Posts Tagged Robotic

[Abstract] EEG predicts upper limb motor improvement after robotic rehabilitation in chronic stroke patients

Introduction/Background

Robotic rehabilitation is known to be at least as effective as conventional training for upper limb motor recovery after stroke; nevertheless, which patients could benefit from this treatment is unknown and finding markers that could predict rehabilitation outcome is a challenge.

We aimed at understanding the neural mechanisms of motor function recovery after upper limb robotic rehabilitation in chronic stroke patients using neurophysiological markers obtained by electroencephalography recording (EEG).

Material and method

Fourteen chronic stroke patients (M/F: 11/3; 59.5 ± 13 yrs) with mild to moderate upper limb paresis were subjected to 10 sessions of upper limb rehabilitation with a planar mobile robotic device (MOTORE, Humanware). Fugl–Meyer Assessment Scale (FMAS) and Wolf Motor Function Test (WMFT) were administered before (t0), at the end (t1) and at 1 month follow-up (t2); at the same timing 64-channals EEG was recorded.

We analyzed power spectrum density in different frequency bands of the affected and unaffected hemispheres with 64-ch EEG and their correlation with motor impairment as measured by clinical scales. Correlation analyses were performed to identify the indicators of good rehabilitative outcome.

Results

Clinical assessment indicated a significant functional improvement in upper limb motor function at the end of rehabilitation as assessed with FMAS and WMFT score that is maintained at follow-up. We found a positive correlation between global Alpha activity at t0 and WMFT score variation (t0–t1) and between global Beta activity at t0 and WMFT time variation (t0–t1) and a positive correlation between Beta activity at t0 in the unaffected hemisphere and FMAS variation (t0–t1 and t0–t2).

Conclusion

Robotic rehabilitation improves upper limb motor performance in stroke patients even in the chronic phase. The amount of Alpha and Beta band power at t0 is suggestive of rehabilitation-related motor outcome. Our results suggest that EEG recording preliminarily to robotic rehabilitation could help identifying good responders to treatment thus optimizing results.

 

via EEG predicts upper limb motor improvement after robotic rehabilitation in chronic stroke patients – ScienceDirect

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[WEB SITE] Project3 – Flexo-glove

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Project Description

Flexo-glove is a 3D printed soft exoskeleton robotic glove with compact and streamlined design for assistance in activities of daily livings and rehabilitation purposes of patients with hand function impairment.

Specifications:

  • Overall weight of 330g including battery
  • Providing 22N pinch force, 48N power grasp force and object grasp size of up to 81mm in diameter
  • Two control modes: intention-sensing via wireless surface EMG for assistive mode and externally-directed via an accompanying smartphone

Project Details: —> Visit site

My Role:

  • Initiated the project with the idea of using soft 3D printed materials in design of the Flexo-glove inspired by X-Limb
  • Performed feasibility study for using cable-driven mechanism in actuation of rehabilitation glove
  • Leading a group of four mechatronics engineering students to fabricate the prototype and characterise the grip forces

Awards

  • Received Dyason fellowship, $5000 travel fellowship awarded by Melbourne Robotic Lab. to visit Harvard BioRobotics Lab

Related Publications

 A. Mohammadi, J. Lavranos, R. D. Howe, P. Choong and D. Oetomo

  Flexo-glove: A 3D Printed Soft Exoskeleton Robotic Glove for Impaired Hand Rehabilitation and Assistance

  40th International Engineering in Medicine and Biology Conference (EMBC), 2018.

Full Text  PDF 

via Project3 – Flexo-glove

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[WEB SITE] Soft Robotic Glove

Soft Robotic Glove

A lightweight robotic glove to assist people suffering from loss of hand motor control to restore their ability to grasp objects independently

The majority of patients with partial or total loss of hand motor abilities, including those suffering from debilitating disorders like muscular dystrophy, amyotrophic lateral sclerosis (ALS), and incomplete spinal cord injury, experience greatly reduced quality of life due to their inability to perform many daily activities. Tasks often taken for granted by the able-bodied become frustrating and nearly impossible feats due to reduced gripping strength and motor control of the hand.

 

The soft robotic glove under development at the Wyss Institute could one day be an assistive device used for grasping objects, which could help patients suffering from muscular dystrophy, amyotrophic lateral sclerosis (ALS), incomplete spinal cord injury, or other hand impairments to regain some daily independence and control of their environment. Credit: Wyss Institute at Harvard University

Visit site for more —>  Soft Robotic Glove

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[ARTICLE] Quantification of upper limb position sense using an exoskeleton and a virtual reality display – Full Text

Abstract

Background

Proprioceptive sense plays a significant role in the generation and correction of skilled movements and, consequently, in most activities of daily living. We developed a new proprioception assessment protocol that enables the quantification of elbow position sense without using the opposite arm, involving active movement of the evaluated limb or relying on working memory. The aims of this descriptive study were to validate this assessment protocol by quantifying the elbow position sense of healthy adults, before using it in individuals who sustained a stroke, and to investigate its test-retest reliability.

Methods

Elbow joint position sense was quantified using a robotic device and a virtual reality system. Two assessments were performed, by the same evaluator, with a one-week interval. While the participant’s arms and hands were occluded from vision, the exoskeleton passively moved the dominant arm from an initial to a target position. Then, a virtual arm representation was projected on a screen placed over the participant’s arm. This virtual representation and the real arm were not perfectly superimposed, however. Participants had to indicate verbally the relative position of their arm (more flexed or more extended; two-alternative forced choice paradigm) compared to the virtual representation. Each participant completed a total of 136 trials, distributed in three phases. The angular differences between the participant’s arm and the virtual representation ranged from 1° to 27° and changed pseudo-randomly across trials. No feedback about results was provided to the participants during the task. A discrimination threshold was statistically extracted from a sigmoid curve fit representing the relationship between the angular difference and the percentage of successful trials. Test-retest reliability was evaluated with 3 different complementary approaches, i.e. a Bland-Altman analysis, an intraclass correlation coefficient (ICC) and a standard error of measurement (SEm).

Results

Thirty participants (24.6 years old; 17 males, 25 right-handed) completed both assessments. The mean discrimination thresholds were 7.0 ± 2.4 (mean ± standard deviation) and 5.9 ± 2.1 degrees for the first and the second assessment session, respectively. This small difference between assessments was significant (− 1.1 ± 2.2 degrees), however. The assessment protocol was characterized by a fair to good test-retest reliability (ICC = 0.47).

Conclusion

This study demonstrated the potential of this assessment protocol to objectively quantify elbow position sense in healthy individuals. Futures studies will validate this protocol in older adults and in individuals who sustained a stroke.

 

Background

Proprioception is defined as the ability to perceive body segment positions and movements in space [1]. Sensory receptors involved in proprioception are mostly located in muscle [234], joint [56] and skin [37]. Proprioceptive sense is known to play a significant role in motor control [891011] and learning [812], particularly in the absence of vision. The importance of proprioceptive inputs has been demonstrated while studying individuals who presented lack of proprioception due to large-fiber sensory neuropathy [1112]. Despite an intact motor system, somatosensory deafferentation may lead to limitations in several activities involving motor skills, such as eating or dressing [12]. These disabilities may also be observed in individuals with proprioceptive impairments due to a stroke. Indeed, approximately half of the individuals who sustained a stroke present proprioceptive impairments in contralesional upper limb [13]. After a stroke, proprioception is known to be related to recovery of functional mobility and independence in activities of daily living (ADL; [14]). Fewer individuals with significant proprioceptive and motor losses (25%) were independent in ADL than individuals with motor deficits alone (78%). Moreover, fewer individuals with proprioceptive deficits (60%) after a stroke are discharged from the hospital directly to home compared to those without proprioceptive deficits (92%) [15].

Although the negative impact of proprioceptive impairments on motor and functional recovery is known, a large proportion of clinicians (70%) report not using standardised assessment to evaluate somatosensory deficits in patients with a stroke [16]. In clinical and research settings, proprioception is most frequently assessed with limb-matching tasks. Two types of matching tasks have commonly been used: the ipsilateral remembered matching task and the contralateral concurrent matching task [17]. In an ipsilateral remembered matching task, the evaluator or robotic device brings the patient’s limb to a target joint position, when the patient’s eyes are closed, keeps the limb in this position for several seconds, and then moves back the limb to the initial position. The patient needs to memorize the reference position and replicate it with the same (ipsilateral) limb. This task cannot, however, be used to evaluate proprioception in individuals with working memory issues, which represent around 25% of individuals who sustained a stroke [18]. In such cases, the matching error observed could reflect memory deficits, rather than proprioceptive impairments. Moreover, upper limb paresis affects 76% of individuals who sustained a stroke [19], making the task’s execution difficult or impossible. Assessing proprioception with the less affected arm as the indicator arm is therefore frequently considered in patients with hemiparesis. Indeed, in a contralateral concurrent matching task, the patient has to reproduce a mirror image of the evaluated limb position with the opposite (contralateral) limb [17]. However, considering that 20% of individuals who sustained a stroke also presents proprioceptive impairment on the ipsilateral side of the lesion [13], it would be difficult to ascertain whether the error is due to deficits in the evaluated arm, the opposite arm or both. In addition, interhemispheric communication is required in a contralateral concurrent matching task. Individuals with asymmetric stroke or with transcallosal degeneration would therefore be particularly disadvantaged while being assessed with a contralateral concurrent matching task [17].

In order to study proprioception in individuals who sustained a stroke, we developed an assessment protocol, that combines the use of an exoskeleton and a virtual reality system, enabling the quantification of position sense without using the opposite arm, involving active movement of the evaluated limb or relying on working memory. The primary objective of the present study was to validate the assessment protocol by quantifying the elbow joint position sense of healthy adults, before using this protocol with individuals who sustained a stroke. As a secondary objective, test-retest reliability of the assessment protocol was investigated.[…]

 

Continue —> Quantification of upper limb position sense using an exoskeleton and a virtual reality display | Journal of NeuroEngineering and Rehabilitation | Full Text

 

Fig. 1KINARM Exoskeleton Lab. a Modified wheelchair with each arm supported against gravity by exoskeletons; (b) Virtual reality display; (c) Virtual arm and real arm positions (blue line; non-visible for the participant) where ∆Θ represents the angular difference between the real and the virtual arm. The white circle corresponds to the center of rotation, i.e. the elbow joint

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[Abstract] Efficacy of Short-Term Robot-Assisted Rehabilitation in Patients With Hand Paralysis After Stroke: A Randomized Clinical Trial

Background: We evaluated the effectiveness of robot-assisted motion and activity in additional to physiotherapy (PT) and occupational therapy (OT) on stroke patients with hand paralysis.

Methods:A randomized controlled trial was conducted. Thirty-two patients, 34.4% female (mean ± SD age: 68.9 ± 11.6 years), with hand paralysis after stroke participated. The experimental group received 30 minutes of passive mobilization of the hand through the robotic device Gloreha (Brescia, Italy), and the control group received an additional 30 minutes of PT and OT for 3 consecutive weeks (3 d/wk) in addition to traditional rehabilitation. Outcomes included the National Institutes of Health Stroke Scale (NIHSS), Modified Ashworth Scale, Barthel Index (BI), Motricity Index (MI), short version of the Disabilities of the Arm, Shoulder and Hand (QuickDASH), and the visual analog scale (VAS) measurements. All measures were collected at baseline and end of the intervention (3 weeks).

Results: A significant effect of time interaction existed for NIHSS, BI, MI, and QuickDASH, after stroke immediately after the interventions (all, P < .001). The experimental group had a greater reduction in pain compared with the control group at the end of the intervention, a reduction of 11.3 mm compared with 3.7 mm, using the 100-mm VAS scale.

Conclusions: In the treatment of pain and spasticity in hand paralysis after stroke, robot-assisted mobilization performed in conjunction with traditional PT and OT is as effective as traditional rehabilitation.

via Efficacy of Short-Term Robot-Assisted Rehabilitation in Patients With Hand Paralysis After Stroke: A Randomized Clinical Trial – Jorge H. Villafañe, Giovanni Taveggia, Silvia Galeri, Luciano Bissolotti, Chiara Mullè, Grace Imperio, Kristin Valdes, Alberto Borboni, Stefano Negrini, 2018

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[ARTICLE] Systematic Review of Appropriate Robotic Intervention for Gait Function in Subacute Stroke Patients – Full Text

Abstract

The purpose of this study was to critically evaluate the effects of robot-assisted gait training (RAGT) on gait-related function in patients with acute/subacute stroke. We conducted a systematic review of randomized controlled trials published between May 2012 and April 2016. This search included 334 articles (Cochrane, 51 articles; Embase, 175 articles; PubMed, 108 articles). Based on the inclusion and exclusion criteria, 7 studies were selected for this review. We performed a quality evaluation using the PEDro scale. In this review, 3 studies used an exoskeletal robot, and 4 studies used an end-effector robot as interventions. As a result, RAGT was found to be effective in improving walking ability in subacute stroke patients. Significant improvements in gait speed, functional ambulatory category, and Rivermead mobility index were found with RAGT compared with conventional physical therapy . Therefore, aggressive weight support and gait training at an early stage using a robotic device are helpful, and robotic intervention should be applied according to the patient’s functional level and onset time of stroke.

1. Introduction

Stroke is a common disease [1]. In most patients, disabilities remain after stroke, and long-lasting disability requires continuous management and intensive rehabilitation [12]. Furthermore, the economic burden on the patient increases because of the prolonged rehabilitation period. Therefore, the application of intensive and efficient rehabilitation programs and techniques is an urgent need after stroke [3].

Gait impairment is one of the most important problems after stroke and is associated with activities of daily living and mobility issues [4]. Therefore, recovery of gait function is an important goal of rehabilitation for independent living [5]. Interventions to enhance gait function require repetitive task training with high intensity, and extensive effort by physical therapists is essential [5]. Moreover, the most effective rehabilitation intervention, including gait training, must be performed shortly after stroke and in an intensive and task-oriented manner and should include multisensory stimulation [3].

Robot-assisted gait training (RAGT) for patients in the acute/subacute stage who are nonambulatory is effective at reeducating motor control function through repetitive training of a specific task [6]; RAGT provides intensive therapy, which reduces the burden on therapists, and enhances motor reeducation with multisensory stimulation [3]. Several previous studies reported that gait training using robotic devices is effective at enhancing muscular activity patterns [7], muscle tone, joint range of motion [8], gait speed, functional gait capability [79], gait independence, and mobility in the community [1011]. Moreover, patients who received RAGT and conventional physical therapy had a higher chance of regaining independent gait function than those who received only conventional gait training [12]. However, owing to studies that suggested RAGT is ineffective [13], the effect on gait and gait-related function in subacute stroke remains unclear. In a previous review of effectiveness in stroke patients, the RAGT group showed significant improvement in balance and balance-related activity function, but the comparison between the groups was not significant [14]. These results show that RAGT is effective, but whether it is more effective than other gait-related rehabilitation interventions is still unclear. In this context, the effect of RAGT is still not clearly demonstrated, and reviews that have recently demonstrated the effect of RAGT on gait-related outcome measures in patients with acute/subacute stroke are also limited.

Therefore, the aim of this systematic review was to investigate the effects of RAGT on acute/subacute stroke. The specific goals included identifying the effects of RAGT using assessment tools associated with gait and gait-related function in patients with acute/subacute stroke.[…]

Continue —>  Systematic Review of Appropriate Robotic Intervention for Gait Function in Subacute Stroke Patients

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[ARTICLE] Comparison of proximal versus distal upper-limb robotic rehabilitation on motor performance after stroke: a cluster controlled trial – Full Text

 

Abstract

This study examined the treatment efficacy of proximal-emphasized robotic rehabilitation by using the InMotion ARM (P-IMT) versus distal-emphasized robotic rehabilitation by using the InMotion WRIST (D-IMT) in patients with stroke. A total of 40 patients with stroke completed the study. They received P-IMT, D-IMT, or control treatment (CT) for 20 training sessions. Primary outcomes were the Fugl-Meyer Assessment (FMA) and Medical Research Council (MRC) scale. Secondary outcomes were the Motor Activity Log (MAL) and wrist-worn accelerometers. The differences on the distal FMA, total MRC, distal MRC, and MAL quality of movement scores among the 3 groups were statistically significant (P = 0.02 to 0.05). Post hoc comparisons revealed that the D-IMT group significantly improved more than the P-IMT group on the total MRC and distal MRC. Furthermore, the distal FMA and distal MRC improved more in the D-IMT group than in the CT group. Our findings suggest that distal upper-limb robotic rehabilitation using the InMotion WRIST system had superior effects on distal muscle strength. Further research based on a larger sample is needed to confirm long-term treatment effects of proximal versus distal upper-limb robotic rehabilitation.

Introduction

Most stroke survivors are burdened with significant physical dysfunction, and approximately 60% to 80% continue to have upper-limb (UL) motor deficits into the chronic phase of stroke that have a large effect on their daily life1,2. Developing effective rehabilitation interventions to maxmize UL motor recovery and functional independence of patients with stroke is therefore one of the top priorities in clinical practice and research3,4.

Robot-assisted therapy (RT) has emerged during the last decade as a novel rehabilitation approach to intensify UL motor function5,6,7,8. RT helps provide intensive, repetitive, and interactive training in a controlled environment to promote motor control and recovery of patients9,10,11,12,13,14. Although positive results of RT on motor outcomes have been noted13,14,15, there are disparate effects and heterogeneities between trials depending on the robotic types (eg, exoskeleton versus end-effector, or proximal versus distal approach), protocols, dosages, and problems of patients15,16.

Very few studies have directly compared the relative effects of different robotic devices. A recent systematic review15 investigated the effect of robotic types and reported a trend favoring end-effector rather than exoskeleton robotic devices on motor function. However, the superiority of treatment effect on the UL joints targeted by robotics remains unknown, especially for distal robotics15. Thus, comparative trials of different robotic types (eg, proximal versus distal robots) are warranted to tailor robot-aided UL rehabilitation to patient’s needs.

This study mainly compared the treatment effects of the InMotion ARM versus the InMotion WRIST robotic systems. The major difference between the 2 robotic devices is that the InMotion ARM focuses on training shoulder and elbow movements (ie, proximal UL), and the InMotion WRIST targets wrist and forearm movements (ie, distal UL). The proximal UL segments are critical for stability and transport of the arm, and the distal UL joints are mainly responsible for object manipulation and are important for performing daily activities17,18.

Motor control of the proximal UL and distal UL might be driven by different descending pathways19. The dorsolateral pathways (eg, corticospinal and rubrospinal tracts) are important for control of distal UL movements, and the ventromedial pathways (eg, reticulospinal, vestibulospinal, and tectospinal tracts) act more on the axial and proximal UL muscles and movements20,21. Although the neural bases act on proximal and distal UL segments and their functional roles appear to be different, direct comparisons of the clinical efficacy of proximal versus distal UL training in stroke patients are lacking.

Mazzeloni et al.22 used the same robotic systems to evaluate the treatment effects of proximal RT versus distal RT and proximal RT combined in 2 groups. However, the study goals of Mazzeloni et al. and this work are different. The effects of RT directly related to the UL segments specifically treated could not be drawn from the study findings of Mazzeloni et al. The 2 RT systems, InMotion ARM and InMotion WRIST, allow us to directly compare the outcomes affected by the proximal versus distal UL training.

In addition, recent reviews of RT have shown non-significant improvements or small effects on daily function after UL robotic rehabilitation in patients with stroke14,15,23. Major goals of stroke rehabilitation are to improve not only motor function but also functional performance on daily activities. Moreover, many patients were unable to translate the improvements of motor function and muscle strength to daily activity performance, which led to persistent functional dependence24. Therefore, this study provided functional task practice after RT to enhance the gains from proximal and distal UL robotic rehabilitation on motor function and muscle strength transfer into the patients’ daily functional performance.

The study purposes were to investigate the treatment effects of proximal-emphasized RT by using the InMotion ARM (P-IMT) versus distal-emphasized RT by using the InMotion WRIST (D-IMT) compared with a control treatment (CT) in patients with stroke. We designed a conventional rehabilitation program as the CT to provide a higher-level of clinical evidence, which decreased the influence of nondirective research environment and participant factors on treatment efficacy (eg, the Hawthorne effect), and to pose a more ethical approach instead of no treatment or placebo.[…]

Continue —>  Comparison of proximal versus distal upper-limb robotic rehabilitation on motor performance after stroke: a cluster controlled trial | Scientific Reports

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[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

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[ARTICLE] On neuromechanical approaches for the study of biological and robotic grasp and manipulation – Full Text

Abstract

Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological systems vs. engineering synthesis for the design and construction of robotic systems. The past 20 years have seen several conceptual advances in both fields and the quest to unify them. Chief among them is the reluctant recognition that their underlying fundamental mechanisms may actually share limited common ground, while exhibiting many fundamental differences. This recognition is particularly liberating because it allows us to resolve and move beyond multiple paradoxes and contradictions that arose from the initial reasonable assumption of a large common ground. Here, we begin by introducing the perspective of neuromechanics, which emphasizes that real-world behavior emerges from the intimate interactions among the physical structure of the system, the mechanical requirements of a task, the feasible neural control actions to produce it, and the ability of the neuromuscular system to adapt through interactions with the environment. This allows us to articulate a succinct overview of a few salient conceptual paradoxes and contradictions regarding under-determined vs. over-determined mechanics, under- vs. over-actuated control, prescribed vs. emergent function, learning vs. implementation vs. adaptation, prescriptive vs. descriptive synergies, and optimal vs. habitual performance. We conclude by presenting open questions and suggesting directions for future research. We hope this frank and open-minded assessment of the state-of-the-art will encourage and guide these communities to continue to interact and make progress in these important areas at the interface of neuromechanics, neuroscience, rehabilitation and robotics.

Introduction

Grasp and manipulation have captivated the imagination and interest of thinkers of all stripes over the millennia; and with enough reverence to even attribute the intellectual evolution of humans to the capabilities of the hand [123]. Simply put, manipulation function is one of the key elements of our identity as a species (for an overview, see [4]). This is a natural response to the fact that much of our physical and cognitive ability and well-being is intimately tied to the use of our hands. Importantly, we have shaped our tools and environment to match its capabilities (straightforward examples include lever handles, frets in string instruments, and touch-screens). This co-evolution between hand-and-world reinforces the notion that our hands are truly amazing and robust manipulators, as well as rich sensory, perceptual and even social information.

It then comes as no surprise that engineers and physicians have long sought to replicate and restore this functionality in machines—both as appendages to robots and prostheses attached to humans with missing upper limbs [5]. Robotic hands and prostheses have a long and illustrious history, with records of sophisticated articulated hands as early as Gottfried ‘Götz’ von Berlichingen’s iron hand in 1504 [6]. Other efforts [7891011] were often fueled by the injuries of war [12131415] and the Industrial Revolution [16]. The higher survival rate in soldiers who lose upper limbs [1718] and the continual emergence of artificial intelligence [1920] are but the latest impetus. Thus, the past 20 years have seen an explosion in designs, fueled by large scale governmental funding (e.g., DARPA’s Revolutionizing Prosthetics and HAPTIX projects, EU’s INPUT and SOFTPRO projects) and private efforts such as DeepMind. A new player in this space is the potentially revolutionary social network of high-quality amateur scientists as exemplified by the FABLAB movement [21]. They are enabled by ubiquitously accessible and inexpensive 3D printing and additive manufacturing tools [22], collaborative design databases (http://www.eng.yale.edu/grablab/openhand/ and others), and communities with formal journals (http://www.liebertpub.com/overview/3d-printing-and-additive-manufacturing/621/ and http://www.journals.elsevier.com/additive-manufacturing/). Grassroots communities have also emerged that can, for example, compare and contrast the functionality of prosthetic hands whose price differs by three orders of magnitude (http://www.3dprint.com/2438/50-prosthetic-3d-printed-hand).

For all the progress that we have seen, however, (i) robotic platforms remain best at pre-sorted, pick-and-place assembly tasks [23]; and (ii) many prosthetic users still prefer simple designs like the revered whole- or split-hook designs originally developed centuries ago [2425].

Why have robotic and prosthetic hands not come of age? This short review provides a current attempt to tackle this long-standing question in response to the current technological boom in robotic and prosthetic limbs. Similar booms occurred in response to upper limb injuries [25] after the Napoleonic [26], First [12] and Second World Wars [8], and—with the advent of powerful inexpensive computers—in response to industrial and space exploration needs in the 1960’s, 1970’s and 1980’s [272829303132]. We argue that a truly bio-inspired approach suffers, by definition, from both gaps in our understanding of the biology, and technical challenges in mimicking (what we understand of) biological sensors, motors and controllers. Although biomimicry is often not the ultimate goal in robotics in general, it is relevant for humanoids and prostheses. Thus, our approach is to clarify when and why a better understanding of the biology of grasp and manipulation would benefit robotic grasping and manipulation.

Similarly, why is our understanding of the nature, function and rehabilitation of biological arms and hands incomplete? Jacob Benignus Winsløw Jacques-Bénigne Winslow, (1669—1760) noted in his Exposition anatomique de la structure du corps humain (1732) that ‘The coordination of the muscles of the live hand will never be understood’ [33]. Interestingly, he is still mostly correct. As commented in detail before [4], there has been much work devoted to inferring the anatomical, physiological, neural and cognitive processes that produce the upper limb function we so dearly appreciate and passionately work to restore following trauma or pathology. We argue, as Galileo Galilei did, that mathematics and engineering have much to contribute to the understanding of biological systems. Without such a ‘mathematical language’ we run the risk, as Galileo put it, of ‘wandering in vain through a dark labyrinth’ [34]. Thus, this short review also attempts to point out important mathematical and engineering developments and advances that have helped our understanding of our hands.

This review first contrasts the fundamental differences between engineering and neuroscience approaches to biological robotic systems. Whereas the former applies engineering principles, the latter relies on scientific inference. We then discuss how the physics of the world provides a common ground between them because both types of systems have similar functional goals, and must abide by the same physical laws. We go on to evaluate how biological and robotic systems implement the necessary sensory and motor functions using the dramatically different anatomy, morphology and mechanisms available to each. This inevitably raises questions about differences in their sensorimotor control strategies. Whereas engineering system can be designed and manufactured to optimize well-defined functional features, biological systems evolve without such strict tautology. Biological systems likely evolve by implementing ecologically and temporally good-enough, sub-optimal or habitual control strategies in response to the current multi-dimensional functional constraints and goals in the presence of competition, variability, uncertainty, and noise. We conclude by exploring the notion that the functional versatility of biological systems that roboticists admire is, in fact, enabled by the very nonlinearities and complexities in anatomy, sensorimotor physiology, and neural function that engineering approaches often seek to avoid. […]

Continue —> On neuromechanical approaches for the study of biological and robotic grasp and manipulation | Journal of NeuroEngineering and Rehabilitation | Full Text

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[Abstract] A soft robotic supernumerary finger and a wearable cutaneous finger interface to compensate the missing grasping capabilities in chronic stroke patients

Abstract:

Stroke survivors who experience severe hemipare-sis often cannot completely recover the use of their hand and arm. Many of the rehabilitation devices currently available are designed to increase the functional recovery right after the stroke when, in some cases, biological restoring and plastic reorganization of the central nervous system can take place. However, this is not always the case. Even after extensive therapeutic interventions, the probability of regaining functional use of the impaired hand is low. In this respect, we present a novel robotic system composed of a supernumerary robotic finger and a wearable cutaneous finger interface. The supernumerary finger is used to help grasping objects while the wearable interface provides information about the forces exerted by the robotic finger on the object being held. We carried out two experiments, enrolling 16 healthy subjects and 2 chronic stroke patients. Results showed that using the supernumerary finger greatly improved the grasping capabilities of the subjects. Moreover, providing cutaneous feedback significantly improved the performance of the considered task and was preferred by all subjects.

Source: A soft robotic supernumerary finger and a wearable cutaneous finger interface to compensate the missing grasping capabilities in chronic stroke patients – IEEE Xplore Document

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