|Year : 2015 | Volume
| Issue : 2 | Page : 54-57
A haptic device for wrist and elbow rehabilitation
Jun Jiang1, Le Xie2, Guojie Li3
1 Shanghai Engineering Center for Microsatellites, Shanghai Jiao Tong University, Shanghai 200030, China
2 National Digital Manufacturing Technology Center, Shanghai Jiao Tong University, Shanghai 200030, China
3 Shanghai Institute of Space Propulsion, Shanghai 200030, China
|Date of Web Publication||25-Jan-2016|
National Digital Manufacturing Technology Center, Shanghai Jiao Tong University, Shanghai 200030
Source of Support: None, Conflict of Interest: None
Interest in the devices for rehabilitation applications has been increasing. And the devices before have proved that they might assist in and quantify the rehabilitation for upper limb disability caused by stroke. This paper is to introduce rehabilitation application of a haptic device based on virtual reality technology, which is compact, portable, and modular. The focus here is a device with force feedback designed to provide five degrees of freedom, which are rotation, opposition, translation, pitch, and yaw. With five degrees of freedom above, the device can help individuals with arm weakness do their exercise and make patients achieve favorable rehabilitation efficacy during their upper limb rehabilitation.
Keywords: Rehabilitation, upper limbs, haptic device, degree of freedom
|How to cite this article:|
Jiang J, Xie L, Li G. A haptic device for wrist and elbow rehabilitation. Digit Med 2015;1:54-7
| Introduction|| |
Nowadays, there are about 250 million stroke patients all over the world and the obstacle of movement function including upper limb disability exists among 3/4 of the stroke patients.  Every year, the total cost for rehabilitation and lost revenue reaches 20 billion in China. There has been a trend toward more moderately affected survivors, which has increased the demand for stroke rehabilitation in an era of health care cost containment. 
Interest in the rehabilitation applications of devices has been increasing. Besides the cost-effective aspect, devices introduce a higher accuracy and repeatability in rehabilitations.  In the last 2 decades, various robots have been proposed that specifically target different areas of rehabilitation, ranging from upper to lower limbs, and from proximal to distal joints.  MIT-MANUS, developed at MIT, provides a platform for wrist rehabilitation.  From then on, several additional robots for upper limb rehabilitation have been provided, such as Rice Wrist,  which was designed by Rice University. All the devices have proved that they might assist in and quantify the rehabilitation for body disability caused by stroke. 
The ability to interact mechanically with virtual objects through incorporation of force feedback allows users to manipulate objects in the simulated or remote environment with ease when compared with a purely visual display.  Force feedback information can be used in robotic devices, exoskeleton data glove exoskeleton.  Alamri et al.  developed a haptic interface which utilized the Cyber Grasp glove to perform VR activities. More and more devices which can be applied professionally to rehabilitation have been developed, such as the devices that use a motor to constrict a band worn around the fingertip, , shape memory alloys that change shape when an electric current is passed through the alloy, thus constricting the upper limbs and generating pressure. 
A haptic device for wrist and elbow rehabilitation has been developed by our group, which provides five degrees of freedom, which are rotation, opposition, translation, pitch and yaw.
Rehabilititation training of the device
Overview of the device
The objective of the study is to design a compact, portable, and modular mechanism for wrist and elbow rehabilitation, it is very important that the device should be small in size and used conveniently. In order to achieve favorable rehabilitation efficacy, according to kinesiology, the motion model of the device had been studied, which is shown in [Figure 1]. Thinking about the patients' particular case, we set five degrees of freedom (DOFs) to plan the patients' training route. The five DOFs are rotation, cutting, translation, pitch, and yaw. The patients handle cutting to do their rehabilitation by the movement of their wrist and elbow. Deviated from the other devices for rehabilitation, the device has a unique movement which is cutting, because cutting could give patients some fingers' movement to achieve real and coordinative feeling, while their wrist and elbow are doing rehabilitation. It is of high importance that the device should be easy for the patients to use. Generally speaking, the space with a radius of the length of their forearms in front of their chest is just their work space, shown in [Figure 2], while patients do their wrist and elbow rehabilitation. In this way, we get the range of five kinds of motion above after analysis, and the numerical value of every motion is as follows: the range of rotation is ±180°, the range of cutting is 40°, the range of translation is 260 mm, which approximates the length of human's forearm, the range of pitch is ±90°, and the range of yaw is ±180°. According to the analysis result, we can show that the work space takes a hemispherical shape when cutting is neglected. To illustrate the proposed motion model with mechanical movement, the five DOFs are configurable for serial mechanism, which is shown in [Figure 3]. In the configuration, it is easy to get that determining the work space does not involve cutting, in other words, it is unnecessary to calculate cutting when we calculate the motion equations of the device.
Rehabilitation action follows 5 DOFs of the device
With the range of every DOFs and the posture of patients, individuals with arm weakness could do many actions in every DOF. Some of these actions are shown in [Figure 4], [Figure 5], [Figure 6], [Figure 7] and [Figure 8].
When patients do exercise in translation, which is shown in [Figure 4], they can train their shoulders and elbows, and make their shoulders and elbows flex or extend. When patients do exercise in rotation, which is shown in [Figure 5], they can make their shoulders and elbows rotate, and then drive their forearms supinate or pronate. When patients do exercise in yaw, which is shown in [Figure 6], they can train their shoulders and wrists, make their shoulders flex, extend, adduct and abduct, and meanwhile, make wrists adduct and abduct. When patients do exercise in pitch, which is shown in [Figure 7], they can make shoulders flex or extend solely. When patients do exercise in opposition, which is shown in [Figure 8], they can achieve opposition training of hands.
Operation modes of rehabilitation
According to motion model of the device, we can set four modes, which are active mode, passive mode, power-assist mode, and hindering mode. When patients are in active mode, the motors do not run all the time, except for their force feedback in virtual reality environment which will be introduced below, and at this time, patients need to exercise by themselves. In contrast, it is unnecessary for patients to exert their own force at all in the passive mode; the device can drive patients to exercise their upper limb disability by mechanical movement. The power-assisted mode is an assistive mode which can help individuals with arm weakness exercise their function; meanwhile, patients should also exert their own force. Just as the name implies, when patients do their rehabilitation during hindering mode, the device may discourage patients' movement by mechanical movement. Obviously, the difference among four modes of the device is whether the motors run, so we can control the motors' running to switch the modes conveniently. With four modes above, the device can be almost used in every stage of upper limb rehabilitation.
Stroke rehabilitation is a restorative process that seeks to hasten and manage recovery by treating the disability, largely through physical therapy.  This paper introduces rehabilitation application of a 5 DOF device for patients with upper limb disability. Obviously, for patients, with the device owning more DOF, they should get more favorable rehabilitation efficacy. And also, with the virtual reality technology, the patients will be more active, interested, and comfortable in making rehabilitation. Therefore, our future work will be to introduce virtual reality technology into the application of the device. We believe that future improved devices using virtual reality technology will be more useful in rehabilitation.
| Acknowledgment|| |
The work described in this paper was supported by National High Technology Research and Development Program of China (No. 2015AA04320, 2006AA01Z310, 2009AA01Z313). National Natural Science Foundation of China (No. 61190124, 61190120). The project of science and technology commission of Shanghai municipality (No. 14441900800, 14DZ1941100, 14DZ1941103, 13DZ0511000). National Key Technology Support Program (No.2009BAI71B06). National Natural Science Foundation of China (No.61311140171, 60873131). Project of SJTU Medical an Engineering Cross Fund (YJ2013ZD03, YG2012MS54).
| References|| |
Steven KC, Hermano IK. Wrist rehabilitation following stroke: Initial clinical results. ICORR. USA; 2005.
Burgar CG, Lum PS, Shor PC, Machiel Van der Loos HF. Development of robots for rehabilitation therapy: The Palo Alto VA/Stanford experience. J Rehabil Res Dev 2000;37:663-73.
Jakob O, Imre C. Haptic robot for arm and wrist rehabilitation. IFMBE Proceedings 25/IX, WC; 2009. p. 20-3.
Akshay M, Latt WT, Tan HG. Design and implementation of a mechatronic device for wrist and elbow rehabilitation. ICREAT. Singapore; 2007.
Abhishek G, Marcia K, Malley O. Design, Control and performance of Rice Wrist: A force feedback wrist exoskeleton for rehabilitation and training. Inter J Robot Res 2008;27:233-51.
Krebs HI, Volpe BT, Williams D, Celestino J, Charles SK, Lynch D, et al
. Robot-aided neurorehabilitation: A robot for wrist rehabilitation. IEEE Trans Neural Syst Rehabil Eng 2007;15:327-35.
Takahashi CD, Der-Yeghiaian L, Le V, Motiwala RR, Cramer SC. Robot-based hand motor therapy after stroke. Brain 2008;131:425-37.
Domenico C, Diho A. Intrinsic constraints of neural origin: Assessment and application to rehabilitation robotics. IEEE Trans Robot 2009;25:492-501.
McLaughlin M, Rizzo A, Jung Y, Peng W, Yeh SG, Zhu W. Haptics enhanced virtual environments for stroke rehabilitation. IPSI Conference: Cambridge; 2005. p. 2-5.
Alamri A, Eid M, Iglesias R, Shirmohammadi S, El Saddik A. Haptic virtual rehabilitation exercises for post-stroke diagnosis. IEEE Trans Instrum Meas 2007;57:1876-84.
Merrett GV, Metcalf CD, Zheng D, Cunningham S, Barrow S, Demain SH. Design and qualitative evaluation of tactile devices for stroke rehabilitation. IET Assisted Living Conference. London; 2011. p. 1-6.
Minamizawa K, Fukamachi S, Kawakami N, Tachi S. Interactive representation of virtual object in hand-held box by finger-worn haptic display. Haptic interfaces for virtual environment and teleoperator systems, 13-14; 2008. p. 367-8.
Scheibe R, Moehring M, Froehlich B. Tactile feedback at the finger tips for improved direct interaction in immersive environments. IEEE Symposium on 3D User Interfaces; Charlotte, 2011. p. 125-32.
Alan S, Marcia K. Performance enhancement of a haptic arm exoskeleton. Internation symposium on haptic interfaces for virtual environment and teleoperator systems, Virginia; 2006.
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7], [Figure 8]