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Several robotic devices are able to support more than one joint at the same time, to assist both shoulder and elbow, such as MIT-Manus (Massachusetts Institute of Technology Manus), MIME (Mirror Image Movement Enabler) (Lum, et al., 2006), Assisted Rehabilitation and Measurement Guide (ARM) guide, and GENTLEs (Loureiro, Amirabdollahian, Topping, Driessen, & Harwin, 2003). The robotic therapy target for these robots is the same, active assist exercise. Where active refers to the patient's ability to be active and engaged. The assist refers to the therapist assistance provided to patients as needed (Curtin , Molineux , & Supky- Mellson, 2009). Moreover, these robots are easy to adjust with the human upper limb length, which make it simpler and easier to manufacture. However, determining the movement of the upper limb is not easy with only one interface (patients hand). End-effector based robots cannot control the torque at particular joint, in addition, the range of motion (ROM) is limited. as a result, a limited set of rehabilitation exercises can be generated by these rehabilitation robotics. MIT-Manus as shown in Figure 3.3 allows the movement only in one plane (Krebs, Hogan, Aisen, & Volpe, 1998), moreover it utlilises massed practice and force feedback method to provide therapy that targets reaching motions towards an endpoint. The force feedback provided by the device consists of forces applied in the same direction as the reaching motion to assist muscle in the task completion. Studies conducted to evaluate the effectiveness of robot-assisted therapy with the MIT-Manus revealed that this system can improve the clinical outcomes for repetitive, goal directed therapy (Krebs, et al., 2004), as well as improve the motor and functional recovery gains in subject with actuate and chronic hemiparesis. However, MIME and ARM guide, as shown in Figure 3.3, are both limited to linear movement, because the forearm is usually followed a straight-line trajectory, and both are designed for upper limb rehabiliation through massed practice methods (Lum, Reinkensmeyer, Mahoney, Rymer , & Burgar, 2002). On the one hand, Studies conducted by Kahn et al. regarding ARM guide devices did not reveal significant differnces between results obtained with robotic assistive and resistive forces employed by this device and the free, unassisted methods used in conventional therapy for the training of reaching motions. On the other hand, MIME was the first robotic rehabilitaion system that explored bilateral training for upper limb stroke rehabilitaion, focusing specifically on the practice of reaching motion. The device is coupled to the user’s unimpaired arm, allowing three dimensional motions that are assited or resisted through force feedback (Lum, et al., 2006). Recently, rehabilitation robotics research has shifted to exoskeleton devices. Exoskeleton robots have

the potential to meet the growing of patience demands that traditional therapy is struggling to provide. Since it provides the patient with intensive rehabilitation systematically for a longer duration (Huang & Krakauer, 2009). The robotic devices are able to treat the patient without the presence of the therapist, and with more frequent therapy sessions, thus will result in a reduction of the cost of the rehabilitation process. Moreover, it can be attached at several locations in the upper limb. There are many of commercial robotic devices that has been used for the upper limb rehabilitation.

Figure 3.3. a) MIT-Manus; (b) MIME; (c) GENTLE/s.

One of the most popular devices is Armeo (ARMin) as shown in Figure 3.4/a below, which includes 7 DOF, active and passive; the active robot is called ArmeoPower (Nef, Guidali, Klamroth-Marganska, & Riener, 2009), and the passive is named ArmeoSpring as shown in Figure 3.4-b/c, respectively. (Sanchez, et al., 2004). Both of them used to assist shoulder, elbow, wrist, and fingers (whole upper limb) and the input signal is the joint angles and grasp force. InteliArm robot is used also to assist the whole upper limb with joint angles and torques input signals, the degree of freedom is fluctuates between 8-10 DOF (Ren, Park, & Zhang, 2009). The MGA robot assists shoulder and elbow with five degrees of freedom (5 DOF), the input signal joint torque and the actuator is electric motors (Carignan , Tang, & Roderick , 2009).

Robotic devices used for upper limb rehabilitation differ from each other by several factors such as: the DOF, joint movements they support, main control inputs, mechanical design and

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structure, and type of assistance. Kiguchi (Kiguchi, Esaki, Tsuruta, Watanabe, & Fukuda T., 2003), MARIONET-Suzler (Suzler, Peshkin, & Patton, 2007), Rosen (Rosen , Brand, Fuchs, & Arcan, 2001), and Song (Song, Tong, Hu, & Li, 2008), all are robotic devices that assist elbow movements. However, some of them are classified to end-effector based such as MARIONET-Suzler and Song, and to exoskeleton-based as in Rosen and Kiguchi. The inputs signal vary from one device to another, in the mentioned devices above the input signal is sEMG except in MARIONET-Suzler as it is the joint angle. In addition, they all share the same degree of freedom: 1DOF. Kiguchi is utilised to support the shoulder joint with 2DOF (Kiguchi, Iwami, Makoto, & Watanabe, 2003).

REHAROB is an industrial rehabilitation robot that is used for the upper limb motion therapy for disabled, in other words, it is used for physical therapy. It was developed to support the upper limb joints, shoulder and elbow. REHAROB as shown in Figure 3.4/c consist of two arms supporting 6 DOF in each, in total 12 DOF. The input signal for this device is the end point torque, where the patients force causes movement of the device when it is in the passive state. REHAROB can also be used in the assessment, as it quantifies the patient's range of motion (ROM) (Fazekas, Hovath, Troznai, & Toth, 2007).

Figure 3.4. (a) ARMin; (b) Armeo Spring; (c) REHAROB.

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