[Abstract] Recent Patents on Wrist Rehabilitation Equipment

Abstract

Background: Wrist activity is very frequent in our daily routine, and is under heavy load during the movement such as supporting and push-pull. So wrist can get damaged very easily in daily life. Based on the rehabilitation medicine and ergonomics, the particularity and complexity of human limbs should be considered in the design process. During the treatment process, the wrist joint rehabilitation equipment can provide stable, accurate, safe and comfortable repeated rehabilitation training for patients. The use of rehabilitation training equipment can greatly reduce the cost of treatment and improve the rehabilitation efficiency.

Objective: The related patents of rehabilitation training equipment for wrist joint will be reviewed, and the structure and working principle of these equipments will be illustrated. The results of the analysis provide some meaningful reference for the optimal design of the wrist joint.

Methods: Based on the comparative analysis of the latest patents related to wrist rehabilitation equipment, the key problems and future development of the rehabilitation equipment are put forward.

Results: The patents of the rehabilitation training equipment for the wrist are classified in the paper. Studies show that remarkable improvements have been achieved in the invention of the wrist rehabilitation equipment.

Conclusion: In the future, the mechanical design, control system and rehabilitation strategy of wrist rehabilitation equipment should be further studied.

 

via Recent Patents on Wrist Rehabilitation Equipment: Ingenta Connect

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[Abstract] Design and development of an upper limb rehabilitation robotic system – IEEE Conference Publication

Abstract

This paper presents ongoing research activities for the designing and development of an upper limb rehabilitation robotic system needed by the Prokinetic Rehabilitation Clinic. Prokinetic therapists identified the need of a passive rehabilitation robotic system (RRS) with 3 degrees of freedom for upper limb. The medical and technical requirements analysis for an upper limb rehabilitation robotic system, the video motion analysis were carried out, and the mechanical, actuation, control systems and human-machine interface of the RRS were designed and developed. The results of designing and developing an upper limb rehabilitation robotic system are presented here.

Published in: 2018 19th International Carpathian Control Conference (ICCC)

Date of Conference: 28-31 May 2018

 

via Design and development of an upper limb rehabilitation robotic system – IEEE Conference Publication

[Abstract] Kinematic analysis and control for upper limb robotic rehabilitation system – IEEE Conference Publication

Abstract

Present physical rehabilitation practice implies one-to-one therapist — patient interactions. This leads to shortage of therapists and high costs for patient or healthcare insurance systems. Along with Prokinetic Rehabilitation Clinic, we proposed a new intelligent, adaptive robotic system (RAPMES), which can provide the rehabilitation protocols, defined by a therapist, for the wrist and elbow of upper limb, considering the patient reactions and based on real-time feedback. RAPMES is a passive rehabilitation robotic system (RRS) with 3 degrees of freedom, and assists the rehabilitation process for elbow, forearm and wrist movements. Computation of the kinematic model for the RAPMES robotic device is required in order to determine the parameters associated with the mechanical joints, so that the experimental model executes certain trajectories in space. In this paper, we will present both forward and inverse kinematics determined for the experimental model. The kinematic model was implemented in Matlab environment, and we present a series of simulations, conducted in order to validate the proposed kinematic model. Then, we impose the functional movements (determined using the real-time video motion analysis system, as polynomial movement functions) as input to the kinematic model, and we present a series of simulations and results. The RAPMES control algorithm includes the kinematic model, and uses the polynomial movement functions as control input.

Published in: 2018 19th International Carpathian Control Conference (ICCC)

Date of Conference: 28-31 May 2018

 

I. Introduction

Statistics shows that, at European Union level, the upper limb is second common body part injured, as a result of unintentional physical injury [1]. Also, one can note the shortage of therapists and high costs for patient or healthcare insurance systems. Current development in robotics may offer a solution for this problem [2], allowing the creation of robotic devices to support the rehabilitation process, in a supervised or unsupervised way, in physiotherapy clinics or at home. In this context, we proposed RAPMES, a new intelligent, adaptive robotic system, which can provide the rehabilitation protocols, defined by a therapist, for the wrist and elbow of upper limb, considering the patient reactions and based on real-time feedback. RAPMES robotic system is designed on an ongoing research project, which implies several stages of development. In a first stage, we conducted a study involving therapists, the personnel and devices existent in a physiotherapy clinic. The role of this study was to determine the requirements for the robotic device, and to reveal the specific therapeutic needs of patients with rehabilitation indications at wrist and elbow level. On a second stage, we used a real-time video motion analysis system, to determine and understand specific functional movements frequently made with the dominant upper limb, by healthy persons. One of our research objectives is to include these movements as a part of RAPMES control algorithm, as they may offer a better rehabilitation of the upper limb, for specific moves. Next, we designed the robotic device, based on findings described above, and realized an experimental model of the robotic device.

via Kinematic analysis and control for upper limb robotic rehabilitation system – IEEE Conference Publication

[WEB SITE] Scientists develop combined therapy for stroke victim recovery

Scientists in Switzerland have demonstrated that combining a brain-computer interface (BCI) with functional electrical stimulation (FES) can help stroke victims recover greater use of their paralysed limbs – even years after the stroke.

 

 

Paralysis of an arm and/or leg is one of the most common results of a stroke. However, a team of scientists at the Defitech Foundation Chair in Brain-Machine Interface, in association with other members of EPFL’s Center for Neuroprosthetics, the Clinique Romande de Réadaptation in Sion, and the Geneva University Hospitals, have developed a technique aimed at enabling stroke victims to recover greater use of their paralysed limbs. The scientists’ pioneering approach utilises two existing therapies – a brain-computer interface (BCI) and functional electrical stimulation (FES).

Explaining the key to their approach, José del R. Millán, who holds the Defitech Chair at EPFL, said: “The key is to stimulate the nerves of the paralysed arm precisely when the stroke-affected part of the brain activates to move the limb, even if the patient can’t actually carry out the movement. That helps re-establish the link between the two nerve pathways where the signal comes in and goes out.”.

Combined therapy tested on stroke patients

Twenty-seven patients aged between 36 and 76 took part in the clinical trial. All had a similar lesion that resulted in moderate to severe arm paralysis following a stroke occurring at least ten months earlier. Half of the patients were treated with the scientists’ dual-therapy approach and reported clinically significant improvements. The other half were treated only with FES and served as a control group.

For the first group, the scientists used a BCI system to link the patients’ brains to computers by means of electrodes. This enabled them to pinpoint exactly where the electrical activity occurred in the brain tissue when the patients tried to reach out their hands. Each time the electrical activity was identified the system immediately stimulated the arm muscle controlling the corresponding wrist and finger movements. The patients in the second group also had their arm muscles stimulated, but at random times. This control group enabled the scientists to determine how much of the additional motor-function improvement could be attributed to the BCI system.

New technology could dramatically shorten diagnosis time of stroke patients…

 

The scientists noted a significant improvement in arm mobility among patients in the first group after just ten one-hour sessions. When the full round of treatment was completed, some of the first-group patients’ scores on the Fugl-Meyer Assessment – a test used to evaluate motor recovery among patients with post-stroke hemiplegia – were over twice as high as those of the second group.

“Patients who received the BCI treatment showed more activity in the neural tissue surrounding the affected area. Due to their plasticity, they could help make up for the functioning of the damaged tissue,” says Millán.

 

Electroencephalographies (EEGs) of the patients clearly showed an increase in the number of connections among the motor cortex regions of their damaged brain hemisphere, which corresponded with the increased ease in carrying out the associated movements. In addition, the enhanced motor function didn’t seem to diminish with time. Evaluated again 6-12 months later, the patients were found to have lost none of their recovered mobility.

The study results were published in Nature Communications.

via Scientists develop combined therapy for stroke victim recovery

[ARTICLE] Automatic Control of Wrist Rehabilitation Therapy (WRist-T) device for Post-Ischemic Stroke Patient – Full Text PDF

Abstract

Since a decade, the wrist rehabilitation services in Malaysia has been operated by the physiotherapist (PT). Throughout the rehabilitative procedure, PT commonly used a conventional method which later triggered some problems related to the effectiveness of the rehab services. Timeconsuming, long-waiting time, lack of human power and all those leading to exhaustion, both for the patient and the provider. Patients could not commit to the therapy session due to logistic and domestic problems. This problem can be greatly solved with rehabilitation robot, but the current product in the market is expensive and not affordable especially for lowincome earners family. In this paper, an automatic control of wrist rehabilitation therapy; called WRist-T device has been developed. There are based on three different modes of exercises that can be carried out by the device which is the flexion/extension, radial/ulnar deviation and pronation/supination. By using this device, the patient can easily receive physiotherapy session with minor supervision from the physiotherapist at the hospital or rehabilitation centre and also can be conducted at patient home.

Full Text: PDF

 

References

N. Bayona,“The role of task-specific training in rehabilitation therapies,”Topics in Stroke Rehabilitation, vol. 12, 2005,pp. 58–65.

R. Bonita, R. Beaglehole, “Recovery of motor function after stroke,”Stroke, 1988,pp. 19.

S. Cramer, J. Riley, “Neuroplasticity and brain repair after stroke,”Current Opinion in Neurology,vol. 21, 2008,pp. 76–82.

D.J. Reinkensmeyer, J. Emken, S. Cramer, “Robotics, motor learning, and neurologic recovery,”Annual Review of Biomedical Engineering, vol. 6, 2004, pp. 497-525.

M. Takaiwa, “Wrist rehabilitation training simulator for P.T. using pneumatic parallel manipulator,”IEEE International Conference on Advanced Intelligent Mechatronics (AIM), 2016, pp. 276-281.

H. Al-Fahaam, S. Davis, S. Nefti-Meziani, “Wrist Rehabilitation exoskeleton robot based on pneumatic soft actuators,”International Conference for Students of Applied Engineering (ICSAE), 2016, pp. 491-496.

D. Dauria, F. Persia, B. Siciliano,“Human-Computer Interaction in Healthcare: How to Support Patients during their Wrist Rehabilitation,”IEEE Tenth International Conference on Semantic Computing (ICSC), 2016, pp. 325-328.

W.M. Hsieh, Y.S. Hwang, S.C. Chen, S.Y. Tan,C.C. Chen, and Y.L. Chen, “Application of the Blobo Bluetooth ball in wrist rehabilitation training,”Journal of Physical Therapy Science, vol. 28, 2016, pp. 27- 32.

A. Hacıoğlu, O.F. Özdemir, A,K, Şahin, Y.S. Akgül, “Augmented reality based wrist rehabilitation system,”Signal Processing and Communication Application Conference (SIU), 2016. pp. 1869-1872.

Z.J. Lu, L.C.B. Wang, L.H. Duan, Q.Q. Lui, H.Q. Sun, Z.I. Chen, “Development of a robot MKW-II for hand and Wrist Rehabilitation Training,”The Annual IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, 2016, pp. 302-307.

 

via Automatic Control of Wrist Rehabilitation Therapy (WRist-T) device for Post-Ischemic Stroke Patient | Mohd Adib | Journal of Telecommunication, Electronic and Computer Engineering (JTEC)

[BOOK] New Vibratory Device for Wrist Rehabilitation – Innovation, Engineering and Entrepreneurship – Google Books

New Vibratory Device for Wrist Rehabilitation

H Puga – Innovation, Engineering and Entrepreneurship, 2018

Wrist injuries are very common in most of the population, specially bone fractures,
but also other pathologies such as tendinitis and neurological diseases. When the
wrist is injured, their flexion-extension and radial-ulnar deviation and pronation …

 

via Innovation, Engineering and Entrepreneurship – Google Books

[Conference paper] Kinematic Design of a Parallel Robot for Elbow and Wrist Rehabilitation|Abstract+References

Abstract

This paper presents the kinematics of modular a parallel robot for post-stroke rehabilitation of elbow and wrist. The targeted motions for rehabilitation are: elbow flexion, pronation/supination, flexion/extension and adduction/abduction (radial/ulnar deviation) of the wrist. The kinematic structure of the robotic system is presented starting from general considerations concerning the rehabilitation protocol of the upper limb. Its kinematics is developed and simulation results are presented for a proposed training exercise.

References

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   Allington J, Spencer SJ, Klein J, Buell M, Reinkensmeyer DJ, Bobrow J (2011) Supinator extender (SUE): a pneumatically actuated robot for forearm/wrist rehabilitation after stroke. In: Proceedings of the Conference on IEEE Engineering in Medicine and Biology Society, pp 1579–1582Google Scholar
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   Carbone G et al (2017) A study of feasibility for a limb exercising device. Advances in Italian mechanism science. In: Proceedings of the first international conference of the IFToMM Italy, pp 11–21Google Scholar
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   Ceccarelli M (2004) Fundamentals of mechanics of robotic manipulation. SpringerCrossRefGoogle Scholar
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   Chan DYI, Chan CCH, Au DKS (2006) Motor relearning programme for stroke patients: a randomized controlled trial. Clin Rehabil 20(3):191–200CrossRefGoogle Scholar
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   Chen Y, Li G, Zhu Y, Zhao J, Cai H (2014) Design of a 6-DOF upper limb rehabilitation exoskeleton with parallel actuated joints. Bio-Med Mater Eng 24:2527–2535Google Scholar
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   Colizzi L, Lidonnici A, Pignolo P (2012) Upper limb rehabilitation after stroke: ARAMIS a “robomechatronic” innovative approach and prototype. In: Proceedings of the 4th IEEE RAS & EMBS international conference on biomedical robotics and biomechatronics (BioRob), pp 1410–1414Google Scholar
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   Dorobantu M et al (2012) Profile of the Romanian hypertensive patient data from SEPHAR II study. Rom J Intern Med 50(4):285–296Google Scholar
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   Duret C, Courtial O, Grosmaire A, Hutin E (2015) Use of a robotic device for the rehabilitation severe upper limb paresis in subacute stroke: exploration of patient/robot interaction and the motor recovery process. BioMed Res Int, Article ID 482389CrossRefGoogle Scholar
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    Ho NS et al (2011) An EMG-driven exoskeleton hand robotic training device on chronic stroke subjects: task training system for stroke rehabilitation. In: Proceedings of IEEE International Conference on Rehabilitation RoboticsGoogle Scholar
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    Major KA, Major ZZ, Carbone G, Pîslă A, Vaida C, Gherman B, Pîslă D (2016) Ranges of motion as basis for robot-assisted post-stroke rehabilitation. Int J Bioflux Soc Hum Vet Med 8(4):192–196Google Scholar
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    Mihelj M, Nef T, Riener R (2007) Armin II—7 dof rehabilitation robot: mechanics and kinematics. In Proceedings of 2007 IEEE international conference on robotics and automation, pp 4120–4125Google Scholar
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    Plitea N et al (2017) Parallel robotic system for elbow and wrist rehabilitation. Patent pendingGoogle Scholar
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    Tarnita D, Geonea I, Petcu A, Tarnita DN (2016) Experimental characterization of human walking on stairs applied to humanoid dynamics. In: Advances in robot design and intelligent control. Springer, pp 293–301Google Scholar
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    Veerbeek M et al (2014) What is the evidence for physical therapy poststroke? A systematic review and meta-analysis. PLoS ONE 9(2)CrossRefGoogle Scholar

via Kinematic Design of a Parallel Robot for Elbow and Wrist Rehabilitation | SpringerLink

[Abstract] Motor skill changes and neurophysiologic adaptation to recovery-oriented virtual rehabilitation of hand function in a person with subacute stroke: a case study.

Abstract

PURPOSE:

The complexity of upper extremity (UE) behavior requires recovery of near normal neuromuscular function to minimize residual disability following a stroke. This requirement places a premium on spontaneous recovery and neuroplastic adaptation to rehabilitation by the lesioned hemisphere. Motor skill learning is frequently cited as a requirement for neuroplasticity. Studies examining the links between training, motor learning, neuroplasticity, and improvements in hand motor function are indicated.

METHODS:

This case study describes a patient with slow recovering hand and finger movement (Total Upper Extremity Fugl-Meyer examination score = 25/66, Wrist and Hand items = 2/24 on poststroke day 37) following a stroke. The patient received an intensive eight-session intervention utilizing simulated activities that focused on the recovery of finger extension, finger individuation, and pinch-grasp force modulation.

RESULTS:

Over the eight sessions, the patient demonstrated improvements on untrained transfer tasks, which suggest that motor learning had occurred, as well a dramatic increase in hand function and corresponding expansion of the cortical motor map area representing several key muscles of the paretic hand. Recovery of hand function and motor map expansion continued after discharge through the three-month retention testing.

CONCLUSION:

This case study describes a neuroplasticity based intervention for UE hemiparesis and a model for examining the relationship between training, motor skill acquisition, neuroplasticity, and motor function changes. Implications for rehabilitation Intensive hand and finger rehabilitation activities can be added to an in-patient rehabilitation program for persons with subacute stroke. Targeted training of the thumb may have an impact on activity level function in persons with upper extremity hemiparesis. Untrained transfer tasks can be utilized to confirm that training tasks have elicited motor learning. Changes in cortical motor maps can be used to document changes in brain function which can be used to evaluate changes in motor behavior persons with subacute stroke.

 

via Motor skill changes and neurophysiologic adaptation to recovery-oriented virtual rehabilitation of hand function in a person with subacute stroke: … – PubMed – NCBI

[Abstract] Biomechatronics design of a robotic arm for rehabilitation – IEEE Conference Publication

Abstract

Rehabilitation is an important process to restore muscle strength and joint’s range of motion. This paper proposes a biomechatronic design of a robotic arm that is able to mimic the natural movement of the human shoulder, elbow and wrist joint. In a preliminary experiment, a subject was asked to perform four different arm movements using the developed robotic arm for a period of two weeks. The experimental results were recorded and can be plotted into graphical results using Matlab. Based on the results, the robotic arm shows encouraging effect by increasing the performance of rehabilitation process. This is proven when the result in degree value are accurate when being compared with the flexion of both shoulder and elbow joints. This project can give advantages on research if the input parameter needed in the flexion of elbow and wrist.

I. Introduction

According to the United Nations (UN), by 2030 the number of people over 60 years will increase by 56 per cent, from 901 million to more than 1.4 billion worldwide [1]. As the number of older persons is expected to grow, it is imperative that government and private health care providers prepare adequate and modern facilities that can provide quality services for the needs of older persons especially in rehabilitation centers. Implementation of robotic technology in rehabilitation process is a modern method and definitely can contribute in this policy and capable in promoting early recovery and motor learning [2]. Furthermore, systematic application of robotic technology can produce significant clinical results in motor recovery of post-traumatic central nervous system injury by assisting in physical exercise based on voluntary movement in rehabilitation [3].

via Biomechatronics design of a robotic arm for rehabilitation – IEEE Conference Publication

[Abstract] Effect of task specific training and wrist-fingers extension splint on hand joints range of motion and function after stroke

Abstract

BACKGROUND:Most stroke patients experience hand impairments that can result in persistent limitations in daily activities.

OBJECTIVE:This study aimed at estimating the immediate and retention effects of task specific training and wrist/fingers extension splint on hand joints range of motion and function after stroke.

METHODS:Twenty-four right handed patients with first ever stroke represented the sample of the study. The participants were randomly assigned into two equal groups. The study group received task specific exercises five times a week for an hour concurrently with wrist/fingers extension splint which was used two hours for each three hours (day and night) excluding exercises and sleeping hours for 16 weeks. The control group received traditional passive stretch and range of motion exercises. Manual dexterity and upper limb function were assessed by nine holes peg test and Fugl-Meyer upper extremity and hand. Goniometry was used for measuring wrist, metacarpophalangeal, thumb carpometacarpal joints active range of motion.

RESULTS:Significant improvements were observed in nine holes peg test, Fugl-Meyer upper extremity and hand scores and ranges of motion at post-intervention and follow-up compared to pre-intervention at P≤0.05.

CONCLUSIONS:The results of this study provide an evidence that task specific training and wrist/fingers extension splint are effective in improving fingers dexterity, upper extremity function and wrist/hand range of motion.

DOI: 10.3233/NRE-162128

Journal: NeuroRehabilitation, vol. 41, no. 2, pp. 437-444, 2017

Published: 14 October 2017

 

via Effect of task specific training and wrist-fingers extension splint on hand joints range of motion and function after stroke – IOS Press