Design and control of an active 1-DoF mechanism for knee rehabilitation

Naghavi, Nader; Mahjoob, M. J.

doi:10.3109/17483107.2015.1027299

Cited by 8 publications

(6 citation statements)

References 13 publications

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“…In ref. [5], a similar work is introduced. A PID controller is used in controlling 1-DOF mechanism for knee rehabilitation, and the results of that research show an error more than 2 • in the passive and the active modes.…”

Section: Resultsmentioning

confidence: 99%

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RBF neural network-based admittance PD control for knee rehabilitation robot

et al. 2022

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Early-stage rehabilitation therapy for post-stroke patients consists of intensive and accurate training sessions. During these sessions, the therapist moves the patient’s joint within its range of motion repetitively. Patients, at this stage, often cannot control their muscles, and neurological disorders may occur and lead to undesirable movements. Thus, the therapist should train the joint gently to handle any sudden involuntary movements. Otherwise, the joint may undergo excessive torques, which may injure it. In this paper, we address this case and develop a clinical rehabilitation robotic system for training the knee joint taking into account the occurrence of these undesirable movements. The developed system has an innovative mechanism to measure interaction torques exerted by involuntary movements. Then, we introduce a new control approach consisting of an admittance controller and a proportional-derivative controller augmented by a radial basis function (PD-RBF) neural network. The PD-RBF guides the robot joint along a predefined trajectory, while the admittance part tracks any sudden interaction torques and updates the predefined trajectory accordingly. Thus, the robot trains the knee joint and once an undesirable movement occurs the robot gets along with this movement smoothly, then it gets back to the predefined trajectory. To validate the performance of the proposed admittance PD-RBF controller, we consider two controllers, an admittance adaptive sliding mode control and an admittance conventional PD one. Then, a compatarive study is conducted on these controllers via real-world experiments. The obtained results verify the efficiency of the admittance PD-RBF and prove its superiority over the other aforementioned controllers.

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Section: Resultsmentioning

confidence: 99%

“…In ref. [5], Naghavi et al implement a PID control loop to perform trajectory tracking control for a knee rehabilitation robot. A neuromuscular electrical stimulation device is controlled by an adaptive PID controller with an online tuning parameter to perform exercises for the upper limb [6,7].…”

Section: Introductionmentioning

confidence: 99%

RBF neural network-based admittance PD control for knee rehabilitation robot

et al. 2022

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“…In the meantime, a stationary-based robot for knee rehabilitation was previously designed and fabricated in our labora- tory [20]. This robot has one DOF for knee F/E (Fig.…”

Section: B the Proposed Robotmentioning

confidence: 99%

“…Many stationary-based robots rehabilitate the hip, knee or ankle separately. For instance, hip and knee joints are mainly addressed by robots with one active Degree of Freedom (DOF) in the sagittal plane to allow Flexion/Extension (F/E) motion [18]- [20]. On the other hand, rehab robots focusing on ankle joint usually provide more than one DOF to account for the complex kinematics of the ankle-foot complex [21]- [25].…”

Section: Introductionmentioning

confidence: 99%

A New 4-DOF Robot for Rehabilitation of Knee and Ankle-Foot Complex: Simulation and Experiment

Alipour¹,

Mahjoob

Fakhari³

et al. 2022

Journal of Robotics and Control

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Stationary robotic trainers are lower limb rehab robots which often incorporate an exoskeleton attached to a stationary base. The aim is to recover range of motion, increase muscles strength and reduce joint stiffness. The issue observed in the stationery trainers which involve knee and ankle-foot complex joints simultaneously is that they restrict the natural motion of ankle-foot in rehab trainings due to the insufficient Degrees of Freedom (DOFs) of these trainers. This restriction makes the joints deviate from their natural motion patterns, exerting potentially harmful forces and strain the joints. In this work, we propose a new stationary knee-ankle-foot rehab robot with all necessary DOFs including knee flexion/extension in addition to ankle plantarflexion/dorsiflexion, ankle-foot abduction-adduction and foot supination/pronation. Axes of motions are determined based on the kinematics of the joints. A typical rehab training exercise has been considered to evaluate the system performance. The chosen training (i.e., passive assistance) was first implemented in simulation to synthesize the control loop and to extract the parameters required for selecting the robot’s components. The robot was then fabricated and tested on a healthy subject. Results showed that all natural motions of the ankle-foot complex were generated during the training. Therefore, the proposed system fulfils the desired aim properly, so that it can be utilized in the design of rehab robots.

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“…Considering the cost of these multi-DOF rehab devices is usually quite expensive, designers also proposed a series of 1-DOF rehab mechanisms for specified tasks. Naghavi and Mahjoob [8] proposed an active 1-DOF mechanism for knee rehabilitation. Franci et al [9] designed a parallel mechanism for modeling passive motion at the human tibiotalar joint.…”

Section: Introductionmentioning

confidence: 99%

Design of a Single-Degree-of-Freedom Immersive Rehabilitation Device for Clustered Upper-Limb Motion

Zhao

Zhang

Guan

et al. 2021

Journal of Mechanisms and Robotics

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Mechanical devices such as robots are widely adopted for limb rehabilitation. Due to the variety of human body parameters, the rehabilitation motion for different patients usually has its individual pattern, thus we adopt clustering-based machine learning technique to find a limited number of motion patterns for upper-limb rehabilitation, so that they could represent the large amount of those from people who have various body parameters. Using the regression motion of the clustering result as the target, in this paper we seek to apply kinematic-mapping-based motion synthesis framework to design a one-DOF mechanism such that it could lead the patients' upper limb through the target motion. Also, considering rehab training generally involves a large amount of repetition in daily basis, this paper has developed a rehab system with Unity3D based on Virtual Reality (VR). The proposed device and system could provide an immersive experience to the users, as well as the rehab motion data to the administrative staff for evaluation of users' status. The construction of the integrated system as well as the experimental trial of the prototype are presented in the end of this paper.

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Design and control of an active 1-DoF mechanism for knee rehabilitation

Cited by 8 publications

References 13 publications

RBF neural network-based admittance PD control for knee rehabilitation robot

RBF neural network-based admittance PD control for knee rehabilitation robot

A New 4-DOF Robot for Rehabilitation of Knee and Ankle-Foot Complex: Simulation and Experiment

Design of a Single-Degree-of-Freedom Immersive Rehabilitation Device for Clustered Upper-Limb Motion

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