Hybrid impedance control of a robot manipulator for wrist and forearm rehabilitation: Performance analysis and clinical results

Akdoğan, Erhan; Aktan, Mehmet Emin; Koru, Ahmet Taha; Arslan, M. Selçuk; Atlıhan, Murat; Kuran, Banu

doi:10.1016/j.mechatronics.2017.12.001

Cited by 74 publications

(39 citation statements)

References 17 publications

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“…In [10] an algorithm was proposed for planning the tool location together with a compliance force control. In [14] a hybrid impedance control of a robot manipulator is developed for wrist and forearm rehabilitation. In [15], a methodology based on sensor-less force control technique and the quarry matrix was proposed to control the x and y trajectories of the tool pose and the polishing force in the z-direction in a parallel machine.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Sliding Mode Control for Robotic Surface Treatment Using Force Feedback

et al. 2018

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This work presents a hybrid position-force control of robots in order to apply surface treatments such as polishing, grinding, finishing, deburring, etc. The robot force control is designed using sliding mode concepts to benefit from robustness. In particular, the sliding mode force task is defined using equality constraints to attain the desired tool pressure on the surface, as well as to keep the tool orientation perpendicular to the surface. In order to deal with sudden changes in material stiffness, which are ultimately transferred to the polishing tool and can produce instability and compromise polishing performance, several adaptive switching gain laws are considered and compared. Moreover, a lower priority tracking controller is defined to follow the desired reference trajectory on the surface being polished. Hence, deviations from the reference trajectory are allowed if such deviations are required to satisfy the constraints mentioned above. Finally, a third-level task is also considered for the case of redundant robots in order to use the remaining degrees of freedom to keep the manipulator close to the home configuration with safety in mind. The main advantages of the method are increased robustness and low computational cost. The applicability and effectiveness of the proposed approach is substantiated by experimental results using a redundant 7R manipulator: the Rethink Robotics Sawyer collaborative robot.

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Section: Introductionmentioning

confidence: 99%

Adaptive Sliding Mode Control for Robotic Surface Treatment Using Force Feedback

et al. 2018

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“…The use of robots in rehabilitation is increasing by the day due to a number of particular qualities, such as their ability to perform repetitive movements with precise accuracy, to make objective measurements and evaluations, and to make positive contributions in terms of cost and time and making the treatment process easily and remotely accessible [1]. Clinical studies have demonstrated the contribution of robots to the rehabilitation processes [2].…”

Section: Introductionmentioning

confidence: 99%

Development of an intelligent controller for robot-aided assessment and treatment guidance in physical medicine and rehabilitation

Aktan¹,

Akdoğan²

2021

Turk J Elec Eng & Comp Sci

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In this study, an intelligent controller was developed for a rehabilitation robot called DIAGNOBOT, which can be used for assessment and treatment in the rehabilitation of wrist and forearm. The controller has a decision support system structure strengthened with conventional statistical methods and databases. The controller uses the patient's biomechanical parameters to make an assessment and proposes a treatment in line with this. In accordance with the recommended treatment, it produces the control parameters, the torque and position information for the control of the rehabilitation robot. The system's ability to assessment and treatment was tested with voluntary patients. Through these test studies, the treatments recommended by the developed intelligent controller have been proven to have a very high rate of accuracy.

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“…They have been demonstrated to provide repeated and progressive rehabilitation training required for the effective recovery of patients with limb disabilities. To meet the requirement of assistance at different rehabilitation stages, active or passive rehabilitation robots of multiple degrees-of-freedom (DoFs) have been developed to assist the motion of human upper limbs [1][2][3][4][5][6][7][8][9][10][11][12][13] or lower limbs [14][15][16][17][18]. Compared with end-effector type robots [2,[11][12][13]18], exoskeleton type robots [1,[3][4][5][6][7][8][9][10][14][15][16][17] can provide direct assistance and recovery evaluation at each human joint.…”

Section: Introductionmentioning

confidence: 99%

“…Due to the limited space around the limb, adding an external force sensor would be inconvenient. To reduce the complexity of rehabilitation, force estimation and control methods without using external force sensors have been adopted [6][7][8][9]. To more accurately control the interaction force, series elastic actuators (SEAs) have been used [1-3, 13-14, 20].…”

Section: Introductionmentioning

confidence: 99%

A Spatial-Motion Assist-as-Needed Controller for the Passive, Active, and Resistive Robot-Aided Rehabilitation of the Wrist

Lin

Lai

et al. 2020

IEEE Access

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Demand for robot-assisted therapy has increased at every stage of the neurorehabilitation recovery. This paper presents a controller that is suitable for the assist-as-needed (AAN) training of the wrist when performing the spatial motion. A compact wrist exoskeleton robot is presented to realize the AAN controller. This wrist robot includes series elastic actuators with high torque-to-weight ratios to provide accurate force control required for the AAN controller. In addition to assist-as-needed rehabilitation, the parameters of the AAN controller can be adjusted to deliver passive, active, or resistive rehabilitation. Experimental results demonstrate that the proposed AAN controller can provide the total solution to cover each stage of wrist spatial-motion rehabilitation.

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Hybrid impedance control of a robot manipulator for wrist and forearm rehabilitation: Performance analysis and clinical results

Cited by 74 publications

References 17 publications

Adaptive Sliding Mode Control for Robotic Surface Treatment Using Force Feedback

Adaptive Sliding Mode Control for Robotic Surface Treatment Using Force Feedback

Development of an intelligent controller for robot-aided assessment and treatment guidance in physical medicine and rehabilitation

A Spatial-Motion Assist-as-Needed Controller for the Passive, Active, and Resistive Robot-Aided Rehabilitation of the Wrist

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