Posts Tagged Upper limb rehabilitation

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



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.


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.


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.


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.


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.


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


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[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.


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.

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


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

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[ARTICLE] Vision-Based Pose Estimation for Robot-Mediated Hand Telerehabilitation – Full Text PDF/HTML


Vision-based Pose Estimation (VPE) represents a non-invasive solution to allow a smooth and natural interaction between a human user and a robotic system, without requiring complex calibration procedures. Moreover, VPE interfaces are gaining momentum as they are highly intuitive, such that they can be used from untrained personnel (e.g., a generic caregiver) even in delicate tasks as rehabilitation exercises.

In this paper, we present a novel master–slave setup for hand telerehabilitation with an intuitive and simple interface for remote control of a wearable hand exoskeleton, named HX. While performing rehabilitative exercises, the master unit evaluates the 3D position of a human operator’s hand joints in real-time using only a RGB-D camera, and commands remotely the slave exoskeleton. Within the slave unit, the exoskeleton replicates hand movements and an external grip sensor records interaction forces, that are fed back to the operator-therapist, allowing a direct real-time assessment of the rehabilitative task.

Experimental data collected with an operator and six volunteers are provided to show the feasibility of the proposed system and its performances. The results demonstrate that, leveraging on our system, the operator was able to directly control volunteers’ hands movements.

1. Introduction

Traditional rehabilitation is performed in a one-to-one fashion, namely one therapist (or sometimes several) working with one patient, leading to high personnel and management costs, especially for demanding patients such as those with brain or post surgery injuries. Due to the high hospitalization costs, all these patients are leaving clinics and returning to their homes sooner than in the past [1], when their rehabilitative program is not yet finished. These patients can greatly benefit from a telerehabilitation equipment, which is able to provide remote assistance and relief without the burden of going to the clinic on a daily basis. On the other hand, therapists can surely benefit from non-invasive systems capable of acquiring information about their movements which are then sent to the patient (or even to many patients), possibly in real-time to allow a direct control; modern vision-based techniques offer interesting sparks in such way. The possibility to provide high quality rehabilitation programs regardless of patients physical location and leveraging on vision is thus certainly attractive.

Continue —> Sensors | Free Full-Text | Vision-Based Pose Estimation for Robot-Mediated Hand Telerehabilitation | HTML

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Figure 2. HX while holding the sensorized object in a pinch (a) and lateral (b) grasping exercise. The DoMs of the HX device are: (1) the flexion/extension of the index MCP; (2) of the index P-DIP (under-actuated); (3) of the thumb MCP and IP (under-actuated) and (4) the CMC opposition. Other Degrees-of-Freedom (DoF), like thumb intra/extra rotation and the index abduction/adduction, are passive [29]. The HX is used to grasp the sensorized object, whose squeezable soft-pads provide force information on the basis of a optoelectronic deformation transduction [34].

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[ARTICLE] Development of a Soft Actuated Upper Extremity Exoskeleton Employing Series Elastic Actuator for Post Stroke Rehabilitation – Full Text PDF

9th International Conference on Rehabilitation Robotics, 2005. ICORR 2005


The integration of robotic devices and conventional physiotherapy is becoming more and more acceptable worldwide. When an exoskeleton is in the conceptual design phase, the actuator selection is one of the most crucial sections.

In this paper a rotary Seies Elastic Actuator(SEA) is introduced, designed and developed for upper limb application used in the rehabilitation exoskeleton. Albeit the SEA had been used in the lower extremity,it is not utilized for the upper limb rehabilitation yet. This paper will design,implement and analyze the advantages of using SEA in the upper limb instead of conventional electric motors and shows the stability of this system when implemented on the proposed exoskeleton.

Actually the designed exoskeleton is performing simultaneous tasks of elbow and shoulder flexion/extension by means of just one electric motor and a SEA mounted on the elbow joint.

Full Text PDF

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This paper presents design and development of real time biosignal-driven illusion system: Augmented Reality based Illusion System (ARIS) for upper limb motor rehabilitation. ARIS is a hospital / home based self- motivated whole arm rehabilitation system that aims to improve and restore the lost upper limb functions due to Cerebrovascular Accident (CVA) or stroke.

Taking the advantage of human brain plasticity nature, the system incorporates with number of technologies to provide fast recovery by re-establishing the neural pathways and synapses that able to control the mobility. These technologies include Augmented Reality (AR) where illusion environment is developed, computer vision technology to track multiple colors in real time, EMG acquisition system to detect the user intention in real time and 3D modelling library to develop Virtual Arm (VA) model where human biomechanics are applied to mimic the movement of real arm. The system operates according to the user intention via surface electromyography (sEMG) threshold level. In the case of real arm cannot reach to the desired position, VA will take over the job of real arm to complete the exercise.

The effectiveness of the developed ARIS has evaluated via questionnaire, graphical and analytical measurements which provided with positive results.


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In this article, we discuss the development of a novel upper limb rehabilitation robot integrated with video games. Our solution is operated via a novel human–computer interface, which stimulates shoulder, elbow movements, and fine finger movements. It is capable to train patients with partially recovered motor control ability. The interface enables therapists to select motivating and engaging motor training exercises represented as video games and specify rehabilitation exercises for patients using a grasping and upper limb interface. The paper presents concept of this novel interface, discusses the implementation issues and demonstrates technical and practical feasibility of our concept through a number of application examples.


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ARTICLE: Current Trends in Robot-Assisted Upper-Limb Stroke Rehabilitation: Promoting Patient Engagement in Therapy – Full Text

…Robotic therapy devices enable unique methods for promoting patient engagement by providing assistance only as needed and by detecting patient movement intent to drive to the device. Use of these methods has demonstrated improvements in functional outcomes, but careful comparisons between methods remain to be done…

via Current Trends in Robot-Assisted Upper-Limb Stroke Rehabilitation: Promoting Patient Engagement in Therapy – Springer.

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ARTICLE: Non-invasive Brain Stimulation in Physical Medicine and Rehabilitation – Full Text

…The non-invasive brain stimulation techniques of transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) have developed considerably over the last 25 years. Recent studies have used these techniques to enhance motor and cognitive function, modulate psychiatric symptoms, and reduce pain. Here, we briefly present TMS and tDCS techniques, discuss their safety, and provide examples of studies applying these interventions to enhance movement function following stroke. Though further studies are required, investigations so far provide important first steps in the use of non-invasive brain stimulation techniques to aid routine rehabilitation therapy. We discuss future directions for the field in terms of study development, choice of motor task, and target sites for stimulation…

via Non-invasive Brain Stimulation in Physical Medicine and Rehabilitation – Springer.

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