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[Infographic] Classification of sensor types used in virtual rehabilitation for upper limb rehabilitation

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[ARTICLE] Clinical Application of Virtual Reality for Upper Limb Motor Rehabilitation in Stroke: Review of Technologies and Clinical Evidence – Full Text

Abstract

Neurorehabilitation for stroke is important for upper limb motor recovery. Conventional rehabilitation such as occupational therapy has been used, but novel technologies are expected to open new opportunities for better recovery. Virtual reality (VR) is a technology with a set of informatics that provides interactive environments to patients. VR can enhance neuroplasticity and recovery after a stroke by providing more intensive, repetitive, and engaging training due to several advantages, including: (1) tasks with various difficulty levels for rehabilitation, (2) augmented real-time feedback, (3) more immersive and engaging experiences, (4) more standardized rehabilitation, and (5) safe simulation of real-world activities of daily living. In this comprehensive narrative review of the application of VR in motor rehabilitation after stroke, mainly for the upper limbs, we cover: (1) the technologies used in VR rehabilitation, including sensors; (2) the clinical application of and evidence for VR in stroke rehabilitation; and (3) considerations for VR application in stroke rehabilitation. Meta-analyses for upper limb VR rehabilitation after stroke were identified by an online search of Ovid-MEDLINE, Ovid-EMBASE, the Cochrane Library, and KoreaMed. We expect that this review will provide insights into successful clinical applications or trials of VR for motor rehabilitation after stroke.

1. Introduction

Stroke is one of the leading causes of disability and socioeconomic burden worldwide [1]. Although the age-standardized stroke incidence has decreased in most regions, the growth of aging populations, who are at risk of stroke, may lead to an increase in the crude incidence of stroke [2]. According to a policy statement by an American Heart Association working group, approximately 4% of US adults will have a stroke by 2030 [3]. Stroke-related mortality has shown a remarkable decline due to better management in the acute phase, which means there are more people living with disabilities after stroke [1,3].Upper limb hemiparesis is one of the most common impairments after stroke [4] and is associated with activity limitation and a worse quality of life [5,6,7]. Therefore, adequate recovery of upper limb weakness is necessary. Spontaneous motor recovery occurring up to one year after stroke can be accelerated with active rehabilitation strategies [8,9]. However, the effects of conventional rehabilitation modalities are limited and novel therapeutic approaches are required [10].Virtual rehabilitation using virtual reality (VR) technology is a novel promising modality for motor rehabilitation after stroke [11] that can add beneficial components to current rehabilitation strategies. Considering motor learning theory, task-oriented, intensive (that is, more doses and movements), and repetitive training is essential for promoting neuroplasticity and thereby, motor recovery (Figure 1) [12]. Several advantages of virtual rehabilitation can be suggested in terms of rehabilitation intensity and motivation. VR can motivate patients’ participation by increasing enjoyment and gamification—“the process of adding game-design elements and game principles to something (e.g., task) so as to encourage participation”—thereby increasing task repetition (intensity) [13,14,15]. Flexible and individualized rehabilitation design is possible according to the patient’s motor impairment, which makes the step-by-step approach possible. A low-cost virtual rehabilitation system can be used as an adjunctive therapy to conventional rehabilitation, with less direct supervision by a therapist [16], and it can also be considered for use as a tele- or home-based rehabilitation tool [17]. Functional assessment and digital tracking of patients’ progress is possible using motion sensors combined with VR systems for rehabilitation [18].

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Figure 1. Approaches to promote neural plasticity.In this comprehensive narrative review of the application of VR in motor rehabilitation after stroke, we will cover (1) the technologies used in VR rehabilitation including sensors, haptic devices, and VR displays; (2) the clinical application and evidence for VR in motor rehabilitation in stroke; and (3) considerations for VR application in stroke rehabilitation. We expect that this review will provide insights into successful clinical applications or trials of VR for motor rehabilitation after stroke.[…]

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[ARTICLE] A new hand rehabilitation system based on the cable-driven mechanism and dielectric elastomer actuator – Full Text

Abstract

The increasing number of patients with hand disabilities after strokes or peripheral nerve injuries necessitates the continuous development of rehabilitation system devices to accelerate muscle recovery and to help patients regain the motor functions of their hands. This paper introduces the design of a hand rehabilitation system for patients who have a solitary impairment of their hand extension. The system was designed to be portable, simple, and cheap. Using a system based on a cable-driven mechanism instead of traditional rigid links reduces the degrees of freedom of the finger to one. The dielectric elastomer actuator was designed and fabricated as a smart actuator for the system, which supports the low cost of the system. A kinematic analysis of the cable-driven mechanism has been done. Parameters of the actuator were optimized to reach the required output. In order to characterize the performance of the actuator, a uniaxial tension test, isotonic test, and isometric test have been implemented.

1 Introduction

The hand is a vital, multifunctional organ for humans that plays an important role in physical activities and in the development of fine and gross motor skills. Any disease disrupting the hand function will lead to disability and, consequently, worsen the quality of human life. The need to develop hand rehabilitation strategies became a vital issue with an increase in the number of patients (and old people in particular) who suffer from impairments in their hand motor function after strokes and injuries. The strategies for hand rehabilitation depend on maintaining the muscles’ ability and preventing their atrophy by doing repetitive hand exercises (Brewer et al.2012). As traditional, human-assisted therapy is challenging and expensive, many hand rehabilitation devices or robot-assisted therapies were recently introduced and achieved excellent results by enhancing the motor function of the muscles. Those devices offer a new kind of physiotherapy; in this way, patients practice moving their muscles by following or withstanding the robot’s force. Recently, there have been significant developments with the advances in robotic technology, such as the exoskeleton and bioengineering, that have become a significant addition to physiotherapy methods.

As a result of the variety of hand rehabilitation protocols, different robots have been designed to run alternative therapies. The rehabilitation clinics have different types of stationary hand rehabilitation devices which are set up in the clinics and have acquired good results, especially with the computer interface assistance that increases the patients’ motivation (Dovat et al.2008Schabowsky et al.2010). The availability of these devices is still insufficient for the majority of patients, due to the long time required for motor recovery training and the expensive fees for using the equipment. Also, these devices do not help them directly in their daily life activities.

Portable devices introduce an alternative to avoid some of these issues as the patients can train themselves at home. The bulky exoskeleton device is the most common type of portable assistive system which supplies highly accurate motion. It is a mechanism of rigid links fixed onto the palm side of the hand and controls the hand–finger motion (Ranman and Al-Jumaily2012Iqbal et al.2014Agarwal et al.2015Jo and Bae20152016Allotta et al.2017Jo et al.2019). Despite its excellent results, the bulky size and complicated structure present a burden for the patient and limit its workspace area. Also, the rigid structures of some of these devices are impeding the therapeutic potential of robotics by reducing their biomimetic qualities, and the motion in non-actuated directions, such as finger abduction, could include having rigid axes of rotation that become misaligned with the finger’s anatomic axis during motion (Chu and Patterson2018).

In contrast, soft rehabilitation devices, which are simple and lightweight, solve this problem by using the natural exoskeleton of the hand and wearable gloves to control hand motion. These devices have been fabricated from easily deformable materials such as fluids, gels, and soft polymers that have better biomimetic qualities, due to their increased compliance and inconstancy, while complying with the contours of the human body. The lack of rigid components removes constraints on non-actuated degrees of freedom and reduces joint alignment issues, which could prevent joint damage. The main problem of this type of device is its actuation system, as most of them are actuated by the pneumatic system, which has a large complex volume and low accuracy (Polygerinos et al.2013Zhang et al.2015Low et al.2015Jo and Bae2016Chu and Patterson2018). Recently, a soft glove for hand rehabilitation with a cable-driven mechanism was introduced (Yamaura et al.2009). Another trial was made by (Park et al.2016), who proposed a cable-driven structure of the hand exoskeleton system for virtual reality purposes. Cherian et al. (2018) introduced the Exo-Glove, the most popular one, which is suitable for the extension and flexion of the finger. However, tendon-driven systems have a major limitation in that they induce significant joint reaction forces. In and Cho (2013) indicated that, since the tendons are attached further away with a larger moment arm compared to the actual human tendons, these forces should not be a problem unless the spasticity of the patient’s fingers is very high.

Several types of actuators are used in hand rehabilitation systems. The electric motors are the standard type due to their availability, reliability, and easy torque control with high precision, but the rigid structure may affect safety. Although the pneumatic actuator has fewer requirements for maintenance and might be stopped under a load without causing damages, the difficulty in controlling it and the air storage bulk size limits its use. Also, the hydraulic actuator has the same problem as the size of its parts; however, it may supply higher actuated torque and can be controlled with high precision, as reported by Yue et al. (2017). There are some trials for using smart actuators in hand rehabilitation systems to decrease the disadvantage of the previous actuators; for example, Tang et al. (2013) designed an exoskeleton system to assist hand rehabilitation exercises based on a shape memory alloy actuator. While it offered a light and straightforward structure, its temperature-dependent nature makes precise control difficult.

Using dielectric elastomer materials (DEMs) as a smart actuator for the system might be a remedy for the common defects of actuation methods. The dielectric elastomer material has the closest material properties for natural muscles, particularly in the stress and strain levels. As mentioned by Pelrine et al. (2002) and Madden (2008), its strain is between 10 % and 100 %, which is similar to or higher than in muscle. Also, the stress is 0.1–8 MPa. Work density in the muscle may reach 40 kJ m−3, compared to between 10 and 150 kJ m−3 in silicone and VHB-based elastomers, respectively. The continuous power output of dielectric elastomers also matches or exceeds that of our skeletal muscle, with human muscle producing about 50 W kg−1 compared to about 400 W kg−1 in the elastomers. In addition, it does not have a temperature-dependent response like the shape memory alloys so that it can work in different environments.

As the design of the hand rehabilitation robotics is different from the traditional design of robots because it involves humans, the safety and availability of the device are essential requirements for the rehabilitation system. This research aims to design a bio-mimic, soft hand rehabilitation system that must be portable, simple, and cheap. A cable-driven mechanism is proposed to work instead of the rigid links and be actuated by the dielectric elastomer actuator. This design mimics the natural procedure of finger motion as the cable-driven and the dielectric elastomer actuator (DEA) represent, instead, the natural tendon and muscle, respectively. While there are a variety of hand rehabilitation devices for the patients whose therapy needs are different to others, the target patients for this rehabilitation system are those who have a solitary impairment of their hand extension, as in peripheral radial nerve compression or injury. Nicholls and Furness (2019) indicated that most patients respond well to conservative therapy. They are considering relative rest from offending muscle activity, such as limiting repetitive pronation, supination, wrist flexion, and ulnar deviation. If symptoms are not resolved with the cessation of activity and rest, then splinting is considered.

The rest of the paper is organized as follows. The kinematic and dynamic analysis of the natural hand is given in Sect. 2. The proposed design of the cable system is presented in Sect. 3. The development and fabrication of the DEA are presented in Sect. 4, while Sect. 5 presents the performance characterization of the DEA. The conclusion and future work are presented in Sects. 6 and 7, respectively.

Figure 1 The human hand–finger structure.

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[ARTICLE] Implementation of an Upper-Limb Exoskeleton Robot Driven by Pneumatic Muscle Actuators for Rehabilitation – Full Text

Abstract

Implementation of a prototype of a 4-degree of freedom (4-DOF) upper-limb exoskeleton robot for rehabilitation was described in this paper. The proposed exoskeleton robot has three DOFs at the shoulder joint and one DOF at the elbow joint. The upper-limb exoskeleton robot is driven by pneumatic muscle actuators (PMA) via steel cables. To implement the passive rehabilitation control, the rehabilitation trajectories expressed in the Fourier series were first planned by the curve fitting. The fuzzy sliding mode controller (FSMC) was then applied to the upper-limb exoskeleton robot for rehabilitation control. Several rehabilitation scenarios were carried out to validate the designed PMA-actuated exoskeleton robot.

1. Introduction

Accidents, aging, stroke, and neural diseases cause impairments of motor function. Those with movement difficulties are always hindered by daily living activities. To help impaired patients to gain motor abilities recovery, a rehabilitation treatment needing a repetitive and progressive functional training exercise is required [1]. However, the conventional rehabilitation exercises performed by therapists and caregivers in free-hand assisting treatments are typically time-consuming and labor-intensive. Robotic devices are therefore necessarily introduced to facilitate rehabilitation training to reduce the cost of therapist labor [2].Research studies that were conducted with robotic devices show that robotic training devices are well suited for rehabilitation because the consistency in repetitive rehabilitation therapy can be assured [3]. Especially in the upper-limb rehabilitation, end-effector-type rehabilitation robots were designed to provide the effective motor recovery assistance [4], but most structures of these robots are bulky and stationary, and the availability is thus limited in the settings.Recent findings in exoskeleton robots attract more interest in developing rehabilitation assistance devices due to a low-cost lightweight portable structure [5]. The 8.5 kg of exoskeleton robot is a mechanical structure type of a wearable device that synchronizes with human limbs, providing powered assistance for weak individuals, or being used in human training for rehabilitation. Commonly, a human user wears an exoskeleton robot to recover motor abilities; the robot must deliver the force to drive an arm to follow the rehabilitation trajectory smoothly and safely [6], and thus the control technologies for the exoskeleton robots are critical to the improvement of the rehabilitation effect. Kang and Wang [7] studied an adaptive control strategy for a class of 5- degree of freedom (DOF) upper-limb exoskeleton robot with shoulder, elbow, and wrist joint movements to improve the fault tolerance and safety with unknown large parameter variances or even actuator faults. Brahmi et al. [8] presented a robust control design for a 7-DOF exoskeleton, CAREX-7, weighing about 1.6 kg, in which the external force is adapted based on backstepping control with a force observer being integrated to estimate the user’s force. Wu et al. [9] developed a neural-fuzzy adaptive controller using the radial basis function network for a rehabilitation exoskeleton to assist human arm movement. A further experimental investigation was conducted for the position tracking and frequency response. Galiana et al. [10] used electric motors transmitted with Bowden cables to the compliant brace for a wearable soft robotic device. Rehabilitation exercises were performed even there exist misalignments. Although the aforementioned different control methods have been successfully applied to exoskeleton robots for rehabilitation training, in regard to the aim of developing electric motor-actuated exoskeleton robots, their weights are still considerable due to the design of hanging motors.Compared to electric motors, soft actuators like pneumatic muscle actuators (PMAs) have the merits of inherent compliance, compactness, high power-to-weight ratio, and low cost [11,12]. Current developments in PMAs have made exoskeleton robots lighter and safer. PMA is a braided pneumatic drive that will contract in the axial direction as gas is filled into the braided tube through a hose linked to the compressor. Tsagarakis and Caldwell [13,14] described the construction and testing of a seven degree of motion upper arm rehabilitation system that weighs 2 kg. Each joint is actuated via antagonistic pairs of PMAs. PID (Proportion-Integral-Derivative) -based joint torque control was implemented on each joint, and an impedance control scheme was employed for the overall exoskeleton system. Moreover, the designed shoulder adduction/abduction and wrist actuators are directly coupled with the pulleys and mounted to the arm structure. This results in a complicated mechanical structure. Besides, torque sensors, position sensors, and pressure sensors are required for the torque tracking control for training. In comparison with the works of Tsagarakis et al., we install all PMAs to the back frame to make the exoskeleton robot more compact. Moreover, only encoders for the measurement of joint angles are required for the rehabilitation trajectory control. Xiong and Jiang [15] presented an exoskeleton robotic arm driven by pneumatic muscle actuators for stroke rehabilitation. A PID control method was applied to the patient-active–robot-passive and patient-passive–robot-active rehabilitation training modes. Andrikopoulos et al. [16] presented the design and implementation of a 2-DOF wrist exoskeletal prototype whose motion is achieved via pneumatic muscle actuators. The movement capabilities were experimentally evaluated via a PID-based control algorithm. Tu et al. [17] developed a portable upper limb exoskeleton rehabilitation robot that is unidirectionally actuated by PMAs to performs frequent intensive rehabilitation training, and the iterative learning control (ILC) was designed to control this hybrid rehabilitation system to execute repetitive task training. Oguntosin et al. [18] demonstrated a prototype of a wearable soft robotic assistive device for elbow motion therapies. The highly compliant rotation was realized by a proportional control on pneumatic control of the air. Natividad and Yeow [19] developed a wearable soft robotic shoulder exosuit that weighs 3.59 kg. Position control was achieved by applying varying magnitudes of pressure to pneumatic actuators. Ohta et al. [20] presented a robotic arm–wrist–hand system with seven degrees of freedom (DOFs). The arm is pneumatically powered using McKibben type pneumatic artificial muscles, and the wrist and hand motions are actuated by servomotors. Simulation and experimental results were also presented using sliding mode and PID position control. However, the hybrid pneumatic/servomotor-powered actuation makes the structure and control system more complicated.From the referred literature, it can be found that almost the linear type of controllers are employed for the rehabilitation control of PMA-actuated upper-limb exoskeletons. However, it is rather difficult to control PMA-actuated systems on account of nonlinear phenomena such as friction, the compressibility of air, and external loading such that linear type of controllers are not enough for the improvement of rehabilitation effects [21,22].In general, for an upper-limb exoskeleton robot design, actuators, sensors, processors, and the required mechanisms or mechanical linkages must be fitted to the hardware and must conform to the movement of the human arm. Therefore, in this paper, a 4-DOF upper-limb exoskeleton robot driven by PMAs was developed to support the shoulder–elbow motion. Instead of a conventional serial type of manipulator design, the shoulder joint is designed as a ball-socket joint inspired by human anatomy. Moreover, due to their lightweight property, PMAs are used in the proposed exoskeleton robot for safety. Based on a passive rehabilitation mode, the fuzzy sliding mode control was proposed to achieve the rehabilitation trajectory tracking on account of the system uncertainties and nonlinearity such that the rehabilitation performance can be improved. Experimental tests were executed to provide a validation on the proposed architectures and controllers.

2. System Design

PMA-Actuated Upper-Limb Exoskeleton Robot Building

The design of an upper-limb exoskeleton robot must comply with the movement of a human arm and match with the anatomical structure as closely as possible. However, the detailed designs will result in a complex and bulky exoskeleton structure. As shown in Figure 1, the proposed upper-limb exoskeleton robot in this paper has four DOFs according to the required function, mainly including shoulder abduction/adduction θ_1 of the joint J1, shoulder flexion/extension θ_2 of the joint J2, shoulder internal/external rotation θ_3 of the joint J3, elbow flexion/extension θ_4 of the joint J4.

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Figure 1. Degrees of freedom (DOFs) and mechanical design of the upper-limb exoskeleton robot.

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[Abstract] Design and Implementation of An Interactive Hand Rehabilitation Training System Based on LabVIEW

Abstract

With the development of science and technology in multidisciplinary fields of automation control, rehabilitation medicine and robotics and the improvement of people’s living standards, medical rehabilitation robots are playing an increasingly important role in life. The traditional hand rehabilitation robots are exoskeleton rigid robots with complex structure and small fault tolerance. It is dangerous for the rehabilitation of human finger joints, while soft wearable hand rehabilitation robots have better safety and flexibility. For the rehabilitation needs of stroke fingers, a virtual online game of human-computer interaction is developed using LabVIEW and a soft wearable hand rehabilitation robot, in order to improve the initiative of patients in the process of active rehabilitation training and to increase the interest of patients in active rehabilitation training, which also improves the initiative of patients to participate in active rehabilitation training.

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[ARTICLE] The effects of anxiety and dual-task on upper limb motor control of chronic stroke survivors – Full Text

Abstract

This study was designed to investigate the effects of anxiety and dual-task on reach and grasp motor control in chronic stroke survivors compared with age- and sex-matched healthy subjects (HC). Reach and grasp kinematic data of 68 participants (high-anxiety stroke (HA-stroke), n = 17; low-anxiety stroke (LA-stroke), n = 17; low-anxiety HC, n = 17; and high-anxiety HC, n = 17) were recorded under single- and dual-task conditions. Inefficient reach and grasp of stroke participants, especially HA-stroke were found compared with the control groups under single- and dual-task conditions as evidenced by longer movement time (MT), lower and earlier peak velocity (PV) as well as delayed and smaller hand opening. The effects of dual-task on reach and grasp kinematic measures were similar between HCs and stroke participants (i.e., increased MT, decreased PV that occurred earlier, and delayed and decreased hand opening), with greater effect in stroke groups than HCs, and in HA-stroke group than LA-stroke group. The results indicate that performing a well-learned upper limb movement with concurrent cognitive task leads to decreased efficiency of motor control in chronic stroke survivors compared with HCs. HA-stroke participants were more adversely affected by challenging dual-task conditions, underlying importance of assessing anxiety and designing effective interventions for it in chronic stroke survivors.

Introduction

Approximately 60% of stroke survivors suffer from permanent upper limb dysfunctions despite receiving rehabilitation1. Stroke-induced motor impairments (e.g., muscle weakness, spasticity, and impaired coordination), sensory deficits (proprioceptive and/or tactile sensory loss) and perceptual-cognitive dysfunctions (e.g., attentional problems and visuospatial impairments), as well as secondary physiological adaptations (e.g., contractures, and muscle atrophy) can directly affect skilled/well-learned upper limb movements such as reach and grasp2. Slowed and segmented movement, dysmetria, inadequate aperture and impairments of hand preshaping have been reported as common problems, involved in clumsy function or disuse of the upper limb following stroke2,3,4,5. Reach and grasp, a fundamental part of object manipulation, requires the integration of sensory, motor and cognitive information6,7 and frequently performed with a concurrent cognitive task (e.g., reach and grasp of a cup of coffee while talking on the phone or reach and grasp goods from store shelves while recalling shopping list8.

Typically, a dual-task paradigm is used to investigate whether and to what extent control of a motor action requires attentional resources. Based on limited processing capacity theory, if a motor and cognitive task compete for shared attentional resources, performing the two task simultaneously may result in disruption of performance in one or both task, known as dual-task interference (for example, enhanced error and slower performance compared with the single-task condition)9. Individuals are frequently challenged by dual-task conditions in daily life, hence, flexible adaptation to the changing motor and cognitive requirements of daily functions, as well as environment is necessary for successfully and independently performing activities of daily livings (ADLs)10.

Stroke survivors may experience greater dual-task interference compared to healthy subjects because of impaired cognitive and motor function11. Although the effects of dual-task have been widely studied on balance and gait in stroke survivors11,12, few studies have been conducted on the effects of dual-task on upper limb function of these patients. In this regard, Shin et al. reported a significant dual-task effect on upper limb movement smoothness and reach error in chronic stroke survivors using a robotic-assisted planar reaching. However, they did not compare stroke survivors with healthy participants10. Bank et al. used a virtual goal-directed upper limb movement (i.e., controlling the movement of the virtual mouse to collect virtual targets), which performed with or without auditory stroop task in order to compare the cognitive-motor interference in patients with neurological disorders (stroke and Parkinson’s disease) with sex-and age-matched healthy controls. They did not find greater cognitive-motor interference in stroke participants than the healthy controls. They explained this finding might be related to their measure that was not precise. They suggested using a more precise measure for assessing upper limb motor control such as a motion analysis system13. Houwink et al. used a motion analysis system to investigate the effect of an auditory stroop task on upper limb motor control in chronic stroke survivors while drawing a circle. They found dual-task interference only in the affected upper limb of patients who had moderate upper limb paresis. However, they used an experimentally designed upper limb task, not a natural everyday task such as reach and grasp, which based on their stated limitation is susceptible to learning that is different among stroke survivors and healthy subjects14. It remains to be determined, however, whether dual-task would affect motor control of a well-learned/skillful upper limb movement such as reach and grasp in chronic stroke survivors.

Anxiety is the second most common psychological disorders among stroke survivors15, affecting up to 24% of patients15,16. It has been suggested that anxiety symptoms persist for up to 10 years after stroke17 and are associated with low functional outcomes17, increased dependency in ADLs18, and decreased quality of life17. Anxiety increases distraction by task-irrelevant stimuli (i.e., impaired attentional control), leading to decreased processing efficiency needed for motor planning and execution of a well-learned/skillful movement19. Kotani et al. recently showed that anxiety disrupted the hand’s fine motor control of expert pianists through incoordination of multi-joints movements20. Despite the high prevalence of anxiety in stroke survivors and its potential to affect motor control, to the best of our knowledge, no attention has been paid to the effects of anxiety on upper limb motor control of these patients. Understanding the effects of anxiety on upper limb motor control is therefore needed to develop and target interventions to address this common psychological disorder, improve upper limb motor control, and enhance the independence of stroke survivors in ADLs. Therefore, the aim of this study was to investigate whether dual-task interference would be observed in upper limb motor control of stroke survivors when performing a well-learned everyday motor task compared with age-and sex-matched healthy subjects. The study also aimed to determine the effect of anxiety on upper limb motor control of these patients.[…]

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[Abstract + References] Neuromotor Recovery Based on BCI, FES, Virtual Reality and Augmented Feedback for Upper Limbs

Abstract

Recently investigated rehabilitative practices involving Brain-Computer Interface (BCI) and Functional Electrical Stimulation (FES) techniques provided long-lasting benefits after short-term recovering programs. The prevalence of this revolutionary approach received a boost from virtual reality and augmented reality, which contribute to the brain neuroplasticity improvement and can be used in neurorehabilitation and treatment of motor/mental disorders. This work presents a therapy system for stroke rehabilitation based on these techniques. The novelty of the proposed system consists of including an eye tracking device that detects the patient’s vigilance during exercises and warns if patient is not focused on the items of interest from the virtual environment. This additional feature improves the level of user involvement and makes him/her conscious of the rehabilitation importance and pace. Moreover, the system architecture is reconfigurable, and the functionalities are specified by software. The laboratory tests have validated the system from a technical point of view, and preliminary results from the clinical tests have highlighted the system’s quick accommodation to the proposed therapy and fast progress for each user.This is a preview of subscription content, log in to check access.

References

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[Abstract] A Plug-and-Train Robotic Kit (PLUTO) For Hand Rehabilitation: Pilot Usability Study – Conference Publication

Abstract

Hand rehabilitation requires intensive training with various gross and fine movements. Thus, rehabilitation robots for the hand that accommodate for the different degrees of freedom are often complex and expensive. This work presents the design of a portable plug-and-train robot (PLUTO), which tackles the problem by having a single actuator that can be coupled with different passive mechanisms for training wrist flexion-extension, ulnar-radial deviation, hand opening-closing, and forearm pronation-supination. The robot is capable of providing training in active and assisted regimes. Training is through performance adaptive computer games to provide feedback to the patients and to motivate them during training. The usability was evaluated in patients, caregivers, and clinicians with standardized questionnaires: System Usability Scale (SUS) and User Experience Questionnaire (UEQ). Patients and caregivers were administered the questionnaire after two training sessions. Clinicians, on the other hand, had a single session demo after which their feedback was obtained. In this paper, we present the initial results of 5 clinicians, 5 caregivers, and 5 patients. All groups found the system to be highly usable (180 scores on the system usability scale). Furthermore, the scores from UEQ feedback were all positive, and all groups found the system attractive. The patients and the clinicians rated the system positively in both pragmatic and hedonic scales. We believe that a simple approach proposed here can result in a compact tool with a high benefit-to-cost ratio for both in-clinic and home-based hand rehabilitation.

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[ARTICLE] A comparison of the effects and usability of two exoskeletal robots with and without robotic actuation for upper extremity rehabilitation among patients with stroke: a single-blinded randomised controlled pilot study – Full Text

Abstract

Background

Robotic rehabilitation of stroke survivors with upper extremity dysfunction may yield different outcomes depending on the robot type. Considering that excessive dependence on assistive force by robotic actuators may interfere with the patient’s active learning and participation, we hypothesised that the use of an active-assistive robot with robotic actuators does not lead to a more meaningful difference with respect to upper extremity rehabilitation than the use of a passive robot without robotic actuators. Accordingly, we aimed to evaluate the differences in the clinical and kinematic outcomes between active-assistive and passive robotic rehabilitation among stroke survivors.

Methods

In this single-blinded randomised controlled pilot trial, we assigned 20 stroke survivors with upper extremity dysfunction (Medical Research Council scale score, 3 or 4) to the active-assistive robotic intervention (ACT) and passive robotic intervention (PSV) groups in a 1:1 ratio and administered 20 sessions of 30-min robotic intervention (5 days/week, 4 weeks). The primary (Wolf Motor Function Test [WMFT]-score and -time: measures activity), and secondary (Fugl-Meyer Assessment [FMA] and Stroke Impact Scale [SIS] scores: measure impairment and participation, respectively; kinematic outcomes) outcome measures were determined at baseline, after 2 and 4 weeks of the intervention, and 4 weeks after the end of the intervention. Furthermore, we evaluated the usability of the robots through interviews with patients, therapists, and physiatrists.

Results

In both the groups, the WMFT-score and -time improved over the course of the intervention. Time had a significant effect on the WMFT-score and -time, FMA-UE, FMA-prox, and SIS-strength; group × time interaction had a significant effect on SIS-function and SIS-social participation (all, p < 0.05). The PSV group showed better improvement in participation and smoothness than the ACT group. In contrast, the ACT group exhibited better improvement in mean speed.

Conclusions

There were no differences between the two groups regarding the impairment and activity domains. However, the PSV robots were more beneficial than ACT robots regarding participation and smoothness. Considering the high cost and complexity of ACT robots, PSV robots might be more suitable for rehabilitation in stroke survivors capable of voluntary movement.

Introduction

Approximately 30–66% of stroke survivors suffer from upper extremity dysfunction, which leads to impediment of activities of daily living (ADL) and social participation [1]. Various interventions have been applied for upper extremity rehabilitation, and robotic rehabilitation has been recently popularised [2,3,4].

Robotic rehabilitation has potential advantages regarding the high repetition of specific tasks and interactivity, leading to active participation with less burden on therapists [25]. Recent systematic reviews have suggested the beneficial effects of robotic rehabilitation on upper extremity dysfunction among patients with stroke [46]. Veerbeek et al. described that robotic rehabilitation is more beneficial for the improvement of the motor control and strength of a paretic arm, but not for that of ADL, than is conventional therapy [6]. Furthermore, Mehrholz et al. demonstrated that robotic rehabilitation has more beneficial effects on ADL as well as on arm function and muscle strength compared to conventional therapy [4]. However, these conclusions should be considered cautiously because the robots that were included in these reviews were heterogenous: 28 and 24 different rehabilitation robots were included in the systemic reviews by Veerbeek et al. and Mehrholz et al., respectively. We recently showed that the use of end-effector and exoskeleton rehabilitation robots led to significant functional outcome differences stemming from distinct characteristics of the robots; this indicates that the differential effects might result from the inherent characteristics of the rehabilitation robot that was used [7]. In addition to the structural difference, the type of robotic control architecture (e.g., position, force, and impedance control) or robotic actuation (e.g., hydraulic power, pneumatic, and electric motor actuation) could also affect the therapeutic outcome [89]. Nonetheless, there is a lack of studies that examined the differential effects according to the characteristics of robots. If the discrepant effects during upper extremity rehabilitation are understood according to the characteristics of robots, more suitable robotic rehabilitation may be applied and provided to each patient.

Accordingly, robotic devices can be classified as active-assistive and passive robotic devices according to the training modality. A passive robot does not provide assistive force, while an active-assistive robot provides assistive force with robotic actuators when the user is unable to make active movements [10,11,12]. Robotic active assistance is thought to be beneficial for users without voluntary movement because they can be trained with according to an ideal path or speed. Nonetheless, active assistance using manipulation for upper limb rehabilitation is too complex to be adopted with ease because the upper extremities are composed of several joints and different muscles, which allow movements with multiple degrees of freedom. Moreover, musculoskeletal problems associated with stroke such as spasticity, contractures, deformity, or hemiplegic shoulder pain make the application of robotic assistance more difficult. Additionally, excessive dependence on assistive force might interfere with active learning and participation for users who can perform voluntary movement. Therefore, we hypothesised that an active-assistive robot does not make a meaningful difference in terms of upper extremity rehabilitation relative to that made by a passive robot. Thus, we aimed to explore whether there is a difference in clinical and kinematic outcomes between active-assistive and passive robots during robot-assisted upper extremity rehabilitation of patients with stroke showing a Medical Research Council (MRC) scale score of 3 or 4 for the paretic proximal upper limb. In addition, we assessed the usability of robotic assistance. To our knowledge, this is the first clinical trial to directly compare rehabilitative effects between active-assistive and passive robots.[…]

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[Abstract] Design of Dynamic Tangible Workspaces for Games: Application on Robot-Assisted Upper Limb Rehabilitation

Abstract

A key element for the success of any game is its ability to produce a different experience at each round, thus keeping the player engagement high. This is particularly important for those games that also have a serious objective, such as gamified rehabilitation systems, aiming at encouraging patients in performing home rehabilitation exercises. In all cases, a game element which is typically static is the workspace, i.e. the “floor” upon which the game takes place. This is especially true for robot-assisted rehabilitation games, where the workspace must satisfy the requirements given by the robot’s locomotion and localization systems, as well as the patient’s exercise motion requirements.In this article we present a simple yet effective solution for designing dynamic and customizable tangible workspaces, which relies on hexagonal tiles and our previously proposed Cellulo localization system. These “hextiles” can be easily tangibly rearranged at each game round to yield a desired workspace shape and configuration, allowing tabletop mobile robots to move continuously within each new workspace. We ground our solution in the context of robot-assisted rehabilitation, where high adaptability is crucial for the efficacy of the solution, and propose a dynamic extension of our “tangible Pacman” rehabilitation game.Experiments show that the proposed solution allows for adaptation in range of motions, exercise types, physical and cognitive difficulty, besides reducing repetitiveness.

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