Posts Tagged hand rehabilitation

[Abstract] Design of a Low-Cost Exoskeleton for Hand Tele-Rehabilitation After Stroke

Abstract

The impairment of finger movements after a stroke results in a significant deficit in hands everyday performances. To face this kind of problems different rehabilitation techniques have been developed, nevertheless, they require the presence of a therapist to be executed. To overcome this issue have been designed several apparatuses that allow the patient to perform the training by itself. Thus, an easy to use and effective device is needed to provide the right training and complete the rehabilitation techniques in the best way. In this paper, a review of state of the art in this field is provided, along with an introduction to the problems caused by a stroke and the consequences for the mobility of the hand. Then follows a complete review of the low cost home based exoskeleton project design. The objective is to design a device that can be used at home, with a lightweight and affordable structure and a fast mounting system. For implementing all these features, many aspects have been analysed, starting from the rehabilitation requirements and the ergonomic issues. This device should be able to reproduce the training movements on an injured hand without the need for assistance by an external tutor.

via Design of a Low-Cost Exoskeleton for Hand Tele-Rehabilitation After Stroke | SpringerLink

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[Student thesis] Exoskeleton for hand rehabilitation – Full Text PDF

Abstract

This document presents the development of a first proposal prototype of a rehabilitation exoskeleton hand. The idea was to create a lighter, less complex and cheaper exoskeleton than the existing models in the market but efficient enough to carry out rehabilitation therapies.The methodology implemented consists of an initial literature review followed by data collection resulting in a pre-design in two dimensions using two different software packages, MUMSA and WinmecC. First, MUMSA provides the parameters data of the movement of the hand to be done accurately. With these parameters, the mechanisms of each finger are designed using WinmecC. Once the errors were solved and the mechanism was achieved, the 3D model was designed.The final result is presented in two printed 3D models with different materials. The models perform a great accurate level on the motion replica of the fingers by using rotary servos. The properties of the model can change depending on the used material. ABS material gives a flexible prototype, and PLA material does not achieve it. The use of distinct methods to print has a high importance on the difficulties of development throughout the entire process of production. Despite found difficulties in the production, the model was printed successfully, obtaining a compact, strong, lightweight and eco-friendly with the environment prototype.

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via Exoskeleton for hand rehabilitation

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[ARTICLE] Measurements by A LEAP-Based Virtual Glove for the Hand Rehabilitation – Full Text

Abstract

Hand rehabilitation is fundamental after stroke or surgery. Traditional rehabilitation requires a therapist and implies high costs, stress for the patient, and subjective evaluation of the therapy effectiveness. Alternative approaches, based on mechanical and tracking-based gloves, can be really effective when used in virtual reality (VR) environments. Mechanical devices are often expensive, cumbersome, patient specific and hand specific, while tracking-based devices are not affected by these limitations but, especially if based on a single tracking sensor, could suffer from occlusions. In this paper, the implementation of a multi-sensors approach, the Virtual Glove (VG), based on the simultaneous use of two orthogonal LEAP motion controllers, is described. The VG is calibrated and static positioning measurements are compared with those collected with an accurate spatial positioning system. The positioning error is lower than 6 mm in a cylindrical region of interest of radius 10 cm and height 21 cm. Real-time hand tracking measurements are also performed, analysed and reported. Hand tracking measurements show that VG operated in real-time (60 fps), reduced occlusions, and managed two LEAP sensors correctly, without any temporal and spatial discontinuity when skipping from one sensor to the other. A video demonstrating the good performance of VG is also collected and presented in the Supplementary Materials. Results are promising but further work must be done to allow the calculation of the forces exerted by each finger when constrained by mechanical tools (e.g., peg-boards) and for reducing occlusions when grasping these tools. Although the VG is proposed for rehabilitation purposes, it could also be used for tele-operation of tools and robots, and for other VR applications.

1. Introduction

Hand rehabilitation is extremely important for recovering from post-stroke or post-surgery residual impairments and its effectiveness depends on frequency, duration and quality of the rehabilitation sessions [1]. Traditional rehabilitation requires a therapist for driving and controlling patients during sessions. Procedure effectiveness is evaluated subjectively by the therapist, basing on experience. In the last years, several automated (tele)rehabilitation gloves, based on mechanical devices or tracking sensors, have been presented [2,3,4,5,6,7,8,9,10]. These gloves allow the execution of therapy at home and rehabilitation effectiveness can be analytically calculated and summarized in numerical parameters, controlled by therapists through Internet. Moreover, these equipment can be easily interfaced with virtual reality (VR) environments [11], which have been proven to increase rehabilitation efficacy [12]. Mechanical devices are equipped with pressure sensors and pneumatic actuators for assisting and monitoring the hand movements and for applying forces to which the patient has to oppose [13,14]. However, they are expensive, cumbersome, patient specific (different patients cannot reuse the same system) and hand specific (the patient cannot use the same system indifferently with both hands). Tracking-based gloves consist of computer vision algorithms for the analysis and interpretation of videos from depth sensing sensors to calculate hand kinematics in real time [10,15,16,17,18,19]. Besides depth sensors, LEAP [20] is a small and low-cost hand 3D tracking device characterized by high-resolution and high-reactivity [21,22,23], used in VR [24], and has been recently presented and tested with success in the hand rehabilitation, with exercises designed in VR environments [25]. Despite the advantages of using LEAP with VR, a single sensor does not allow accurate quantitative evaluation of hand and fingers tracking in case of occlusions. The system proposed in [10] consisted on two orthogonal LEAPs designed to reduce occlusions and to improve objective hand-tracking evaluation. The two sensors were fixed to a wood support that maintained them orthogonal each other. The previous prototype was useful to test the robustness of each sensor, in presence of the other, to the potential infra-red interferences, to evaluate the maintenance of the maximum operative range of each sensor and, finally, to demonstrate the hand tracking idea. However, it was imprecise, due to the usage of raw VG support and positioning system, the non-optimal reciprocal positioning of the sensors, and the impossibility of performing a reciprocal calibration independent of the sensors measurements. This fact did not allow the evaluation of the intrinsic precision of the VG and to perform accurate, real-time quantitative hand tracking measurements. In this paper, we present a method for constructing an engineered version of the LEAP based VG, a technique for its accurate calibration and for collecting accurate positioning measurements and high-quality evaluation of positioning errors, specific of VG. Moreover, real-time experimental hand tracking measurements were collected (a video demonstrating its real-time performance and precision was also provided in the Supplementary Materials), presented and discussed.[…]

 

Continue —>  Measurements by A LEAP-Based Virtual Glove for the Hand Rehabilitation

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Figure 1
VG mounted on its aluminium support.

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[Abstract] Fuzzy logic-based mobile computing system for hand rehabilitation after neurological injury.  

Abstract

BACKGROUND:

Effective neurological rehabilitation requires long term assessment and treatment. The rapid progress of virtual reality-based assistive technologies and tele-rehabilitation has increased the potential for self-rehabilitation of various neurological injuries under clinical supervision.

OBJECTIVE:

The objective of this study was to develop a fuzzy inference mechanism for a smart mobile computing system designed to support in-home rehabilitation of patients with neurological injury in the hand by providing an objective means of self-assessment.

METHODS:

A commercially available tablet computer equipped with a Bluetooth motion sensor was integrated in a splint to obtain a smart assistive device for collecting hand motion data, including writing performance and the corresponding grasp force. A virtual reality game was also embedded in the smart splint to support hand rehabilitation. Quantitative data obtained during the rehabilitation process were modeled by fuzzy logic. Finally, the improvement in hand function was quantified with a fuzzy rule database of expert opinion and experience.

RESULTS:

Experiments in chronic stroke patients showed that the proposed system is applicable for supporting in-home hand rehabilitation.

CONCLUSIONS:

The proposed virtual reality system can be customized for specific therapeutic purposes. Commercial development of the system could immediately provide stroke patients with an effective in-home rehabilitation therapy for improving hand problems.

Source: Fuzzy logic-based mobile computing system for hand rehabilitation after neurological injury. – PubMed – NCBI

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[ARTICLE] Neural Plasticity in Moderate to Severe Chronic Stroke Following a Device-Assisted Task-Specific Arm/Hand Intervention – Full Text

Currently, hand rehabilitation following stroke tends to focus on mildly impaired individuals, partially due to the inability for severely impaired subjects to sufficiently use the paretic hand. Device-assisted interventions offer a means to include this more severe population and show promising behavioral results. However, the ability for this population to demonstrate neural plasticity, a crucial factor in functional recovery following effective post-stroke interventions, remains unclear. This study aimed to investigate neural changes related to hand function induced by a device-assisted task-specific intervention in individuals with moderate to severe chronic stroke (upper extremity Fugl-Meyer < 30). We examined functional cortical reorganization related to paretic hand opening and gray matter (GM) structural changes using a multimodal imaging approach. Individuals demonstrated a shift in cortical activity related to hand opening from the contralesional to the ipsilesional hemisphere following the intervention. This was driven by decreased activity in contralesional primary sensorimotor cortex and increased activity in ipsilesional secondary motor cortex. Additionally, subjects displayed increased GM density in ipsilesional primary sensorimotor cortex and decreased GM density in contralesional primary sensorimotor cortex. These findings suggest that despite moderate to severe chronic impairments, post-stroke participants maintain ability to show cortical reorganization and GM structural changes following a device-assisted task-specific arm/hand intervention. These changes are similar as those reported in post-stroke individuals with mild impairment, suggesting that residual neural plasticity in more severely impaired individuals may have the potential to support improved hand function.

Introduction

Nearly 800,000 people experience a new or recurrent stroke each year in the US (1). Popular therapies, such as constraint-induced movement therapy (CIMT), utilize intense task-specific practice of the affected limb to improve arm/hand function in acute and chronic stroke with mild impairments (2, 3). Neuroimaging results partially attribute the effectiveness of these arm/hand interventions to cortical reorganization in the ipsilesional hemisphere following training in acute and mild chronic stroke (4). Unfortunately, CIMT requires certain remaining functionality in the paretic hand to execute the tasks, and only about 10% of screened patients are eligible (5), thus disqualifying a large population of individuals with moderate to severe impairments. Recently, studies using device-assisted task-specific interventions specifically targeted toward moderate to severe chronic stroke reported positive clinical results (68). However, these studies primarily focus on clinical measures, but it is widely accepted that neural plasticity is a key factor for determining outcome (911). Consequently, it remains unclear whether moderate to severe chronic stroke [upper extremity Fugl-Meyer Assessment (UEFMA) < 30] maintains the ability to demonstrate neural changes following an arm/hand intervention.

Neural changes induced by task-specific training have been investigated widely using animal models (12). For instance, monkeys or rodents trained on a skilled reach-to-grasp task express enlarged representation of the digits of the hand or forelimb in primary motor cortex (M1) following training as measured by intracortical microstimulation (13, 14). Additionally, rapid local structural changes in the form of dendritic growth, axonal sprouting, myelination, and synaptogenesis occur (1518). Importantly, both cortical and structural reorganization corresponds to motor recovery following rehabilitative training in these animals (19, 20).

The functional neural mechanisms underlying effective task-specific arm/hand interventions in acute and chronic stroke subjects with mild impairments support those seen in the animal literature described above. Several variations of task-specific combined arm/hand interventions, including CIMT, bilateral task-specific training, and hand-specific robot-assisted practice, have shown cortical reorganization such as increased sensorimotor activity and enlarged motor maps in the ipsilesional hemisphere related to the paretic arm/hand (2124). These results suggest increased recruitment of residual resources from the ipsilesional hemisphere and/or decreased recruitment of contralesional resources following training. Although the evidence for a pattern of intervention-driven structural changes remains unclear in humans, several groups have shown increases in gray matter (GM) density in sensorimotor cortices (25), along with increases in fractional anisotropy in ipsilesional corticospinal tract (CST) (26) following task-specific training in acute and chronic stroke individuals with mild impairments.

The extensive nature of neural damage in moderate to severe chronic stroke may result in compensatory mechanisms, such as contralesional or secondary motor area recruitment (27). These individuals show increased contralesional activity when moving their paretic arm, which correlates with impairment (28, 29) and may be related to the extent of damage to the ipsilesional CST (30). This suggests that more impaired individuals may increasingly rely on contralesional corticobulbar tracts such as the corticoreticulospinal tract to activate the paretic limb (29). These tracts lack comparable resolution and innervation to the distal parts of the limb, thus sacrificing functionality at the paretic arm/hand (31). Since this population is largely ignored in current arm/hand interventions, it is unknown whether an arm/hand intervention for these more severely impaired post-stroke individuals will increase recruitment of residual ipsilesional corticospinal resources. These ipsilesional CSTs maintain the primary control of hand and finger extensor muscles (32) and are thus crucial for improved hand function. Task-specific training assisted by a device may reengage and strengthen residual ipsilesional corticospinal resources by training distal hand opening together with overall arm use.

The current study seeks to determine whether individuals with moderate to severe chronic stroke maintain the ability to show cortical reorganization and/or structural changes alongside behavioral improvement following a task-specific intervention. We hypothesize that following a device-assisted task-specific intervention, moderate to severe chronic stroke individuals will show similar functional and structural changes as observed in mildly impaired individuals, demonstrated by (i) a shift in cortical activity related to paretic hand opening from the contralesional hemisphere toward the ipsilesional hemisphere and (ii) an increase in GM density in sensorimotor cortices in the ipsilesional hemisphere.[…]

Continue —> Frontiers | Neural Plasticity in Moderate to Severe Chronic Stroke Following a Device-Assisted Task-Specific Arm/Hand Intervention | Neurology

Figure 5. Statistical maps of gray matter (GM) density changes across all patients. Significant increases (red/yellow) and decreases (Blue) in GM density are depicted on sagittal, coronal, and axial sections (left to right) on Montreal Neurological Institute T1 slices. Sections show the maximum effect on (A) ipsilesioned M1/S1, (B) contralesional M1/S1, and (C) ipsilesional thalamus. Les indicates the side of the lesioned hemisphere. Color maps indicate the t values at every voxel. A statistical threshold was set at p < 0.001 uncorrected.

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[Abstract] Neural Plasticity in Moderate to Severe Chronic Stroke Following a Device-Assisted Task-Specific Arm/Hand Intervention

Currently, hand rehabilitation following stroke tends to focus on mildly impaired individuals, partially due to the inability for severely impaired subjects to sufficiently use the paretic hand. Device-assisted interventions offer a means to include this more severe population, and show promising behavioral results. However, the ability for this population to demonstrate neural plasticity, a crucial factor in functional recovery following effective post-stroke interventions, remains unclear. This study aimed to investigate neural changes related to hand function induced by a device-assisted task-specific intervention in individuals with moderate to severe chronic stroke (upper extremity Fugl Meyer < 30). We examined functional cortical reorganization related to paretic hand opening and gray matter structural changes using a multi-modal imaging approach. Individuals demonstrated a shift in cortical activity related to hand opening from the contralesional to the ipsilesional hemisphere following the intervention. This was driven by decreased activity in contralesional primary sensorimotor cortex and increased activity in ipsilesional secondary motor cortex. Additionally, subjects displayed increased gray matter density in ipsilesional primary sensorimotor cortex and decreased gray matter density in contralesional primary sensorimotor cortex. These findings suggest that despite moderate to severe chronic impairments, post-stroke participants maintain ability to show cortical reorganization and gray matter structural changes following a device-assisted task-specific arm/hand intervention. These changes are similar as those reported in post-stroke individuals with mild impairment, suggesting that residual neural plasticity in more severely impaired individuals may have the potential to support improved hand function.

Source: Neural Plasticity in Moderate to Severe Chronic Stroke Following a Device-Assisted Task-Specific Arm/Hand Intervention

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[Editorial] Advances in Rehabilitation and Assistive Robots for Restoring Limb Function in Persons with Movement Disorders. 

Editorial

Advances in Rehabilitation and Assistive Robots for Restoring Limb Function in Persons with Movement Disorders

1Department of Health Care Sciences, UT Southwestern Medical Center at Dallas, Dallas, TX 75390, USA
2Research Center for Neural Engineering, The Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Shenzhen 518055, China
3School of Energy Systems, Lappeenranta University of Technology, 53851 Lappeenranta, Finland
4The Robotics Research Group, College of Engineering, Peking University, Beijing 100871, China
5The Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL 60611, USA
6Faculty of Health Sciences and Medicine, Bond University, Robina, QLD 4226, Australia

Received 3 July 2016; Accepted 3 July 2016

Copyright © 2016 Fan Gao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


People with movement disorders are plagued with debilitating conditions, which significantly degrade their quality of life. Traditional rehabilitation typically involves intensive interaction between patients and therapists. While effective, traditional rehabilitation cannot keep abreast of the increasing patient population primarily attributed to a higher surviving rate after diseases and/or injuries. Furthermore, patients living in the rural areas have fairly limited access to rehabilitation services. In the past two decades, tremendous efforts have been put into developing rehabilitation and assistive robots to facilitate the rehabilitation training while relieving the physical involvement of therapists and/or lowering the related cost. Most notably, the rehabilitation and assistive robots have been significantly advanced with developments in actuators, sensors, microprocessors, and mobile software platforms. However, unlike traditional robotics, the intimate interaction between robot and human in rehabilitation robots indicates that the success is also closely related to a thorough understanding of the human neuromuscular aspects and human-machine interaction.

This special issue primarily aims to gather the latest achievements in rehabilitation robots, exoskeletons, and prostheses including the following topics:

(a) development of rehabilitation robots, exoskeleton, and upper/lower limb prostheses driven by bionics;
(b) functional evaluation of rehabilitation robots, exoskeleton, and upper/lower limb prostheses with an emphasis on human movement biomechanics;
(c) musculoskeletal modeling and simulation of human movements while wearing exoskeleton or prostheses;
(d) noninvasive human-machine interface based on electromyography and/or electroencephalogram;
(e) sensors for monitoring kinematics/kinetics, as well as biological signals in real time;
(f) innovative actuators and control algorithms applied to rehabilitation robots, exoskeletons, and prostheses.

In this special issue, collective studies address the aforementioned key elements via both technical and biomechanical approaches. A reconfigurable robotic hand exoskeleton was proposed to meet the fast growing need in hand rehabilitation. A novel control algorithm integrating sliding model control with cerebellar model articulation controller neural network was implemented in lower limb exoskeleton to enhance the coordination between patient and exoskeleton. An upper limb exoskeleton was enhanced with integrated optical cameras to offer more accurate estimation of joint posture than traditional motion capture system. A hybrid upper limb rehabilitation system consisting of a shoulder-elbow-forearm exoskeleton and a robotic manipulator was validated and tested in the clinic. The characteristics of muscle-tendon stimulation such as perception threshold and vibration frequency significantly influenced the muscle forces as well as the reaction time. Patellar retention was found to be superior to patellar replacement in knee arthroplasty via a comprehensive computer simulation. These collective studies, as part of the latest representative work, offered some new insights into the development and implementation of rehabilitation and assistive robots.

Fan Gao
Guanglin Li
Huapeng Wu
Qining Wang
Jie Liu
Justin Keogh

Source: Advances in Rehabilitation and Assistive Robots for Restoring Limb Function in Persons with Movement Disorders

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[ARTICLE] Study of multi-sensory stimulation for the design of hand rehabilitation equipment for stroke patients

Abstract

Stroke has long been a critical health issue in adults, affecting their physical, cognitive, and emotional functioning.

The purpose of this study was to develop hand rehabilitation equipment based on multi-sensory stimulation therapy for stroke patients. An experiment was conducted with seventeen professional occupational therapists (each having more than five years of work experience) who individually evaluated the effectiveness of hand rehabilitation using seven hand gestures with two treatment approaches (top-down and bottom-up) and their corresponding six rehabilitation techniques (top-down: mirror therapy and auditory stimulation; bottom-up: tactile stimulation, thermal stimulation, electrical stimulation, and vibration stimulation). Our study used a within-subject partial hierarchical design, where rehabilitation techniques were partially nested within treatment approaches and crossed with hand gestures.

Analyses of the three-way factorial analysis of variance showed that rehabilitation technique had a significant effect and that vibration stimulation and mirror therapy were most effective.

Based on the findings of this study, multi-sensory stimulation equipment (combining vibration stimulation and mirror therapy) was designed to improve the sensorimotor ability of stroke patients.

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[iPad App] Tyromotion – Finger(s) in motion

iPad Screenshot 1

Fingermotion

This professional App was designed for training of your fingerskills on your iPad!

It consists of various courses to be traced with one or multiple fingers. So you can train actively selective finger movements and fine motor skills. Your training success can be shown through direct optical feedback. Try this challenging, but motivating, entirely novel way of hand rehabilitation!

Tyromotion – Creating the future of rehabilitation!

Download the App here

via Tyromotion – Finger(s) in motion.

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[BROCHURE] GLOREHA Hand Rehabilitation Glove

Gloreha® is an innovative device for the rehabilitation of patients with any hand deficiency. It allows an effective, intensive, early, stimulant and flexible neuromotor treatment. While the patient can follow the exercise through 3D animation on the screen, a comfortable and light glove mobilizes the fingers’ joints. Hand movements are connected with video and audio effects that stimulate the neurocognitive recovery. Gloreha allows varied and longer therapies with a minimal overview by the therapists.

Get the Broshure –> GLOREHA Hand Rehabilitation Glove

 

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