force-reflecting hand system used in the robot-assisted virtual reality therapy. (C) Virtual reality feedback during the fMRI movement task. For each hand, one arrow points to the starting position of the hand (open) and another arrow defines the magnitude of finger flexion during the task.

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[Abstract] Design factors and opportunities of rehabilitation robots in upper-limb training after stroke


The occurrence of strokes has been progressively increasing. Upper limb recovery after stroke is more difficult than lower limb. One of the rapidly expanding technologies in post-stroke rehabilitation is robot-aided therapy. The advantage of robots is that they are able to deliver highly repetitive therapeutic tasks with minimal supervision of a therapist. However, from the literature, the focus of robotic design in stroke rehabilitation has been technology-driven. Clinical and therapeutic requirements were not seriously considered in the design of rehabilitation robots. The purpose of this study was twofold: (1) demonstrate the missing elements of current robot-aided therapy; (2) identify design factors and opportunities of rehabilitation robots (in upper-limb training after stroke). In this study, we performed a literature review on articles relevant to rehabilitation robots in upper-limb training after stroke. We identified the design foci of current rehabilitation robots for upper limb stroke recovery. Using the therapeutic framework for stroke rehabilitation in occupational therapy, we highlighted design factors and opportunities of rehabilitation robots. The outcomes of this study benefit the robotics design community in the design of rehabilitation robots.

1. Introduction

A robot is defined as a machine programmable to perform and modify tasks in response to changes in the environment [1]. The benefits of robots are noticeable in productivity, safety, and in saving time and money. The advancement of robot technologies in the past decade caused the wide adoption of robots in our lives and in the society. For instance, in education, robots were implemented in undergraduate courses to teach core artificial intelligence concepts, e.g., algorithms for searching tree data structures [2]. In agriculture, robotic milking systems (being able to reduce labor/operational costs) were installed to replace conventional milking that gave cows the freedom to be milked throughout the day [3]. In healthcare, service robots were implemented to provide functional assistance for the elderly in home environments, e.g., bringing medication for the emergency and picking up heavy objects low on the ground [4].

Source: Design factors and opportunities of rehabilitation robots in upper-limb training after stroke – IEEE Xplore Document

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[Abstract+References] Impedance Control of a Pneumatic Muscles-Driven Ankle Rehabilitation Robot – Conference paper


Pneumatic muscle is a new type of flexible actuator with advantages in terms of light weight, large output power/weight ratio, good security, low price and clean. In this paper, an ankle rehabilitation robot with two degrees of freedom driven by pneumatic muscle is studied. The force control method with an impedance controller in outer loop and a position inner loop is proposed. The demand of rehabilitation torque is ensured through tracking forces of three pneumatic muscle actuators. In the simulation, the constant force and variable force are tracked with error less than 10 N. In the experiment, the force control method also achieved satisfactory results, which provides a good support for the application of the robot in the ankle rehabilitation.


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Source: Impedance Control of a Pneumatic Muscles-Driven Ankle Rehabilitation Robot | SpringerLink

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[Abstract+References] A Review of Upper and Lower Limb Rehabilitation Training Robot – Conference paper


With the aging of society, the number of patients with limb disorders caused by stroke has increased year by year, it is necessary to introduce more advanced technology into the field of rehabilitation treatment. Rehabilitation training based on the brain plasticity has been proved by clinical medical practice as an effective treatment method, and because of the serious lack of professional rehabilitation therapists, a large number of rehabilitation training robot have been designed so far. This article analyzed and described the research status on upper and lower limbs rehabilitation training robot, and at last the paper forecasts the future development trend of rehabilitation robot.

Source: A Review of Upper and Lower Limb Rehabilitation Training Robot | SpringerLink

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[REVIEW] Is robot-assisted therapy effective in upper extremity recovery in early stage stroke? —a systematic literature review


[Purpose] The aim of this study was to systematically investigate the effects of robot-assisted therapy on the upper extremity in acute and subacute stroke patients.

[Subjects and Methods] The papers retrieved were evaluated based on the following inclusion criteria: 1) design: randomized controlled trials; 2) population: stroke patients 3) intervention: robot-assisted therapy; and 4) year of publication: May 2012 to April 2016. Databased searched were: EMBASE, PubMed and COCHRAN databases. The Physiotherapy Evidence Database (PEDro) scale was used to assess the methodological quality of the included studies. [Results] Of the 637 articles searched, six studies were included in this systematic review. The PEDro scores range from 7 to 9 points.

[Conclusion] This review confirmed that the robot-assisted therapy with three-dimensional movement and a high degree of freedom had positive effects on the recovery of upper extremity motor function in patients with early-stage stroke. We think that the robot-assisted therapy could be used to improve upper extremity function for early stage stroke patients in
clinical setting.

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[ARTICLE] A Neuromuscular Electrical Stimulation (NMES) and robot hybrid system for multi-joint coordinated upper limb rehabilitation after stroke – Full Text



It is a challenge to reduce the muscular discoordination in the paretic upper limb after stroke in the traditional rehabilitation programs.


In this study, a neuromuscular electrical stimulation (NMES) and robot hybrid system was developed for multi-joint coordinated upper limb physical training. The system could assist the elbow, wrist and fingers to conduct arm reaching out, hand opening/grasping and arm withdrawing by tracking an indicative moving cursor on the screen of a computer, with the support from the joint motors and electrical stimulations on target muscles, under the voluntary intention control by electromyography (EMG). Subjects with chronic stroke (n = 11) were recruited for the investigation on the assistive capability of the NMES-robot and the evaluation of the rehabilitation effectiveness through a 20-session device assisted upper limb training.


In the evaluation, the movement accuracy measured by the root mean squared error (RMSE) during the tracking was significantly improved with the support from both the robot and NMES, in comparison with those without the assistance from the system (P < 0.05). The intra-joint and inter-joint muscular co-contractions measured by EMG were significantly released when the NMES was applied to the agonist muscles in the different phases of the limb motion (P < 0.05). After the physical training, significant improvements (P < 0.05) were captured by the clinical scores, i.e., Modified Ashworth Score (MAS, the elbow and the wrist), Fugl-Meyer Assessment (FMA), Action Research Arm Test (ARAT), and Wolf Motor Function Test (WMFT).


The EMG-driven NMES-robotic system could improve the muscular coordination at the elbow, wrist and fingers.


Stroke is a main cause of long-term disability in adults [1]. Approximately 70 to 80% stroke survivors experienced impairments in their upper extremity, which greatly affects the independency of their daily living [23]. In the upper limb rehabilitation, it also has been found that the recovery of the proximal joints, e.g., the shoulder and the elbow, is much better than the distal, e.g., the wrist and fingers [45]. The main possible reasons are: 1) The spontaneous motor recovery in early stage after stroke is from the proximal to the distal; and 2) the proximal joints experienced more effective physical practices than the distal joints throughout the whole rehabilitation process, since the proximal joints are easier to be handled by a human therapist and are more voluntarily controllable by most of stroke survivors [2]. However, improved proximal functions in the upper limb without the synchronized recovery at the distal makes it hard to apply the improvements into meaningful daily activities, such as reaching out and grasping objects, which requires the coordination among the joints of the upper limb, including the hand. More effective rehabilitation methods which may benefit the functional restoration at both the proximal and the distal are desired for post-stroke upper limb rehabilitation.

Besides the weakness and spasticity of muscles in the paretic upper limb, discoordination among muscles is also one of the major impairments after stroke, mainly reflected as abnormal muscular co-activating patterns and loss of independent joint control [26]. Stereotyped movements of the entire limb with compensation from the proximal joints are commonly observed in most of persons with chronic stroke who have passed six months after the onset of the stroke, during which abnormal motor synergies were gradually developed. Neuromuscular electrical stimulation (NMES) is a technique that can generate limb movements by applying electrical current on the paretic muscles [7]. Post-stroke rehabilitation assisted with NMES has been found to effectively prevent muscle atrophy and improve muscle strength [7], and the stimulation also evokes sensory feedback to the brain during muscle contraction to facilitate motor relearning [8]. It has been found that NMES can improve muscular coordination in a paralysed limb by limiting ‘learned disuse’ that stroke survivors are gradually accustomed to managing their daily activities without using certain muscles, which has been considered as a significant barrier to maximizing the recovery of post-stroke motor function [9]. However, difficulties have been found in NMES alone to precisely activate groups of muscles for dynamic and coordinated limb movements with desired accuracy in kinematics, for example, speeds and trajectories. It is because most of the NMES systems adopted transcutaneous stimulation with surface electrodes only recruiting muscles located closely to the skin surface with limited stimulation channels [8]. Therefore, the muscular force evoked may not be enough to achieve the precise limb motions. However, limb motions with repeated and close-to-normal kinematic experiences are necessary to enhance the sensorimotor pathways in rehabilitation, which has been found to contribute to the motor recovery after stroke [10]. Furthermore, faster muscular fatigue would be experienced when using NMES with intensive stimuli, in comparison with the muscle contraction by biological neural stimulation [11].

The use of rehabilitation robots is one of the solutions to the shortage of affordable professional manpower in the industry of physical therapy, to cope with the long-term and labour-demanding physical practices [10]. In comparison with the NMES, robots can well control the limb movements with electrical motors. Various robots have been proposed for upper limb training after stroke [1213]. Among them, the robots with the involvement of voluntary efforts from persons after stroke demonstrated better rehabilitation effects than those with passive limb motions, i.e., the limb movements are totally dominated by the robots [10]. Physical training with passive motions only contributed to the temporary release of muscle spasticity; whereas, voluntary practices could improve the motor functions of the limb with longer sustainability [1014]. In our previous studies, we designed a series of voluntary intention-driven rehabilitation robotics for physical training at the elbow, the wrist and fingers [1415161718]. Residual electromyography (EMG) from the paretic muscles was used to control the robots to provide assistive torques to the limb for desired motions. The results of applying these robots in post-stroke physical training showed that the target joint could obtain motor improvements after the training; however, more significant improvements usually appeared at its neighbouring proximal joint mainly due to the compensatory exercises from the proximal muscles [1517]. In order to improve the muscle coordination during robot-assisted training, we integrated NMES into the EMG-driven robot as an intact system for wrist rehabilitation [1619]. It has been found that the combined assistance with both robot and NMES could reduce the excessive muscular activities at the elbow and improve the muscle activation levels related to the wrist, which was absent in the pure robot assisted training [16]. More recently, combined treatment with robot and NMES for the wrist by other research group also demonstrated more promising rehabilitation effectiveness in the upper limb functions than pure robot training [20]. However, most of the proposed devices are for single joint treatment, and cannot be used for multi-joint coordinated upper limb training. Furthermore, the training tasks provided by these devices are not easy to be directly translated into daily activities. We hypothesized that multi-joint coordinated upper limb training assisted by both NMES and robot could improve the muscular coordination in the whole upper limb and promote the synchronized recovery at both the proximal and distal joints. In this work, we designed a multi-joint robot and NMES hybrid system for the coordinated upper limb physical practice at the elbow, wrist and fingers. Then, the rehabilitation effectiveness with the assistance of the device was evaluated by a pilot single-group trial. EMG signals from target muscles were used for voluntary intention control for both the robot and NMES parts.


The NMES-robot system

The system developed is a wearable device as shown in Fig. 1. It can support a stroke subject to perform sequencing limb movements, i.e., 1) elbow extension, 2) wrist extension associated with hand open, 3) wrist flexion and 4) elbow flexion, with the purpose of simulating the coordination of the joints in arm reaching out, hand open for grasping, and withdrawing in daily activities. The starting position of the motion cycle was set at the elbow joint extended at 180° and the wrist extended at 45°, which is also the end point for a motion cycle. In each phase of the motion, visual guidance on a computer screen was provided to a subject by following a moving cursor on the computer screen with a constant angular velocity at 10°/s for the movement of the wrist and the elbow. The subject was asked to minimize the target and actual joint positions during the tracking. In the limb tasks, assistances would be provided from the mechanical motors and NMES at the same time related to the wrist and elbow flexion/extension. NMES alone was applied for finger extension, and there was no assistance from the system for finger flexion (hand grasp). It is because that the main impairment in the hand for persons with chronic stroke is hand open, and the hand grasp can be achieved passively due to spasticity in finger flexors, and one channel NMES has demonstrated the capacity to achieve the gross open of the hand with finger extensions in clinical practices [2]. With the attempt to reduce the overall weight of the system, especially at the distal joints, for the coordinated multi-joint training of the whole upper limb, finger motions were only supported by the NMES in this work. The robot and NMES combined effects on individual finger motions in chronic stroke have been investigated in our previous work [21]. A hanging system was used to lift up the testing limb to a horizontal level (Fig. 1), to compensate the limb gravity and the weight of the wearable part of the system (totally 895 g).

Fig. 1 a The schematic diagram of the experimental setup, b a photo of a subject who is conducting the tracking task with the NMES-robot, c a photo of a subject wearing the mechanical parts of the system, d the configuration of the NMES electrodes and EMG electrodes on a driving muscle. The driving muscles in the study are BIC, TRI, FCR and the muscle union of ECU-ED

Continue —> A Neuromuscular Electrical Stimulation (NMES) and robot hybrid system for multi-joint coordinated upper limb rehabilitation after stroke | Journal of NeuroEngineering and Rehabilitation | Full Text


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[ARTICLE] Effect of Upper Extremity Robot-Assisted Exercise on Spasticity in Stroke Patients – Full Text


Objective: To determine the efficacy of a stretching and strengthening exercise program using an upper extremity robot, as compared with a conventional occupational therapy program for upper extremity spasticity in stroke patients.


Methods: Subjects were randomly divided into a robot-assisted therapy (RT) group and a conventional rehabilitation therapy (CT) group. RT group patients received RT and CT once daily for 30 minutes each, 5 days a week, for 2 weeks. RT was performed using an upper-extremity robot (Neuro-X; Apsun Inc., Seoul, Korea), and CT was administered by occupational therapists. CT group patients received CT alone twice daily for 30 minutes, 5 days a week, for 2 weeks. Modified Ashworth Scale (MAS) was used to measure the spasticity of upper extremity. Manual muscle tests (MMT), Manual Function Tests (MFT), Brunnstrom stage, and the Korean version of Modified Barthel Index (K-MBI) were used to measure the strength and function of upper extremity. All measurements were obtained before and after 2-week treatment.


Results: The RT and CT groups included 22 subjects each. After treatment, both groups showed significantly lower MAS scores and significant improvement in the MMT, MFT, Brunnstrom stage, and K-MBI scores. Treatment effects showed no significant differences between the two groups.


Conclusion: RT showed similar treatment benefits on spasticity, as compared to CT. The study results suggested that RT could be a useful method for continuous, repeatable, and relatively accurate range of motion exercise in stroke patients with spasticity.


Spasticity is defined as a velocity-dependent increase in tonic stretch reflex, resulting from over-excitation of the stretch reflex due to upper motor neuron lesions [1]. It occurs frequently in patients with post-stroke hemiplegia. Excessive spasticity reduces patients’ range of motion (ROM) to the extent that it obstructs daily living activities and functional improvement, thereby adversely affecting successful rehabilitation.

Various treatment methods are used to control spasticity, such as exercise, drug therapy, electrostimulation, surgery, and local nerve block using botulinum toxin [2, 3, 4, 5]. Conventional rehabilitation therapy for spasticity administered by therapists includes passive stretching and ROM exercise treatment. The amount and effects of repetitive exercise manually induced by therapists may differ according to the therapists’ levels of experience [6].

In recent decades, rehabilitation treatment using a robot has been developed to reproduce accurate motions repeatedly with less input of physical effort and time by therapists. Upper extremity rehabilitation treatment using robots has been available since the 1990s and the clinical effects on upper extremity function recovery are reported.

Studies on robotic assisted rehabilitation therapy in stroke patients have shown significant improvement in motor abilities of the exercised limb and enhanced functional outcomes [7, 8, 9, 10, 11]. However, some studies indicated that when the duration and intensity of conventional treatment is matched with robotic treatment, motor recovery, activities of daily living, strength, and motor control show no group-wise differences [7]. Nevertheless, additional sessions of robotic treatment promote better motor recovery in patients with stroke, as compared with additional conventional treatment [12].

Previously, studies indicated variable treatment effects of robot-assisted rehabilitation treatment on upper extremity spasticity. Fazekas et al. [13] reported significant change in Modified Ashworth Score (MAS) of shoulder adductors and elbow flexor only in the robotic treatment group. However, it reportedly has a small, non-significant effect on muscle tone based on MAS in other studies [10, 11, 14].

The aim of the present study was to evaluate the effect of upper extremity rehabilitation robots on spasticity in stroke patients. We conducted a randomized controlled trial to evaluate upper extremity spasticity, motor power and functions in response to therapy.


Continue —> KoreaMed Synapse

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[Abstract] Robot-assisted post-stroke motion rehabilitation in upper extremities: a survey


Recent neurological research indicates that the impaired motor skills of post-stroke patients can be enhanced and possibly restored through task-oriented repetitive training.

This is due to neuroplasticity – the ability of the brain to change through adulthood. Various rehabilitation processes have been developed to take advantage of neuroplasticity to retrain neural pathways and restore or improve motor skills lost as a result of stroke or spinal cord injuries (SCI).

Research in this area over the last few decades has resulted in a better understanding of the dynamics of rehabilitation in post-stroke patients and development of auxiliary devices and tools to induce repeated targeted body movements. With the growing number of stroke rehabilitation therapies, the application of robotics within the rehabilitation process has received much attention. As such, numerous mechanical and robot-assisted upper limb and hand function training devices have been proposed.

A systematic review of robotic-assisted upper extremity (UE) motion rehabilitation therapies was carried out in this study. The strengths and limitations of each method and its effectiveness in arm and hand function recovery were evaluated. The study provides a comparative analysis of the latest developments and trends in this field, and assists in identifying research gaps and potential future work.

Source: Robot-assisted post-stroke motion rehabilitation in upper extremities: a survey : International Journal on Disability and Human Development

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