Posts Tagged Exoskeleton

[ARTICLE] Design and Preliminary Feasibility Study of a Soft Robotic Glove for Hand Function Assistance in Stroke Survivors – Full Text

Various robotic exoskeletons have been proposed for hand function assistance during activities of daily living (ADL) of stroke survivors. However, traditional exoskeletons involve the use of complex rigid systems that impede the natural movement of joints, and thus reduce the wearability and cause discomfort to the user. The objective of this paper is to design and evaluate a soft robotic glove that is able to provide hand function assistance using fabric-reinforced soft pneumatic actuators. These actuators are made of silicone rubber which has an elastic modulus similar to human tissues. Thus, they are intrinsically soft and compliant. Upon air pressurization, they are able to support finger range of motion (ROM) and generate the desired actuation of the finger joints. In this work, the soft actuators were characterized in terms of their blocked tip force, normal and frictional grip force outputs. Combining the soft actuators and flexible textile materials, a soft robotic glove was developed for grasping assistance during ADL for stroke survivors. The glove was evaluated on five healthy participants for its assisted ROM and grip strength. Pilot test was performed in two stroke survivors to evaluate the efficacy of the glove in assisting functional grasping activities. Our results demonstrated that the actuators designed in this study could generate desired force output at a low air pressure. The glove had a high kinematic transparency and did not affect the active ROM of the finger joints when it was being worn by the participants. With the assistance of the glove, the participants were able to perform grasping actions with sufficient assisted ROM and grip strength, without any voluntary effort. Additionally, pilot test on stroke survivors demonstrated that the patient’s grasping performance improved with the presence and assistance of the glove. Patient feedback questionnaires also showed high level of patient satisfaction and comfort. In conclusion, this paper has demonstrated the possibility of using soft wearable exoskeletons that are more wearable, lightweight, and suitable to be used on a daily basis for hand function assistance of stroke survivors during activities of daily living.

Introduction

The ability to perform basic activities of daily living (ADL) impacts a person’s quality of life and independence (Katz, 1983Andersen et al., 2004). However, an individual’s independence to perform ADLs is jeopardized due to hand motor impairments, which can be observed in patients with neurological disorders such as stroke. In order to improve hand motor functions in terms of strength and range of motion (ROM) (Kutner et al., 2010), stroke survivors undergo rehabilitation programs comprising repetitive practice of simulated ADL tasks (Michaelsen et al., 2006). Normally, patients undergo rehabilitation exercises in a specialized rehabilitation center under the guidance of physiotherapists or occupational therapists. However, due to increasing patient population, it is foreseen that there will be a shortage of physiotherapists to assist in the rehabilitative process. Thus, there will be comparatively less therapy time, which will eventually lead to a slower recovery process for the patients. Over the past decade, technological developments in robotics have facilitated the rehabilitative process and have shown potential to assist patients in their daily life (Maciejasz et al., 2014). One example of such a device is the hand exoskeleton, which is secured around the hand to guide and assist the movement of the encompassed joints. However, due to the complexity of the hand, designing a hand exoskeleton remains a challenging task.

Traditional hand exoskeletons involve the use of rigid linkage-based mechanisms. In this kind of mechanism, rigid components, such as linear actuators, rotary motors, racks, and pinions as well as rigid linkages are normally involved (Worsnopp et al., 2007Rotella et al., 2009Martinez et al., 2010). To assist hand movements that have high degrees of freedom (DOFs), traditional exoskeletons can be incorporated with a substantial number of actuators to achieve the requirement. However, this means that their application is limited due to the increasing bulkiness for higher DOFs. Therefore, these devices are normally restricted in clinical settings and not suitable for performing home therapy. Additionally, their rigidity, weight and constraint on the non-actuated DOFs of the joints pose complications. As a result, the level of comfort and safety of patients is reduced. In view of this, there is an apparent need for the development of exoskeletons that may be used in both clinical and home settings. A lightweight and wearable exoskeleton may allow patients to bring back home to continue daily therapy or to serve as an assistive device for the ADLs.

The development of wearable robotic exoskeletons serves to provide an alternative approach toward addressing this need. Instead of using rigid linkage as an interface between the hand and the actuators, wearable exoskeletons typically utilize flexible materials such as fabric (Sasaki et al., 2004Yap et al., 2016a) and polymer (Kang et al., 2016), driven by compliant actuators such as cables (Sangwook et al., 2014Xiloyannis et al., 2016) and soft inflatable actuators (Polygerinos et al., 2015dYap et al., 2016c). Therefore, they are more compliant and lightweight compared to the rigid linkage-based mechanism. Cable-driven based exoskeletons involve the use of cables that are connected to actuators in the form of electrical motors situated away from the hand (Nilsson et al., 2012Ying and Agrawal, 2012Sangwook et al., 2014Varalta et al., 2014). By providing actuations on both dorsal and palmar sides of the hand, bi-directional cable-driven movements are possible (Kang et al., 2016). These cables mimic the capability of the tendons of the human hand and they are able to transmit the required pulling force to induce finger flexion and extension. However, the friction of the cable, derailment of the tendon, and inaccurate routing of the cable due to different hand dimensions can affect the efficiency of force transmission in the system.

On the other hand, examples of the soft inflatable actuators are McKibben type muscles (Feifei et al., 2006Tadano et al., 2010), sheet-like rubber muscles (Sasaki et al., 2004Kadowaki et al., 2011), and soft elastomeric actuators (Polygerinos et al., 2015b,cYap et al., 2015); amongst which, soft elastomeric actuators have drawn increasing research interest due to their high compliance (Martinez et al., 2013). This approach typically embeds pneumatic chamber networks in elastomeric constructs to achieve different desired motions with pressurized air or water (Martinez et al., 2012). Soft elastomeric actuators are highly customizable. They are able to achieve multiple DOFs and complex motions with a single input, such as fluid pressurization. The design of a wearable hand exoskeleton that utilizes soft elastomeric actuators is usually simple and does not require precise routing for actuation, compared to the cable-driven mechanism. Thus, the design reduces the possibility of misalignment and the setup time. These properties allow the development of hand exoskeletons that are more compliant and wearable, with the ability to provide safe human-robot interaction. Additionally, several studies have demonstrated that compactness and ease of use of an assistive device critically affect its user acceptance (Scherer et al., 20052007). Thus, these exoskeletons provide a greater chance of user acceptance.

Table 1 summarizes the-state-of-art of soft robotic assistive glove driven by inflatable actuators. Several pioneer studies on inflatable assistive glove have been conducted by Sasaki et al. (2004)Kadowaki et al. (2011) and Polygerinos et al. (2015a,b,c). Sasaki et al. have developed a pneumatically actuated power assist glove that utilizes sheet-like curved rubber muscle for hand grasping applications. Polygerinos et al. have designed a hydraulically actuated grip glove that utilizes fiber-reinforced elastomeric actuators that can be mechanically programmed to generate complex motion paths similar to the kinematics of the human finger and thumb. Fiber reinforcement has been proved to be an effective method to constrain the undesired radial expansion of the actuators that does not contribute to effective motion during pressurization. However, this method limits the bending capability of the actuators (Figure S1); as a result, higher pressure is needed to achieve desired bending.

Table 1. Hand assistive exoskeletons driven by inflatable actuators.

This paper presents the design and preliminary feasibility study of a soft robotic glove that utilizes fabric-reinforced soft pneumatic actuators. The intended use of the device is to support the functional tasks during ADLs, such as grasping, for stroke survivors. The objectives of this study were to characterize the soft actuators in terms of their force output and to evaluate the performance of the glove with healthy participants and stroke survivors. The glove was evaluated on five healthy participants in order to determine the ROM of individual finger joints and grip strength achieved with the assistance of the glove. Pilot testing with two stroke survivors was conducted to evaluate the feasibility of the glove in providing grasping assistance for ADL tasks. We hypothesized that with the assistance of the glove, the grasping performance of stroke patients improved.

Specific contributions of this work are listed as follows:

(a) Presented fabric-reinforcement as an alternative method to reinforce soft actuators, which enhanced the bending capability and reduced the required operating pressure of the actuators,

(b) Utilized the inherence compliance of soft actuators and allowed the actuators to achieve multiple motions to support ROM of the human fingers,

(c) Integrated elastic fabric with soft actuators to enhance the extension force for finger extension,

(d) Designed and characterized a soft robotic glove using fabric-reinforced soft actuators with the combination of textile materials, and

(e) Conducted pilot tests with stroke survivors to evaluate the feasibility of the glove in providing functional assistance for ADL tasks.

Design Requirements and Rationale

The design requirements of the glove presented in this paper are similar to those presented by Polygerinos et al. (2015a,b,c) in terms of design considerations, force requirements, and control requirements. For design considerations, weight is the most important design criterion when designing a hand exoskeleton. Previous studies have identified the threshold for acceptable weight of device on the hand, which is in the range of 400–500 g (Aubin et al., 2013Gasser and Goldfarb, 2015). Cable-driven, hydraulic, and pneumatic driven mechanisms are found to be suitable options to meet the criteria. To develop a fully portable system for practical use in home setting, reduction in the weight of the glove as well as the control system is required. The total weight of the control system should not exceed 3 kg (Polygerinos et al., 2015a,b,c). In this work, the criteria for the weight of the glove and control system are defined as: (a) the weight of the glove should be <200 g, and (b) the weight of the control system should be <1.5 kg.

Considering the weight requirement, hydraulic systems are not ideal for this application, as the requirement of a water reservoir for hydraulic control systems and actuation of the actuators with pressurized water will add extra weight to the hand. The second consideration is that the hand exoskeleton should allow fast setup time. Therefore, it is preferable for the hand exoskeleton to fit the hand anatomy rapidly without precise joint alignment. Compared to cable-driven mechanisms, soft pneumatic actuators are found to be more suitable as they allow rapid customization to different finger length. Additionally, they do not require precise joint alignment and cable routing for actuation as the attachment of the soft pneumatic actuators on the glove is usually simple. Therefore, in this work, pneumatic mechanisms were selected. Using pneumatic mechanism, Connelly et al. and Thielbar et al. have developed a pneumatically actuated glove, PneuGlove that is able to provide active extension assistance to each finger while allowing the wearer to flex the finger voluntarily (Connelly et al., 2010Thielbar et al., 2014). The device consists of five air bladders on the palmar side of the glove. Inflation of the air bladders due to air pressurization created an extension force that extends the fingers. However, due to the placement of the air bladders on the palmar side, grasping activities such as palmar and pincer grasps were more difficult. Additionally, this device is limited to stroke survivors who are able to flex their fingers voluntarily.

In this work, the soft robotic glove is designed to provide functional grasping assistance for stroke survivors with muscle weakness and impairments in grasping by promoting finger flexion. While the stroke survivors still preserve the ability to modulate grip force within their limited force range, the grip release (i.e., hand opening) is normally prolonged (Lindberg et al., 2012). Therefore, the glove should assist with grip release by allowing passive finger extension via reinforced elastic components, similar to Saeboflex (Farrell et al., 2007) and HandSOME (Brokaw et al., 2011). The elastic components of these devices pull the fingers to the open hand state due to increased tension during finger flexion. Additionally, the glove should generate the grasping force required to manipulate and counteract the weight of the objects of daily living, which are typically below 1.07 kg (Smaby et al., 2004). Additionally, the actuators in the glove should be controlled individually in order to achieve different grasping configurations required in simulated ADL tasks, such as palmar grasp, pincer grasp, and tripod pinch. For the speed of actuation, the glove should reach full grasping motion in <4 s during simulated ADL tasks and rehabilitation training.

For the actuators, we have recently developed a new type of soft fabric-reinforced pneumatic actuator with a corrugated top fabric layer (Yap et al., 2016a) that could minimize the excessive budging and provide better bending capability compared to fiber-reinforced soft actuators developed in previous studies (Polygerinos et al., 2015c,d). This corrugated top fabric layer allows a small initial radial expansion to initiate bending and then constrains further undesired radial expansion (Figure 1). The detailed comparison of the fiber-reinforced actuators and fabric-reinforced actuators can be found in the Supplementary Material.

 

 

Figure 1. (A) A fabric-reinforced soft actuators with a corrugated fabric layer and an elastic fabric later [Actuator thickness, T= 12 mm, and length, L = 160 mm (Thumb), 170 mm (Little Finger), 180 mm (Index & Ring Fingers), 185 mm (Middle Finger)]. (B) Upon air pressurization, the corrugated fabric layer unfolds and expands due to the inflation of the embedded pneumatic chamber. Radial budging is constrained when the corrugated fabric layer unfolds fully. The elastic fabric elongates during air pressurization and stores elastic energy. The actuator achieves bending and extending motions at the same time. (C) A bending motion is preferred at the finger joints (II, IV, VI). An extending motion is preferred over the bending motion at the finger segments (I, III, V) and the opisthenar (VII).

Continue —>  Frontiers | Design and Preliminary Feasibility Study of a Soft Robotic Glove for Hand Function Assistance in Stroke Survivors | Neuroscience

Advertisements

, , , , , , , , , , , ,

Leave a comment

[WEB SITE] Robot-Assisted Therapy: What Is Right for Your Clinic?

Published on 

One of the advantages of this gait training system is that it uses end-effector technology to assist patients in stepping, while a therapist provides manual facilitation. (Photo by Kevin Hentz)

by Rebecca Martin, OTR/L, OTD, and Dennis Tom-Wigfield, PT, DPT

Investment in therapeutic technologies spans a continuum from elastic bands that cost a few dollars to room-sized mobility and balance systems that require construction build-outs and additional staff. Inhabiting the middle to upper range of this continuum are robotic devices and associated technology, which have become increasingly popular. Though these advanced technologies deserve a thorough cost-benefit analysis and review of competing products prior to purchase, the payoff they may provide in outcomes and efficiency can make the investment well worth the effort.

Among the facility-based technologies that have grabbed recent headlines, robot-assisted therapy is one that may be attractive to healthcare organizations. Robot-assisted therapy is an efficacious method to remediate disability associated with a wide variety of neurological disorders, most notably stroke and spinal cord injury (SCI). Intensity and repetition has been repeatedly demonstrated to be necessary for central nervous system excitation and associated motor learning.1Massed practice, or high-volume repetition, has been shown to improve muscle strength and voluntary function.2 Robot-assisted therapy has the capacity to provide high numbers of specific movements with support or guidance as necessary, ensuring optimal conditions for motor learning and recovery of function.3 Changes can be observed in as little as 6 weeks and peak around 12 weeks of training.4

Nearly all robotic devices include some sort of computer interface, even a virtual reality component, providing the patient and therapist with real-time feedback to improve performance. Robotic devices also allow for quantitative monitoring; measuring changes in strength, range of motion, and trajectory; and illuminating patient engagement trends, time, and effort.3 As the body of literature expands and supports its use, patients are seeking clinics with these resources. Robotic technology has the potential to align patients’ interests in validated strategies with clinics’ interests in efficiency and payor-supported interventions. Clinics have an opportunity to improve patient outcomes and efficiency with which they reach those outcomes by investing in robotic devices. This investment is not trivial, however, and better understanding of the capacity and scope of different devices will help to make sure that everyone’s resources are utilized appropriately.

Assessment: Get the Complete Picture

Before it begins to investigate and trial devices, a clinic should do a careful self-assessment. Clinics should have a good understanding of their patient factors and needs: demographics, diagnoses, and payor mix. Equally important, clinics should have a good understanding of how much of their own resources—money, time, and space—they have to spend. Although money is often considered to be the limiting factor in the acquisition of technology, time and space deserve equal consideration. Nothing would be worse than investing in the perfect body weight support (BWS) gait trainer, only to find that your ceiling is too low to accommodate it. Similarly, clinics should anticipate that therapists will need time outside patient care to learn the devices and that efficiency will suffer in the early learning phase. Clinics will want to consider existing technology and therapist-driven interventions when deciding on their specific needs. Clinics would benefit from having a clear plan for acquisition and incorporation of robotic technology into existing practices. Acquiring too much technology too quickly is a sure way to reduce integration of devices and waste valuable resources.

 

Visit Site —> Robot-Assisted Therapy: What Is Right for Your Clinic? – Rehab Managment

, , , ,

Leave a comment

[ARTICLE] Wearable robotic exoskeleton for overground gait training in sub-acute and chronic hemiparetic stroke patients: preliminary results – Full Text PDF

BACKGROUND: Recovery of therapeutic or functional ambulatory capacity in post-stroke patients is a primary goal of rehabilitation. Wearable powered exoskeletons allow patients with gait dysfunctions to perform over-ground gait training, even immediately after the acute event.
AIM: To investigate the feasibility and the clinical effects of an over-ground walking training with a wearable powered exoskeleton in sub-acute and chronic stroke patients.
DESIGN: Prospective, pilot pre-post, open label, non-randomized experimental study.
SETTING: A single neurological rehabilitation center for inpatients and outpatients.
POPULATION: Twenty-three post-stroke patients were enrolled: 12 sub-acute (mean age: 43.8±13.3 years, 5 male and 7 female, 7 right hemiparesis and 5 left hemiparesis) and 11 chronic (mean age: 55.5±15.9 years, 7 male and 4 female, 4 right hemiparesis and 7 left hemiparesis) patients.
METHODS: Patients underwent 12 sessions (60 min/session, 3 times/week) of walking rehabilitation training using Ekso™, a wearable bionic suit that enables individuals with lower extremity disabilities and minimal forearm strength to stand up, sit down and walk over a flat hard surface with a full weight-bearing reciprocal gait. Clinical evaluations were performed at the beginning of the training period (t0), after 6 sessions (t1) and after 12 sessions (t2) and were based on the Ashworth scale, Motricity Index, Trunk Control Test, Functional Ambulation Scale, 10-Meter Walking Test, 6-Minute Walking Test, and Walking Handicap Scale. Wilcoxon’s test (P<0.05) was used to detect significant changes.
RESULTS: Statistically significant improvements were observed at the three assessment periods for both groups in Motricity Index, Functional Ambulation Scale, 10-meter walking test, and 6-minute walking test. Sub-acute patients achieved statistically significant improvement in Trunk Control Test and Walking Handicap Scale at t0-t2. Sub-acute and chronic patient did not achieve significant improvement in Ashworth scale at t0-t2.
CONCLUSIONS: Twelve sessions of over-ground gait training using a powered wearable robotic exoskeleton improved ambulatory functions in sub-acute and chronic post-stroke patients. Large, randomized multicenter studies are needed to confirm these preliminary data.
CLINICAL REHABILITATION IMPACT: To plan a completely new individual tailored robotic rehabilitation strategy after stroke, including task-oriented over-ground gait training.

Full Text PDF

via Wearable robotic exoskeleton for overground gait training in sub-acute and chronic hemiparetic stroke patients: preliminary results – European Journal of Physical and Rehabilitation Medicine 2017 October;53(5):676-84 – Minerva Medica – Journals

, , , , , ,

Leave a comment

[Abstract] What does best evidence tell us about robotic gait rehabilitation in stroke patients: A systematic review and meta-analysis

Highlights

  • Recovery of walking function is one of the main goals of patients after stroke.
  • RAGT may be considered a valuable tool in improving gait abnormalities.
  • The earlier the gait training starts, the better the motor recovery.

Abstract

Background

Studies about electromechanical-assisted devices proved the validity and effectiveness of these tools in gait rehabilitation, especially if used in association with conventional physiotherapy in stroke patients.

Objective

The aim of this study was to compare the effects of different robotic devices in improving post-stroke gait abnormalities.

Methods

A computerized literature research of articles was conducted in the databases MEDLINE, PEDro, COCHRANE, besides a search for the same items in the Library System of the University of Parma (Italy). We selected 13 randomized controlled trials, and the results were divided into sub-acute stroke patients and chronic stroke patients. We selected studies including at least one of the following test: 10-Meter Walking Test, 6-Minute Walk Test, Timed-Up-and-Go, 5-Meter Walk Test, and Functional Ambulation Categories.

Results

Stroke patients who received physiotherapy treatment in combination with robotic devices, such as Lokomat or Gait Trainer, were more likely to reach better results, compared to patients who receive conventional gait training alone. Moreover, electromechanical-assisted gait training in association with Functional Electrical Stimulations produced more benefits than the only robotic treatment (−0.80 [−1.14; −0.46], p > .05).

Conclusions

The evaluation of the results confirm that the use of robotics can positively affect the outcome of a gait rehabilitation in patients with stroke. The effects of different devices seems to be similar on the most commonly outcome evaluated by this review.

 

via What does best evidence tell us about robotic gait rehabilitation in stroke patients: A systematic review and meta-analysis – Journal of Clinical Neuroscience

, , , , ,

Leave a comment

[Abstract] Recent Advances on Lower Limb Exoskeleton Rehabilitation Robot

Abstract

Background: Lower limb exoskeleton rehabilitation robot is a bionic robot, which is the product of the combination of medical technology and robot technology, simulating human walking movement. It can be mainly used for rehabilitation training of patients with lower limb dysfunction.

Objective: To provide an overview of recent lower limb exoskeleton rehabilitation robot and introduce their respective characteristics and development.

Method: A recent lower limb exoskeleton rehabilitation robot is divided into passive drive, pneumatic drive, hydraulic drive and motor drive. This paper reviews various representative patents related to lower limb exoskeleton rehabilitation robot. The structural characteristics and applications of the typical lower limb exoskeleton rehabilitation robots are introduced.

Results: The differences between different types of lower limb exoskeleton rehabilitation robots are compared and analyzed, and the structural characteristics are concluded. The main problems in its development are analyzed, the development trend is foreseen, and the current and future research of the patents on lower limb exoskeleton rehabilitation robot is discussed.

Conclusion: There are a lot of patents and articles about the exoskeleton rehabilitation robots, however, if these problems can be solved, such as small size, light weight and high power output are solved at the same time, the consistency with human body will be advanced, with the combination of traditional rehabilitation medicine. It will be possible to maximize the rehabilitation of the lower limbs.

Source: Recent Advances on Lower Limb Exoskeleton Rehabilitation Robot: Ingenta Connect

, , , , , , ,

Leave a comment

[ARTICLE] Design and Interaction Control of a New Bilateral Upper-Limb Rehabilitation Device – Full Text

Abstract

This paper proposed a bilateral upper-limb rehabilitation device (BULReD) with two degrees of freedom (DOFs). The BULReD is portable for both hospital and home environment, easy to use for therapists and patients, and safer with respect to upper-limb robotic exoskeletons. It was implemented to be able to conduct both passive and interactive training, based on system kinematics and dynamics, as well as the identification of real-time movement intention of human users. Preliminary results demonstrate the potential of the BULReD for clinical applications, with satisfactory position and interaction force tracking performance. Future work will focus on the clinical evaluation of the BULReD on a large sample of poststroke patients.

1. Introduction

In the United States, more than 700,000 people suffer from stroke each year, and approximately two-thirds of these individuals survive and require rehabilitation [1]. In New Zealand (NZ), there are an estimated 60,000 stroke survivors, and many of them have mobility impairments [2]. Stroke is the third reason for health loss and takes the proportion of 3.9 percent, especially for the group starting on middle age, suffering the stroke as a nonfatal disease in NZ [3]. Professor Caplan who studies Neurology at Harvard Medical School describes stroke as a term which is a kind of brain impairment as a result of abnormal blood supply in a portion of the brain [4]. The brain injury is most likely leading to dysfunctions and disabilities. These survivors normally have difficulties in activities of daily living, such as walking, speaking, and understanding, and paralysis or numbness of the human limbs. The goals of rehabilitation are to help survivors become as independent as possible and to attain the best possible quality of life.

Physical therapy is conventionally delivered by the therapist. While this has been demonstrated as an effective way for motor rehabilitation [5], it is time-consuming and costly. Treatments manually provided by therapists require to take place in a specific environment (in a hospital or rehabilitation center) and may last several months for enhanced rehabilitation efficacy [6]. A study by Kleim et al. [7] has shown that physical therapy like regular exercises can improve plasticity of a nervous system and then benefits motor enrichment procedures in promoting rehabilitation of brain functional models. It is a truth that physical therapy should be a preferable way to take patients into regular exercises and guided by a physical therapist, but Chang et al. [8] showed that it is a money-consuming scheme. Robot-assisted rehabilitation solutions, as therapeutic adjuncts to facilitate clinical practice, have been actively researched in the past few decades and provide an overdue transformation of the rehabilitation center from labor-intensive operations to technology-assisted operations [9]. The robot could also provide a rich stream of data from built-in sensors to facilitate patient diagnosis, customization of the therapy, and maintenance of patient records. As a popular neurorehabilitation technique, Liao et al. [10] indicated that robot-assisted therapy presents market potential due to quantification and individuation in the therapy session. The quantification of robot-assisted therapy refers that a robot can provide consistent training pattern without fatigue with the given parameter. The characterization of individuation allows therapists to customize a specific training scheme for an individual.

Many robotic devices have been developed in recent years for stroke rehabilitation and show great potential for clinical applications [1112]. Typical upper-limb rehabilitation devices are MIME, MIT-Manus, ARM Guide, NeReBot, and ARMin [51321]. Relevant evidences demonstrated that these robots are effective for upper-limb rehabilitation but mostly for the one side of the human body. Further, upper-limb rehabilitation devices can be unilateral or bilateral [2224]. Despite the argument between these two design strategies, bilateral activities are more common than unilateral activities in daily living. Liu et al. [25] pointed that the central nervous system dominates the human movement with coordinating bilateral limb to act in one unit instead of independent unilateral actions. From this point, bilateral robots are expected to be more potential than unilateral devices. Robotic devices for upper-limb rehabilitation can be also divided into two categories in terms of structure: the exoskeleton and the end-effector device [26]. Two examples of upper-limb exoskeletons are the arm exoskeleton [27] and the RUPERT IV [28]. In addition, Lum et al. [13] incorporated a PUMA 560 robot (Staubli Unimation Inc., Duncan, South Carolina) to apply forces to the paretic limbs in the MIME system. This robotic device can be made for both unilateral and bilateral movements in a three-dimensional space. To summarize, existing robotic exoskeletons for upper-limb rehabilitation are mostly for unilateral training.

There are some devices that have been specially designed for bilateral upper-limb training for poststroke rehabilitation. van Delden et al. [29] conducted a systematic review to provide an overview and qualitative evaluation of the clinical applications of bilateral upper-limb training devices. A systematic search found a total of six mechanical devices and 14 robotic bilateral upper-limb training devices, with a comparative analysis in terms of mechanical and electromechanical characteristics, movement patterns, targeted part, and active involvement of the upper limb, training protocols, outcomes of clinical trials, and commercial availability. Obviously, these mechanical devices require the human limbs to actively move for training, while the robotic ones can be operated in both passive and active modes. However, few of these robotic bilateral upper-limb training devices have been commercially available with current technology. For example, the exoskeleton presented in [30] requires the development of higher power-to-weight motors and structural materials to make it mobile and more compact.

The University of Auckland developed an end-effector ReachHab device to assist bilateral upper-limb functional recovery [31]. However, this device suffered from some limitations, such as deformation of the frame leading to significant vibration, also hard to achieve satisfactory control performance. This paper presents the design and interaction control of an improved bilateral upper-limb rehabilitation device (BULReD). This device is portable for both hospital and home environment, easy to use for therapists and patients, and safer with respect to upper-limb robotic exoskeletons. This paper is organized as follows. Following Introduction, a detailed description of the BULReD is given, including mechanical design, electrical design, kinematics, and dynamics. Then, the control design is presented for both passive training and interactive training, as well as the fuzzy-based adaptive training. Experiments and Results is introduced next and the last is Conclusion.[…]

Continue —>  Design and Interaction Control of a New Bilateral Upper-Limb Rehabilitation Device

, , , , , , ,

6 Comments

[ARTICLE] Post-stroke Rehabilitation Training with a Motor-Imagery-Based Brain-Computer Interface (BCI)-Controlled Hand Exoskeleton: A Randomized Controlled Multicenter Trial – Full Text

Repeated use of brain-computer interfaces (BCIs) providing contingent sensory feedback of brain activity was recently proposed as a rehabilitation approach to restore motor function after stroke or spinal cord lesions. However, there are only a few clinical studies that investigate feasibility and effectiveness of such an approach. Here we report on a placebo-controlled, multicenter clinical trial that investigated whether stroke survivors with severe upper limb (UL) paralysis benefit from 10 BCI training sessions each lasting up to 40 min. A total of 74 patients participated: median time since stroke is 8 months, 25 and 75% quartiles [3.0; 13.0]; median severity of UL paralysis is 4.5 points [0.0; 30.0] as measured by the Action Research Arm Test, ARAT, and 19.5 points [11.0; 40.0] as measured by the Fugl-Meyer Motor Assessment, FMMA. Patients in the BCI group (n = 55) performed motor imagery of opening their affected hand. Motor imagery-related brain electroencephalographic activity was translated into contingent hand exoskeleton-driven opening movements of the affected hand. In a control group (n = 19), hand exoskeleton-driven opening movements of the affected hand were independent of brain electroencephalographic activity. Evaluation of the UL clinical assessments indicated that both groups improved, but only the BCI group showed an improvement in the ARAT’s grasp score from 0 [0.0; 14.0] to 3.0 [0.0; 15.0] points (p < 0.01) and pinch scores from 0.0 [0.0; 7.0] to 1.0 [0.0; 12.0] points (p < 0.01). Upon training completion, 21.8% and 36.4% of the patients in the BCI group improved their ARAT and FMMA scores respectively. The corresponding numbers for the control group were 5.1% (ARAT) and 15.8% (FMMA). These results suggests that adding BCI control to exoskeleton-assisted physical therapy can improve post-stroke rehabilitation outcomes. Both maximum and mean values of the percentage of successfully decoded imagery-related EEG activity, were higher than chance level. A correlation between the classification accuracy and the improvement in the upper extremity function was found. An improvement of motor function was found for patients with different duration, severity and location of the stroke.

Introduction

Motor imagery (Page et al., 2001), or mental practice, attracted considerable interest as a potential neurorehabilitation technique improving motor recovery following stroke (Jackson et al., 2001). According to the Guidelines for adult stroke rehabilitation and recovery (Winstein et al., 2016), mental practice may proof beneficial as an adjunct to upper extremity rehabilitation services (Winstein et al., 2016). Several studies suggest that motor imagery can trigger neuroplasticity in ipsilesional motor cortical areas despite severe paralysis after stroke (Grosse-Wentrup et al., 2011Shih et al., 2012Mokienko et al., 2013bSoekadar et al., 2015).

The effect of motor imagery on motor function and neuroplasticity has been demonstrated in numerous neurophysiological studies in healthy subjects. Motor imagery has been shown to activate the primary motor cortex (M1) and brain structures involved in planning and control of voluntary movements (Shih et al., 2012Mokienko et al., 2013a,bFrolov et al., 2014). For example, it was shown that motor imagery of fist clenching reduces the excitation threshold of motor evoked potentials (MEP) elicited by transcranial magnetic stimulation (TMS) delivered to M1 (Mokienko et al., 2013b).

As motor imagery results in specific modulations of brain electroencephalographic (EEG) signals, e.g., sensorimotor rhythms (SMR) (Pfurtscheller and Aranibar, 1979), it can be used to voluntarily control an external device, e.g., a robot or exoskeleton using a brain-computer interface (BCI) (Nicolas-Alonso and Gomez-Gil, 2012). Such system allowing for voluntary control of an exoskeleton moving a paralyzed limb can be used as an assistive device restoring lost function (Maciejasz et al., 2014). Besides receiving visual feedback, the user receives haptic and kinesthetic feedback which is contingent upon the imagination of a specific movement.

Several BCI studies involving this type of haptic and kinesthetic feedback have demonstrated improvements in clinical parameters of post-stroke motor recovery (Ramos-Murguialday et al., 2013Ang et al., 20142015Ono et al., 2014). The number of subjects with post-stroke upper extremity paresis included in these studies was, however, relatively low [from 12 (Ono et al., 2014) to 32 (Ramos-Murguialday et al., 2013) patients]. As BCI-driven external devices, a haptic knob (Ang et al., 2014), MIT-Manus (Ang et al., 2015), or a custom-made orthotic device (Ramos-Murguialday et al., 2013Ono et al., 2014) were used. Furthermore, several other studies reported on using BCI-driven exoskeletons in patients with post-stroke hand paresis (Biryukova et al., 2016Kotov et al., 2016Mokienko et al., 2016), but these reports did not test for clinical efficacy and did not include a control group. While very promising, it still remains unclear whether BCI training is an effective tool to facilitate motor recovery after stroke or other lesions of the central nervous system (CNS) (Teo and Chew, 2014).

Here we report a randomized and controlled multicenter study investigating whether 10 sessions of BCI-controlled hand-exoskeleton active training after subacute and chronic stroke yields a better clinical outcome than 10 sessions in which hand-exoskeleton induced passive movements were not controlled by motor imagery-related modulations of brain activity. Besides assessing the effect of BCI training on clinical scores such as the ARAT and FMMA, we tested whether improvements in the upper extremity function correlates with the patient’s ability to generate motor imagery-related modulations of EEG activity.[…]

Continue —> Frontiers | Post-stroke Rehabilitation Training with a Motor-Imagery-Based Brain-Computer Interface (BCI)-Controlled Hand Exoskeleton: A Randomized Controlled Multicenter Trial | Neuroscience

 

Figure 1. The subject flow diagram from recruitment through analysis (Consolidated Standards of Reporting Trials flow diagram).

, , , , , ,

Leave a comment

[WEB SITE] Study Examines Exoskeleton’s Ability to Improve Walking for Stroke Patients

Conor Walsh and his graduate student, Jaehyun Bae, fine-tune an ankle-assisting exosuit. (Photo courtesy of Rolex Awards/Fred Merz)

A study published recently in Science Translational Medicine suggests that the use of a soft suit exoskeleton system helps aid in the facilitation of walking ability among ambulatory patients following a stroke.

Researchers from Harvard University’s Wyss Institute for Biologically Inspired Engineering, the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), and Boston University’s (BU) College of Health & Rehabilitation Sciences: Sargent College developed the lightweight, soft, wearable ankle-assisting exosuit, and they they suggest in the study that it could help reinforce normal gait in people with hemiparesis after stroke.

The study centers on the use of the exosuit among nine participants, each of whom recently experienced a stroke, and examines the immediate improvements in walking capability that could be obtained when wearing the suit, dubbed the Restore system, according to a media release from ReWalk Robotics Ltd.

According to the release, the study concludes that improvements in paretic limb function contributed to a 20 +/- 4% reduction in forward propulsion interlimb asymmetry and a 10 +/- 3% reduction in the energy cost of walking, which is equivalent to a 32+/- 9% reduction in the metabolic burden associated with poststroke walking.  Relatively low assistance (~12% of biological torques) delivered with a lightweight and nonrestrictive exosuit was sufficient to facilitate more normal walking in ambulatory individuals after stroke.

“This foundational study shows that soft wearable robots can have significant positive impact on gait functions in patients post-stroke, and it is the result of a translational-focused multidisciplinary team of engineers, designers, biomechanists, physical therapists, and most importantly patients who volunteered for this study and gave valuable feedback that guided our research,” says Wyss Core Faculty member Conor Walsh, who is also the John L. Loeb Associate Professor of Engineering and Applied Sciences at SEAS and the Founder of the Harvard Biodesign Lab, in the release.

ReWalk is working with the Wyss Institute on the development of lightweight designs to complete clinical studies, pursue regulatory approvals, and commercialize the systems on a global scale. The first commercial application will be for stroke survivors, followed by Multiple Sclerosis patients and then additional applications.

“Exoskeletons are now a commercially available, disruptive technology that have changed the lives of many individuals in the paraplegic community,” states ReWalk CEO Larry Jasinski, in the release. “The ongoing research at the Wyss Institute on soft exosuits adds a new dimension to exoskeletons that can potentially meet the needs of individuals that have had a stroke, as well as for those diagnosed with Multiple Sclerosis, Parkinson’s disease or people who have limitations in walking.”

[Source(s): ReWalk Robotics Ltd, PR Newswire, Science Daily]

Source: Study Examines Exoskeleton’s Ability to Improve Walking for Stroke Patients – Rehab Managment

, , , ,

Leave a comment

[Conference paper] ERRSE: Elbow Robotic Rehabilitation System with an EMG-Based Force Control – Abstract+References

Abstract

Robotic devices for rehabilitation purposes have been increasingly studied in the past two decades and are becoming more and more diffused, due to their effective support to the traditional therapy. They allow to automate in a repeatable manner the rehabilitative exercises and to quantify outcomes, giving important feedback to the therapist. This paper deals with the design, development and preliminary characterization of a robotic system, with an exoskeleton device, for assisted upper-limb rehabilitation, in which surface EMG measurements are used to implement a force-based active and resistive control. A prototype of the system has been realized, measurements of important parameters of the motion permitted to optimize the design and preliminary tests on the control strategy were carried out. 

References

  1. 1.
    Lo AC et al (2010) Robot-assisted therapy for long-term upper-limb impairment after stroke. N Eng J Med 362:1772–1783CrossRefGoogle Scholar
  2. 2.
    Lum PS, Burgar CG, Shor PC, Majmundar M, Van der Loos M (2002) Robot-assisted movement training compared with conventional therapy techniques for the rehabilitation of upper-limb motor function after stroke. Arch Phys Med Rehabil 83(7):952–959CrossRefGoogle Scholar
  3. 3.
    Prange GB, Jannink MJA, Groothuis-Oudshoorn CGM, Hermens HJ, IJzerman MJ (2006) Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke. J Rehabil Res Dev 43(2):171–184CrossRefGoogle Scholar
  4. 4.
    Huang VS, Krakauer JW (2009) Robotic neurorehabilitation: a computational motor learning perspective. J NeuroEng Rehabil 6Google Scholar
  5. 5.
    Krebs HI, Volpe BT, Williams D, Celestino J, Charles SK, Lynch D, Hogan N (2007) Robot-aided neurorehabilitation: a robot for wrist rehabilitation. Trans Neural Syst Rehabil Eng 15(3):327–335CrossRefGoogle Scholar
  6. 6.
    Colombo R, Pisano F, Micera S, Mazzone A, Delconte C, Carrozza MC, Dario P, Minuco G (2005) Robotic techniques for upper limb evaluation and rehabilitation of stroke patients. IEEE Trans Neural Syst Rehabil Eng 13(3):311–324CrossRefGoogle Scholar
  7. 7.
    Lo H, Quan Xie S (2012) Exoskeleton robots for upper-limb rehabilitation: state of the art and future prospects. Med Eng Phys 34(2012):261–268CrossRefGoogle Scholar
  8. 8.
    Li H, Zhao G, Zhou Y, Chen X, Ji Z, Wang L (2014) Relationship of EMG/SMG features and muscle strength level: an exploratory study on tibialis anterior muscles during plantar-flexion among hemiplegia patients. Biomed Eng Online 13(1):2–15CrossRefGoogle Scholar
  9. 9.
    Kiguchi K, Hayashi Y (2015) EMG-based control of a lower-lim power-assist robot. In: Intelligent assistive robots. Springer tracts in advanced robotics, vol 106, pp 371–383Google Scholar
  10. 10.
    Kawasaki H, Ito S, Ishigure Y, Nishimoto Y, Aoki T, Mouri T, Skaeda H, Abe M (2007) Development of a hand motion assist robot for rehabilitation therapy by patient self-motion control. In: Proceedings of the IEEE international conference on robotic rehabilitation (ICORR), June 2007, pp 234–240Google Scholar
  11. 11.
    Jeong EC (2013) Comparison of wrist motion classification methods using surface electromyogram. J Cent South Univ 20(4):960–968CrossRefGoogle Scholar
  12. 12.
    Celli A et al (2008) Treatment of elbow lesions: new aspects in diagnosis and surgical techniques. Springer, New York, p c2008CrossRefGoogle Scholar
  13. 13.
    Kyrylova A (2015) Development of a wearable mechatronic elbow brace for postoperative motion rehabilitation. Electronic thesis and dissertation repository. Paper 3019Google Scholar
  14. 14.
    Ferris DP, Lewis CL, (2009) Robotic lower limb exoskeletons using proportional myoelectric control. In: Proceedings of the 31st annual international conference of the IEEE EMBS, pp 2119–2124Google Scholar
  15. 15.
    DiCicco M, Lucas L, Matsuoka Y (2004) Comparison of control strategies for an EMG controlled orthotic exoskeleton for the hand. In: Proceedings of the 2004 IEEE international conference on robotics and automation, April 2004Google Scholar

Source: ERRSE: Elbow Robotic Rehabilitation System with an EMG-Based Force Control | SpringerLink

, , , , , , ,

Leave a comment

[Abstract] A survey on sEMG control strategies of wearable hand exoskeleton for rehabilitation

Abstract:

Surface electromyographic (sEMG) signals is one most commonly used control source of exoskeleton for hand rehabilitation. Due to the characteristics of non-invasive, convenient collection and safety, sEMG can conform to the particularity of hemiplegic patients’ physiological state and directly reflect human’s neuromuscular activity. By way of collecting, analyzing and processing, sEMG signals corresponding to identify the target movement model would be translated into robot movement control instructions and input into hand rehabilitation exoskeleton controller. Then patients’ hand can be directed to achieve the realization of the similar action finally. In this paper, the recent key technologies of sEMG-based control for hand rehabilitation robots are reviewed. Then a summarization of controlling technology principle and methods of sEMG signal processing employed by the hand rehabilitation exoskeletons is presented. Finally suitable processing methods of multi-channel sEMG signals for the controlling of hand rehabilitation exoskeleton are put forward tentatively and the practical application in hand exoskeleton control is commented also.

Source: A survey on sEMG control strategies of wearable hand exoskeleton for rehabilitation – IEEE Xplore Document

, , , , , , , , , , , , , , , ,

Leave a comment

%d bloggers like this: