Posts Tagged robotic exoskeleton

[ARTICLE] Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling – Full Text

Abstract

Background

Research efforts in neurorehabilitation technologies have been directed towards creating robotic exoskeletons to restore motor function in impaired individuals. However, despite advances in mechatronics and bioelectrical signal processing, current robotic exoskeletons have had only modest clinical impact. A major limitation is the inability to enable exoskeleton voluntary control in neurologically impaired individuals. This hinders the possibility of optimally inducing the activity-driven neuroplastic changes that are required for recovery.

Methods

We have developed a patient-specific computational model of the human musculoskeletal system controlled via neural surrogates, i.e., electromyography-derived neural activations to muscles. The electromyography-driven musculoskeletal model was synthesized into a human-machine interface (HMI) that enabled poststroke and incomplete spinal cord injury patients to voluntarily control multiple joints in a multifunctional robotic exoskeleton in real time.

Results

We demonstrated patients’ control accuracy across a wide range of lower-extremity motor tasks. Remarkably, an increased level of exoskeleton assistance always resulted in a reduction in both amplitude and variability in muscle activations as well as in the mechanical moments required to perform a motor task. Since small discrepancies in onset time between human limb movement and that of the parallel exoskeleton would potentially increase human neuromuscular effort, these results demonstrate that the developed HMI precisely synchronizes the device actuation with residual voluntary muscle contraction capacity in neurologically impaired patients.

Conclusions

Continuous voluntary control of robotic exoskeletons (i.e. event-free and task-independent) has never been demonstrated before in populations with paretic and spastic-like muscle activity, such as those investigated in this study. Our proposed methodology may open new avenues for harnessing residual neuromuscular function in neurologically impaired individuals via symbiotic wearable robots.

Background

The ability to walk directly relates to quality of life. Neurological lesions such as those underlying stroke and spinal cord injury (SCI) often result in severe motor impairments (i.e., paresis, spasticity, abnormal joint couplings) that compromise an individual’s motor capacity and health throughout the life span. For several decades, scientific effort in rehabilitation robotics has been directed towards exoskeletons that can help enhance motor capacity in neurologically impaired individuals. However, despite advances in mechatronics and bioelectrical signal processing, current robotic exoskeletons have had limited performance when tested in healthy individuals [1] and have achieved only modest clinical impact in neurologically impaired patients [2], e.g., stroke [34], SCI patients [5]. […]

 

Continue —>  Voluntary control of wearable robotic exoskeletons by patients with paresis via neuromechanical modeling | Journal of NeuroEngineering and Rehabilitation | Full Text

Fig. 1

Fig. 1 Enter aSchematic representation of the real-time modeling framework and its communication with the robotic exoskeleton. The whole framework is operated by a Raspberry Pi 3 single-board computer. The framework consists of five main components: a The EMG plugin collects muscle bioelectric signals from wearable active electrodes and transfers them to the EMG-driven model. b The B-spline component computes musculotendon length (Lmt) and moment arm (MA) values from joint angles collected via robotic exoskeleton sensors. c The EMG-driven model uses input EMG, Lmt and MA data to compute the resulting mechanical forces in 12 lower-extremity musculotendon units (Table 1) and joint moment about the degrees of freedom of knee flexion-extension and ankle plantar-dorsiflexion. d The offline calibration procedure identifies internal parameters of the model that vary non-linearly across individuals. These include optimal fiber length and tendon slack length, muscle maximal isometric force, and excitation-to-activation shape factors. eThe exoskeleton plugin converts EMG-driven model-based joint moment estimates into exoskeleton control commands. Please refer to the Methods section for an in-depth description caption

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[Abstract + References] Training of Hand Rehabilitation Using Low Cost Exoskeleton and Vision-Based Game Interface

Abstract

Motivating game-based training have the potential to improve therapy for people with neurological impairments. In recent years, the serious games have become extremely useful tools in rehabilitation field. They aim to stimulate the mobility of the body through an immersive experience that puts the user in interactive virtual environment. This paper is concerned about developing a customized augmented reality system for stroke rehabilitation. This will be done through integrating an interactive serious game interface with a hand exoskeleton device. This game-based rehabilitation system allows users to carry out physical rehabilitation therapies using a natural user interface based on Kinect’s skeletal tracking features and the electromyography (EMG) sensor. During game playing, the interactive user interface provides useful real-time feedback information such as the time required to grasp a desired dynamic virtual object, and the assigned score and thus the ability of the proposed system to provide a compensatory action regarding the dynamic behavior of the virtual target. The main goal of the developed virtual environment is to create positive influences on the rehabilitation process. Patient movement information and signals obtained from the developed exoskeleton device are used together to monitor the rehabilitation progress. The developed exoskeleton hand is a 3D printed low cost device suitable for grasping tasks that can be used even for domestic stroke patients. The developed exoskeleton device is not only a mechanical system able to perform the rehabilitation act but also it presents an effective tracking and traceability software solution. The EMG signals measured during hand motion are used to detect the intention of hand opening or closing which in turn will actuate the mechanical structure to accomplish the desired task. Parameters and results of patients’ exercises are stored and analyzed when needed to evaluate patients’ progress. The developed system is tested experimentally and it is able to restore the functions of the upper limb and mainly give patients more motivation to undergo the rehabilitation exercises.

Supplementary material

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[Abstract] A novel exoskeleton robotic system for hand rehabilitation – Conceptualization to prototyping

Abstract

This research presents a novel hand exoskeleton rehabilitation device to facilitate tendon therapy exercises. The exoskeleton is designed to assist fingers flexion and extension motions in a natural manner. The proposed multi-Degree Of Freedom (DOF) system consists of a direct-driven, optimized and underactuated serial linkage mechanism having capability to exert extremely high force levels perpendicularly on the finger phalanges. Kinematic and dynamic models of the proposed device have been derived. The device design is based on the results of multi-objective optimization algorithm and series of experiments conducted to study capabilities of the human hand. To permit a user-friendly interaction with the device, the control is based on minimum jerk trajectory generation. Using this control system, the transient response and steady state behavior of the proposed device are analyzed after designing and fabricating a two-fingered prototype. The pilot study shows that the proposed rehabilitation system is capable of flexing and extending the fingers with accurate trajectories.

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[REVIEW] Powered robotic exoskeletons in post-stroke rehabilitation of gait: a scoping review – Full Text

Abstract

Powered robotic exoskeletons are a potential intervention for gait rehabilitation in stroke to enable repetitive walking practice to maximize neural recovery. As this is a relatively new technology for stroke, a scoping review can help guide current research and propose recommendations for advancing the research development.

The aim of this scoping review was to map the current literature surrounding the use of robotic exoskeletons for gait rehabilitation in adults post-stroke. Five databases (Pubmed, OVID MEDLINE, CINAHL, Embase, Cochrane Central Register of Clinical Trials) were searched for articles from inception to October 2015. Reference lists of included articles were reviewed to identify additional studies. Articles were included if they utilized a robotic exoskeleton as a gait training intervention for adult stroke survivors and reported walking outcome measures.

Of 441 records identified, 11 studies, all published within the last five years, involving 216 participants met the inclusion criteria. The study designs ranged from pre-post clinical studies (n = 7) to controlled trials (n = 4); five of the studies utilized a robotic exoskeleton device unilaterally, while six used a bilateral design. Participants ranged from sub-acute (<7 weeks) to chronic (>6 months) stroke. Training periods ranged from single-session to 8-week interventions. Main walking outcome measures were gait speed, Timed Up and Go, 6-min Walk Test, and the Functional Ambulation Category.

Meaningful improvement with exoskeleton-based gait training was more apparent in sub-acute stroke compared to chronic stroke. Two of the four controlled trials showed no greater improvement in any walking outcomes compared to a control group in chronic stroke.

In conclusion, clinical trials demonstrate that powered robotic exoskeletons can be used safely as a gait training intervention for stroke. Preliminary findings suggest that exoskeletal gait training is equivalent to traditional therapy for chronic stroke patients, while sub-acute patients may experience added benefit from exoskeletal gait training. Efforts should be invested in designing rigorous, appropriately powered controlled trials before powered exoskeletons can be translated into a clinical tool for gait rehabilitation post-stroke.

Background

Stroke is a leading cause of acquired disability in the world, with increasing survival rates as medical care and treatment techniques improve [1]. This equates to an increasing population with stroke-related disability [1, 2], who experience limitations in communication, activities of daily living, and mobility [3]. A majority of this population ranks recovering the ability to walk or improving walking ability among their top rehabilitation goals [4, 5]; furthermore, the ability to walk is a determining factor as to whether an individual is able to return home after their stroke [6]. However, 30 – 40 % of stroke survivors have limited or no walking ability even after rehabilitation [7, 8] and so there is an ongoing need to advance the efficacy of gait rehabilitation for stroke survivors.

Powered robotic exoskeletons are a recently developed technology that allows individuals with lower extremity weakness to walk [9]. These wearable robots strap to the legs and have electrically actuated motors that control joint motion to automate overground walking. Powered exoskeletons were originally designed to be used as an assistive device to allow individuals with complete spinal cord injury to walk [10]. However, because they allow for walking without overhead body weight support or a treadmill, they have gained attention as an alternate intervention for gait rehabilitation in other populations such as stroke where repetitive gait training has been shown to yield improvements in walking function [11, 12]. Several powered exoskeletons are already commercially available, such as the Ekso (Ekso Bionics, USA), Rewalk (Rewalk Robotics, Israel), and Indego (Parker Hannifin, USA) exoskeletons, with more being developed.

There have been many forms of gait retraining proposed for stroke survivors. Conventional physical therapy gait rehabilitation leads to improvements in speed and endurance [13], particularly when conducted early post-stroke [14]. However, conventional gait retraining using hands-on assistance can be taxing on therapists; the number of steps actually taken in a session reflects this and has been shown to be low in sub-acute hospital rehabilitation [15]. Many of the proposed technology-based gait intervention strategies have focused on reducing the physical strain to therapists while increasing the amount of walking repetition that individuals undergo. For example, body weight-supported treadmill training (BWSTT) allows therapists to manually move the hemiparetic limb in a cyclical motion while the patient’s trunk and weight are partially supported by an overhead harness system; this has shown improvements in stroke survivors’ gait speed and endurance compared to conventional gait training [16], yet still places a high physical demand on therapists. Advances in technology have led to treadmill-based robotics, such as the Lokomat (Hocoma, Switzerland), LOPES (University of Twente, Netherlands), and G-EO (Reha-Technology, Switzerland), which have bracing that attaches to the patient’s legs to take them through a walking motion on the treadmill. The appeal of this technology is that it can provide substantially higher repetitions for walking practice than BWSTT without placing strain on therapists; however, there is conflicting evidence regarding the efficacy of treadmill-based robotics for gait training compared to conventional therapy or BWSTT. Some studies have shown that treadmill robotics improve walking independence in stroke [17, 18] but do not improve speed or endurance [18, 19]. There has been some sentiment that such technology has not lived up to the expectations originally predicted based on theory and practice [20]. One argument is that these treadmill robotics with a pre-set belt speed, combined with body weight support, create an environment where the patient has less control over the initiation of each step [21]; another argument against treadmill-based gait training is the lack of variability in visuospatial flow, which is an essential challenge of overground walking [20]. Powered robotic exoskeletons, though similar in structure to treadmill-based robotics, differ in that they require active participation from the user for both swing initiation and foot placement; for example, some exoskeletons have control strategies which will only assist the stepping motion when it detects adequate lateral weight-shifting [9]. Furthermore, because the powered exoskeletons are used for overground walking, it requires the user to be responsible for maintaining trunk and balance control, as well as navigating their path over varying surfaces.

While these powered exoskeletons hold promise, the literature surrounding their use for gait training is only just beginning to gather, with the majority focusing on spinal cord injury [22, 23, 24]. Several [25, 26, 27] systematic reviews have shown safe usage, positive effects as an assistive device, and exercise benefits for individuals with spinal cord injury. Only one systematic review [28] specifically focusing on powered exoskeletons has included studies involving stroke participants, though studies in spinal cord injury and other conditions were also included. This review focused exclusively on the Hybrid Assistive Limb (HAL) exoskeleton (Cyberdyne, Japan), (which currently is not approved for clinical use outside of Japan), and found beneficial effects on gait function and walking independence; however, the results were combined generally across all included patient populations and not specifically for stroke.

Given that this is a relatively new intervention for stroke, the objective of this scoping review was to map the current literature surrounding the use of powered robotic exoskeletons for gait rehabilitation in post-stroke individuals and to identify gaps in the research. The second objective of this scoping review was to preliminarily explore the efficacy of exoskeleton-based gait rehabilitation in stroke. As this is a relatively new technology for stroke, a scoping review can help guide current research and propose recommendations for advancing the technology.

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Fig. 1 Study results: A flowchart of selection process based on inclusion/exclusion criteria

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[ARTICE] Robotic System for Upper Limb Rehabilitation – Full Text PDF

Abstract

Currently, cerebrovascular diseases are one of the main health problems. Part of the patient’s rehabilitation process, affected by this disease, is manually performed by a physiotherapist, which, due to physical exhaustion, could affect the performance of patient recovery.

In this paper is proposed a robotic exoskeleton for upper limb rehabilitation, which enables assist or supports the therapist’s work. In the first stage, the exoskeleton is controlled passively through programmed commands and routines. Later, a second stage is proposed for biofeedback control system using the exoskeleton and signals acquired through bioinstrumentation equipment. This system will allows the acquisition of the surface electromyography signals (sEMG), as well as proprioceptive information for signal processing and movement’s intention detection of upper limb. As results, are presented the implementation of robotic arm commanded passively and the bioinstrumentation equipment is presented.

In the rehabilitation field, this assistive technology will enable to medical staff, to contribute to recovery and welfare of the patient, affected by some kind of muscular dysfunction, with major effectiveness.

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[ARTICLE] Robotic system for upper limb rehabilitation – Full Text PDF

Abstract

Currently, cerebrovascular diseases are one of the main health problems. Part of the patient’s rehabilitation process, affected by this disease, is manually performed by a physiotherapist, which, due to physical exhaustion, could affect the performance of patient recovery.

In this paper is proposed a robotic exoskeleton for upper limb rehabilitation, which enables assist or supports the therapist’s work. In the first stage, the exoskeleton is controlled passively through programmed commands and routines. Later, a second stage is proposed for biofeedback control system using the exoskeleton and signals acquired through bioinstrumentation equipment. This system will allows the acquisition of the surface electromyography signals (sEMG), as well as proprioceptive information for signal processing and movement’s intention detection of upper limb.

As results, are presented the implementation of robotic arm commanded passively and the bioinstrumentation equipment is presented. In the rehabilitation field, this assistive technology will enable to medical staff, to contribute to recovery and welfare of the patient, affected by some kind of muscular dysfunction, with major effectiveness.

Full Text PDF

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