Archive for category Robotics

[Abstract] A soft supernumerary robotic finger and mobile arm support for grasping compensation and hemiparetic upper limb rehabilitation

Abstract

In this paper, we present the combination of our soft supernumerary robotic finger i.e. Soft-SixthFinger with a commercially available zero gravity arm support, the SaeboMAS. The overall proposed system can provide the needed assistance during paretic upper limb rehabilitation involving both grasping and arm mobility to solve task-oriented activities. The Soft-SixthFinger is a wearable robotic supernumerary finger designed to be used as an active assistive device by post stroke patients to compensate the paretic hand grasp. The device works jointly with the paretic hand/arm to grasp an object similarly to the two parts of a robotic gripper. The SaeboMAS is a commercially available mobile arm support to neutralize gravity effects on the paretic arm specifically designed to facilitate and challenge the weakened shoulder muscles during functional tasks. The proposed system has been designed to be used during the rehabilitation phase when the arm is potentially able to recover its functionality, but the hand is still not able to perform a grasp due to the lack of an efficient thumb opposition. The overall system also act as a motivation tool for the patients to perform task-oriented rehabilitation activities.

With the aid of proposed system, the patient can closely simulate the desired motion with the non-functional arm for rehabilitation purposes, while performing a grasp with the help of the Soft-SixthFinger. As a pilot study we tested the proposed system with a chronic stroke patient to evaluate how the mobile arm support in conjunction with a robotic supernumerary finger can help in performing the tasks requiring the manipulation of grasped object through the paretic arm. In particular, we performed the Frenchay Arm Test (FAT) and Box and Block Test (BBT). The proposed system successfully enabled the patient to complete tasks which were previously impossible to perform.

Source: A soft supernumerary robotic finger and mobile arm support for grasping compensation and hemiparetic upper limb rehabilitation

, , , , , , , , , , ,

Leave a comment

[VIDEO] Fourier X1 Exoskeleton – Fourier Intelligence – YouTube

Δημοσιεύτηκε στις 23 Μαρ 2017

At Fourier Intelligence, we do not believe these people are fated to sit on the wheelchair in their rest life. To let them stand up, and to allow them to walk again, we started to develop a genuinely new exoskeleton products- The Fourier X1

, , , ,

Leave a comment

[Abstract+References] A Novel Human-Robot Cooperative Method for Upper Extremity Rehabilitation

Abstract

There are a certain number of arm dysfunction patients whose legs could move. Considering the neuronal coupling between arms and legs during locomotion, this paper proposes a novel human-robot cooperative method for upper extremity rehabilitation. Legs motion is considered at the passive rehabilitation training of disabled arm, and its traversed trajectory is represented by the patient trunk motion. A Kinect based vision module, two computers and a WAM robot construct the human-robot cooperative upper extremity rehabilitation system. The vision module is employed to track the position of the subject trunk in horizontal; the WAM robot is used to guide the arm of post-stroke patient to do passive training with the predefined trajectory, and meanwhile the robot follows the patient trunk movement which is tracked by Kinect in real-time. A hierarchical fuzzy control strategy is proposed to improve the position tracking performance and stability of the system, which consists of an external fuzzy dynamic interpolation strategy and an internal fuzzy PD position controller. Four experiments were conducted to test the proposed method and strategy. The experimental results show that the patient felt more natural and comfortable when the human-robot cooperative method was applied; the subject could walk as he/she wished in the visual range of Kinect. The hierarchical fuzzy control strategy performed well in the experiments. This indicates the high potential of the proposed human-robot cooperative method for upper extremity rehabilitation.

Source: A Novel Human-Robot Cooperative Method for Upper Extremity Rehabilitation | SpringerLink

, , , , , ,

Leave a comment

[ARTICLE] Effectiveness of robotic assisted rehabilitation for mobility and functional ability in adult stroke patients: a systematic review protocol – Full Text

Abstract

Review question/objective: The objective of this review is to synthesize the best available evidence on the effectiveness of robotic assistive devices in the rehabilitation of adult stroke patients for recovery of impairments in the upper and lower limbs. The secondary objective is to investigate the sustainability of treatment effects associated with use of robotic devices.

The specific review question to be addressed is: can robotic assistive devices help adult stroke patients regain motor movement of their upper and lower limbs?

Background

Stroke is a leading cause of long-term disability and is the third most common cause of mortality in developed countries with 15 million people suffering a stroke yearly.1 Different parts of the brain control different bodily functions. If a person survives a stroke, the effects can vary, depending on the location of brain damage, severity and duration of the stroke. Broadly, the effects of stroke can be physical, cognitive or emotional in nature. In terms of the physical effects of stroke, the loss of motor abilities of the limbs presents significant challenges for patients, as their mobility and activities of daily living (ADLs) are affected. The upper or lower limbs can experience weakness (paresis) or paralysis (plegia), with the most common type of limb impairment being hemiparesis, which affects eight out of 10 stroke survivors.2 Other physical effects of stroke are loss of visual fields, vision perception, difficulty swallowing (dysphagia), apraxia of speech, incontinence, joint pain or neuropathic pain (caused by inability of the brain to correctly interpret sensory signals in response to stimuli on the affected limbs). Cognitive effects of stroke are aphasia, memory loss and vascular dementia. Stroke patients can lose the ability to understand speech or the capacity to read, think or reason, and normal mental tasks can present big challenges, affecting their quality of life. The drastic changes in physical and cognitive abilities caused by stroke also lead to emotional effects for stroke patients. Stroke survivors can experience depression when they encounter problems in doing tasks that they can easily do pre-stroke. Along with depression, they can experience a lack of motivation and mental fatigue.

For stroke patients, rehabilitation is the pathway to regaining or managing their impaired functions. There is no definite end to recovery but the most rapid improvement is within the first six months post stroke.3 Before a patient undergoes rehabilitation, an assessment is first done to determine if a patient is medically stable and fit for a rehabilitation program. If the patient is assessed to be suitable, then depending on the level of rehabilitative supervision required, the patient could undergo rehabilitation in various settings – as an in-patient/outpatient (at either a hospital or nursing facility) or at home.3,4Rehabilitation should be administered by a multi-disciplinary team of physiotherapists, occupational therapist, speech therapist and neuropsychologists, who work together to offer an integrated, holistic rehabilitation therapy.4 Depending on the type of impairment, rehabilitation specialists will assess the appropriate therapies needed and set realistic goals for patients to achieve. Generally, stroke patients should be given a minimum of 45 min for each therapy session over at least five days per week, as long as the patient can tolerate the rehabilitation regimen.3

One of the main goals in stroke rehabilitation is the restoration of motor skills, and this involves patients undergoing repetitive, high-intensity, task-specific exercises that enable them to regain their motor and functional abilities.5,6 It is theorized that the brain is plastic in nature and that repetitive exercises over long periods can enable the brain to adapt and regain the motor functionality that has been repeatedly stimulated.7This involves the formation of new neuronal interconnections that enable the re-transmission of motor signals.8

Source: Effectiveness of robotic assisted rehabilitation for mobilit… : JBI Database of Systematic Reviews and Implementation Reports

, , , , , , ,

Leave a comment

[ARTICLE] Neuroplastic Changes Following Brain Ischemia and their Contribution to Stroke Recovery: Novel Approaches in Neurorehabilitation – Full Text

Ischemic damage to the brain triggers substantial reorganization of spared areas and pathways, which is associated with limited, spontaneous restoration of function. A better understanding of this plastic remodeling is crucial to develop more effective strategies for stroke rehabilitation. In this review article, we discuss advances in the comprehension of post-stroke network reorganization in patients and animal models. We first focus on rodent studies that have shed light on the mechanisms underlying neuronal remodeling in the perilesional area and contralesional hemisphere after motor cortex infarcts. Analysis of electrophysiological data has demonstrated brain-wide alterations in functional connectivity in both hemispheres, well beyond the infarcted area. We then illustrate the potential use of non-invasive brain stimulation (NIBS) techniques to boost recovery. We finally discuss rehabilitative protocols based on robotic devices as a tool to promote endogenous plasticity and functional restoration.

Introduction

Following an ischemic insult within the motor cortex, one or more body parts contralateral to the infarct result impaired or paretic. The degree of the motor impairment depends on many factors, such as the extent of the infarct, the identity of the damaged region(s) and the effectiveness of the early medical care. Substantial functional recovery can occur in the first weeks after stroke, mainly due to spontaneous mechanisms (Kwakkel et al., 2004; Cramer, 2008; Darling et al., 2011; Ward, 2011; Grefkes and Fink, 2014). About 26% of stroke survivors are able to carry on everyday activities (Activity of Daily Living or ADLs, i.e., eating, drinking, walking, dressing, bathing, cooking, writing) without any help, but another 26% is forced to shelter in a nursing home (Carmichael, 2005). Impairments of upper and lower limbs are particularly disabling as they impact on the degree of independence in ADLs. Overall, a significant percentage of the patients exhibit persistent disability following ischemic attacks. Therefore, it is critical to increase our knowledge of post-stroke neuroplasticity for implementing novel rehabilitative strategies. In this review we summarize data about plastic reorganizations after injury, both in the ipsilesional and contralesional hemisphere. We also describe non-invasive brain stimulation (NIBS) techniques and robotic devices for stimulating functional recovery in humans and rodent stroke models.

Neuroplasticity After Stroke

The term brain plasticity defines all the modifications in the organization of neural components occurring in the central nervous system during the entire life span of an individual (Sale et al., 2009). Such changes are thought to be highly involved in mechanisms of aging, adaptation to environment and learning. Moreover, neuronal plastic phenomena are likely to be at the basis of adaptive modifications in response to anatomical or functional deficit or brain damage (Nudo, 2006). Ischemic damage causes a dramatic alteration of the entire complex neural network within the affected area. It has been amply demonstrated, by many studies, that the cerebral cortex exhibits spontaneous phenomena of brain plasticity in response to damage (Gerloff et al., 2006; Nudo, 2007). The destruction of neural networks indeed stimulates a reorganization of the connections and this rewiring is highly sensitive to the experience following the damage (Stroemer et al., 1993; Li and Carmichael, 2006). Such plastic phenomena involve particularly the perilesional tissue in the injured hemisphere, but also the contralateral hemisphere, subcortical and spinal regions.

Continue —> Frontiers | Neuroplastic Changes Following Brain Ischemia and their Contribution to Stroke Recovery: Novel Approaches in Neurorehabilitation | Frontiers in Cellular Neuroscience

Figure 3. Example of a novel robotic system that integrates functional grasping, active reaching arm training and bimanual tasks. An example of a novel robotic system that integrates functional grasping, active reaching arm training and bimanual tasks, consisting of: (i) Virtual Reality: software applications composed of rehabilitative and evaluation tasks; (ii) TrackHold: robotic device to support the weight of the user’s limb during tasks execution; (iii) Robotic Hand Exos: active hand exoskeleton to assist grasping tasks; and (iv) Handgrip sensors to support the bilateral grasping training and evaluation (modified from Sgherri et al., 2017).

, , , , , , ,

Leave a comment

[ARTICLE] A wearable exoskeleton suit for motion assistance to paralysed patients – Full Text

Summary

Background/Objective

The number of patients paralysed due to stroke, spinal cord injury, or other related diseases is increasing. In order to improve the physical and mental health of these patients, robotic devices that can help them to regain the mobility to stand and walk are highly desirable. The aim of this study is to develop a wearable exoskeleton suit to help paralysed patients regain the ability to stand up/sit down (STS) and walk.

Methods

A lower extremity exoskeleton named CUHK-EXO was developed with considerations of ergonomics, user-friendly interface, safety, and comfort. The mechanical structure, human-machine interface, reference trajectories of the exoskeleton hip and knee joints, and control architecture of CUHK-EXO were designed. Clinical trials with a paralysed patient were performed to validate the effectiveness of the whole system design.

Results

With the assistance provided by CUHK-EXO, the paralysed patient was able to STS and walk. As designed, the actual joint angles of the exoskeleton well followed the designed reference trajectories, and assistive torques generated from the exoskeleton actuators were able to support the patient’s STS and walking motions.

Conclusion

The whole system design of CUHK-EXO is effective and can be optimised for clinical application. The exoskeleton can provide proper assistance in enabling paralysed patients to STS and walk.

Continue —> A wearable exoskeleton suit for motion assistance to paralysed patients

 

Figure 1

Figure 1. The wearable exoskeleton suit CUHK-EXO. (A) A patient with the wearable exoskeleton suit CUHK-EXO supported by a pair of smart crutches; (B) diagram of the overall mechanical structure of CUHK-EXO; (C) waist structure of CUHK-EXO; (D) thigh structure of CUHK-EXO; (E) shank structure of CUHK-EXO. (F) foot structure of CUHK-EXO.

, , , ,

Leave a comment

[ARTICLE] The application of virtual reality in neurorehabilitation: motor re-learning supported by innovative technologies – Full Text

Abstract
The motor function impairment resulting from a stroke injury has a negative impact on autonomy, the activities of daily living thus the individuals affected by a stroke need long-term rehabilitation. Several studies have demonstrated that learning new motor skills is important to induce neuroplasticity and functional recovery. Innovative technologies used in rehabilitation allow one the possibility to enhance training throughout generated feedback. It seems advantageous to combine traditional motor rehabilitation with innovative technology in order to promote motor re-learning and skill re-acquisition by means of enhanced training. An environment enriched by feedback involves multiple sensory modalities and could promote active patient participation. Exercises in a virtual environment contain elements necessary to maximize motor learning, such as repetitive
and diffe-rentiated task practice and feedback on the performance and results. The recovery of the limbs motor function in post-stroke subjects is one of the main therapeutic aims for patients and physiotherapist alike. Virtual reality as well as robotic devices allow one to provide specific treatment based on the reinforced feedback in a virtual environment (RFVE), artificially augmenting the sensory information coherent with the real-world objects and events. Motor training based on RFVE is emerging as an effective motor learning based techniques for the treatment of the extremities.

Continue —> The application of virtual reality in neurorehabilitation: motor re-learning supported by innovative technologies (PDF Download Available)

, , , ,

Leave a comment

[ARTICLE] Advanced Myoelectric Control for Robotic Hand-Assisted Training: Outcome from a Stroke Patient – Full Text

A hand exoskeleton driven by myoelectric pattern recognition was designed for stroke rehabilitation. It detects and recognizes the user’s motion intent based on electromyography (EMG) signals, and then helps the user to accomplish hand motions in real time. The hand exoskeleton can perform six kinds of motions, including the whole hand closing/opening, tripod pinch/opening, and the “gun” sign/opening. A 52-year-old woman, 8 months after stroke, made 20×2-hour visits over 10 weeks to participate in robot-assisted hand training. Though she was unable to move her fingers on her right hand before the training, EMG activities could be detected on her right forearm. In each visit, she took 4×10-minute robot-assisted training sessions, in which she repeated the aforementioned six motion patterns assisted by our intent-driven hand exoskeleton. After the training, her grip force increased from 1.5 kg to 2.7 kg, her pinch force increased from 1.5 kg to 2.5 kg, her score of Box & Block test increased from 3 to 7, her score of Fugl-Meyer (Part C) increased from 0 to 7, her hand function increased from Stage 1 to Stage 2 in Chedoke-McMaster assessment. The results demonstrate the feasibility of robot-assisted training driven by myoelectric pattern recognition after stroke.

Introduction

Robot-assisted upper limb training is considered to be more efficient (1) and economic (2) than conventional therapy in neurorehabilitation. Controlling the robot with the user’s own electromyography (EMG) signals connects the user’s intended motion and his actual movements. It can therefore enhance therapeutic effects and promote motor learning (35). Various EMG-driven robots and exoskeletons have been developed for neurorehabilitation (68), primarily based on one-to-one mapping, which typically maps one channel of EMG signal to a corresponding single degree-of-freedom (DOF) or variable such as speed and torque using a conventional “on-off” or proportional strategy. Robots based on such control strategy work well on training joints with only a few DOFs such as elbow and wrist. However, a human hand has up to 27 DOFs (9) and is controlled by complex temporal and spatial coordination of multiple muscles. It is therefore not feasible to regain hand dexterity through conventional control strategies. Myoelectric pattern-recognition techniques have been developed to extract motion intentions from EMG signals (10, 11). The extracted intentions can then be used to control a multiple-DOF robot such as a prosthesis (12). Previous studies have also shown that motion intentions can still be extracted after neurological impairment (1315). We therefore developed an intent-driven hand training system. The system employs an exoskeleton hand, which is controlled by myoelectric pattern recognition. As soon as the user’s intention is detected (usually within 250 ms), the system is able to assist to accomplish the intended motions (16).

Case Report

Subject

A 52-year-old woman participated in this robotic hand-assisted training 8 months after stroke. She was right-handed before stroke and had hemiplegia on her right side after her stroke. She was able to walk independently with an ankle foot orthosis but had difficulties in moving her right arm. Her fingers were flexed naturally. She was unable to move any of the fingers on her right hand, but EMG signals were able to be recorded from her forearm. Her Fugl–Meyer score (Part A–D, max 66) was 16, with a 0 in Part C (Hand, max 14). She had no pain when her whole hand was passively opened or closed. She did not receive any other hand or upper limb therapies while participating in this study. During her visits, she was able to understand and follow all the instructions.

Exoskeleton Hand

The exoskeleton hand, Hand of Hope (Rehab-Robotics, Hong Kong), was used in this study to help the subject move her hand (Figure 1). The exoskeleton hand has five individual fingers. Each finger is actuated by a linear actuator that can pull and push linearly. The mechanical design of the fingers converts these linear movements into the rotations of a virtual metacarpophalangeal (MCP) joint and a virtual proximal interphalangeal (PIP) joint. Both joints rotate together to help the hand perform closing and opening movements (7). The motion range is 55° and 65° for MCP and PIP joints, respectively. The subject’s palm and five fingers are fixed to the exoskeleton hand with Velcro belts. Each finger can be bent or straightened individually by the exoskeleton hand. The exoskeleton hand stands on a brace, which also supports the subject’s forearm, so that the subject can be totally relaxed when attached to the exoskeleton. The exoskeleton hand used in this study can perform six different motion patterns, including hand closing (HC); hand opening (HO); thumb, index, and middle fingers closing (TIMC or tripod pinch); thumb, index, and middle fingers opening; middle, ring, and little fingers closing (MRLC or the “gun” sign); and middle, ring, and little fingers opening. The exoskeleton hand can perform HC, TIMC, or MRLC when it is open. However, after performing any one from these three patterns, it can only return to the original open status (e.g., there is no direct way from the “tripod pinch” to the “gun” sign).

Figure 1. Training with the exoskeleton hand driven by myoelectric pattern recognition.

Continue —> Frontiers | Advanced Myoelectric Control for Robotic Hand-Assisted Training: Outcome from a Stroke Patient | Stroke

, , , , , , , ,

Leave a comment

[ARTICLE] Immediate affective responses of gait training in neurological rehabilitation: A randomized crossover trial – Full Text HTML

Abstract

Objective: To examine the immediate effects of physical therapy and robotic-assisted gait training on affective responses of gait training in neurological rehabilitation.

Design: Randomized crossover trial with blinded observers.

Patients: Sixteen patients with neurological disorders (stroke, traumatic brain injury, spinal cord injury, multiple sclerosis).

Methods: All patients underwent 2 single treatment sessions: physical therapy and robotic-assisted gait training. Both before and after the treatment sessions, the self-report Mood Survey Scale was used to assess the effects of the treatment on distinct affective states. The subscales of the Mood Survey Scale were tested for pre–post changes and differences in effects between treatments, using non-parametric tests.

Results: Fourteen participants completed the study. Patients showed a significant increase in activation (r = 0.55), elation (r = 0.79), and calmness (r = 0.72), and a significant decrease in anger (r = 0.64) after robotic-assisted gait training compared with physical therapy.

Conclusion: Affective responses might be positively influenced by robotic-assisted gait training, which may help to overcome motivational problems during the rehabilitation process in neurological patients.

Introduction

Patients with neurological impairment are known to have reduced quality of life and increased risk for depressive symptoms, which may hinder their ability to perform daily rehabilitation programmes, such as physical therapy (PT) or robotic-assisted gait training (RAGT) (1). During the continuum of rehabilitation it is necessary to consider factors such as choice and enjoyment in order to determine specifically how an individual would participate in rehabilitation programmes. The inclusion of participation scales is recommended when assessing the outcome of rehabilitation programmes (2). According to Self-Determination Theory (3), positive affective responses (e.g. activation, elation, or calmness) are connected with high intrinsic motivation and are an important regulation process in human behaviour. Therefore affective responses to the treatment sessions, as defined by Ekkekakis & Petruzello (4), might be important predictors of motivation, adoption, and maintenance of treatment regimes in the rehabilitation process.

Fatigue is a common and distressing complaint among people with neurological impairment (5). Patients often are afraid that engagement in exercise may increase fatigue (6). In patients with traumatic brain injury, “lack of energy” was rated as 1 of the top 5 problems for participation (7). Therefore it is important to emphasize that it is more likely that a higher level of energy will be achieved after exercise (8, 9). Although not yet a widely recognized determinant of exercise behaviour, affective valence is viewed in psychology and behavioural economics as one of the major factors in human decision-making (10). Findings from exercise psychology have demonstrated that the affective components of pleasure and activation might be crucial for bridging the intention–behaviour gap at the beginning of engagement in exercise (10). Regular participation in physical activity, in the long-term, may be mediated by an individual’s belief in the exercise–psychological wellbeing association. It may also lead to anti-depressive effects (11). Both PT and RAGT can be considered as forms of physical activity; therefore one might speculate that the effects mentioned above could be transferred to neurological patients. While increases in energy and mood in response to a single bout of moderate intensity exercise have been shown in healthy people and several risk-groups (6, 8, 9), no such study has been carried out involving neurological patients.

To our knowledge, only 2 studies concerning RAGT and psychological effects have been published. Koenig et al. (12) described a method to observe mental engagement during RAGT. Recently, Calabro et al. (13) reported positive long-term effects of RAGT on mood and coping strategies in a case study. To our knowledge, apart from these studies, affective responses have not been researched in PT or RAGT.

Thus, the aim of this study was to determine, for patients with neurological impairment: (i) whether a single session of PT and RAGT has immediate effects on affective responses (e.g. activation, elation, or calmness) and; (ii) whether possible affective responses differ between PT and RAGT.

Continue —> Journal of Rehabilitation Medicine – Immediate affective responses of gait training in neurological rehabilitation: A randomized crossover trial – HTML

, , , , ,

Leave a comment

[Abstract+References] Architectural Design of a Cloud Robotic System for Upper-Limb Rehabilitation with Multimodal Interaction 

Abstract

The rise in the cases of motor impairing illnesses demands the research for improvements in rehabilitation therapy. Due to the current situation that the service of the professional therapists cannot meet the need of the motor-impaired subjects, a cloud robotic system is proposed to provide an Internet-based process for upper-limb rehabilitation with multimodal interaction.

In this system, therapists and subjects are connected through the Internet using client/server architecture. At the client site, gradual virtual games are introduced so that the subjects can control and interact with virtual objects through the interaction devices such as robot arms. Computer graphics show the geometric results and interaction haptic/force is fed back during exercising. Both video/audio information and kinematical/physiological data are transferred to the therapist for monitoring and analysis.

In this way, patients can be diagnosed and directed and therapists can manage therapy sessions remotely. The rehabilitation process can be monitored through the Internet. Expert libraries on the central server can serve as a supervisor and give advice based on the training data and the physiological data. The proposed solution is a convenient application that has several features taking advantage of the extensive technological utilization in the area of physical rehabilitation and multimodal interaction.

Supplementary material

11390_2017_1720_MOESM1_ESM.pdf (49 kb)

ESM 1(PDF 49 kb)

Source: Architectural Design of a Cloud Robotic System for Upper-Limb Rehabilitation with Multimodal Interaction | SpringerLink

, , , , , , ,

Leave a comment

%d bloggers like this: