Intelligent bimanual rehabilitation robot with fuzzy logic based adaptive assistance

Harischandra, P. A. Diluka; Abeykoon, A. M. Harsha S.

doi:10.1007/s41315-019-00080-9

Cited by 9 publications

(6 citation statements)

References 23 publications

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Section: Discussionmentioning

confidence: 99%

“…To increase patients' engagement, assist-as-needed (AAN) algorithms are proposed to achieve better bilateral upper limb training effectiveness [29,30]. Harischandra and Abeykoon [29] proposed a novel impedance controlled bimanual robot with fuzzy logic based adaptive assistance. The AAN controller was designed using a simple proportional controller with a fuzzy regulator for gain scheduling, which can provide assistance torque based on patient's ability to coordinating his/her arms.…”

Section: Discussionmentioning

confidence: 99%

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A robot-assisted bilateral upper limb training strategy with subject-specific workspace: A pilot study

Miao

Zhang

McDaid

et al. 2020

Robotics and Autonomous Systems

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This paper proposes a new robot-assisted bilateral upper limb training strategy, focusing on the bilateral coordination of users' upper limbs. The strategy is implemented and evaluated on a bilateral upper limb rehabilitation device (BULReD) that is an Hbot mechanism actuated by two Maxon DC motors. The control system consists of a position controller, an admittance controller and an adaptive algorithm, where the BULReD stiffness is modified session by session based on training performance. This strategy is also integrated with subject-specific workspace for enhanced training safety. Experiments were carried out with five subjects through active reaching tasks. Results indicate that the proposed training strategy requires significant coordination of bilateral upper limbs for task completion, and is able to tune control parameters to an appropriate difficulty level based on participants' training performance. Future work will focus on its clinical evaluation on patients with upper limb disabilities.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

A robot-assisted bilateral upper limb training strategy with subject-specific workspace: A pilot study

Miao

Zhang

McDaid

et al. 2020

Robotics and Autonomous Systems

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“…Additionally, a fuzzy-impedance control law is developed to estimate the human-robot interaction force in [51]. A robotic fuzzy-based adaptive assistance system is presented in [21]. In contrast to these works which adopt fuzzy logic either as a control law for trajectory tracking [3,41] or for assistance [21,51], the proposed solution in this paper integrates the concept of fuzzy logic into the adaptive control architecture to build a safety system that takes pain that could be felt by patients into account.…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy Logic Architecture for Rehabilitation Robotic Systems

Bouteraa

Abdallah

Elmogy

et al. 2020

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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Robots are highly incorporated in rehabilitation in the last decade to compensate lost functions in disabled individuals. By controlling the rehabilitation robots from far, many benefits are achieved. These benefits include but not restricted to minimum hospital stays, decreasing cost, and increasing the level of care. The main goal of this work is to have an effective solution to take care of patients from far. Tackling the problem of the remote control of rehabilitation robots is undergoing and highly challenging. In this paper, a remote wrist rehabilitation system is presented. The developed system is a sophisticated robot ensuring the two wrist movements (Flexion /extension and abduction/adduction). Additionally, the proposed system provides a software interface enabling the physiotherapists to control the rehabilitation process remotely. The patient’s safety during the therapy is achieved through the integration of a fuzzy controller in the system control architecture. The fuzzy controller is employed to control the robot action according to the pain felt by the patient. By using fuzzy logic approach, the system can adapt effectively according to the patients’ conditions. The Queue Telemetry Transport Protocol (MQTT) is considered to overcome the latency during the human robot interaction. Based on a Kinect camera, the control technique is made gestural. The physiotherapist gestures are detected and transmitted to the software interface to be processed and be sent to the robot. The acquired measurements are recorded in a database that can be used later to monitor patient progress during the treatment protocol. The obtained experimental results show the effectiveness of the developed remote rehabilitation system.

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“…A fuzzy-impedance control law was developed to estimate the human-robot interaction force [33]. A robotic system providing fuzzy-based adaptive assistance was presented in [34]. In contrast to the studies cited above, by adopting fuzzy logic as a control law for trajectory tracking [31,32] or for assistance [33,34], the proposed solution integrates the concept of fuzzy logic into the control architecture to build a safety system that takes into account pain that could be felt by the patient.…”

Section: Introductionmentioning

confidence: 99%

“…A robotic system providing fuzzy-based adaptive assistance was presented in [34]. In contrast to the studies cited above, by adopting fuzzy logic as a control law for trajectory tracking [31,32] or for assistance [33,34], the proposed solution integrates the concept of fuzzy logic into the control architecture to build a safety system that takes into account pain that could be felt by the patient. In this study, a fuzzy logic controller was employed with the proposed rehabilitation architecture in order to model patient pain during rehabilitation therapy.…”

Section: Introductionmentioning

confidence: 99%

Development of an IoT-Based Solution Incorporating Biofeedback and Fuzzy Logic Control for Elbow Rehabilitation

et al. 2020

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The last few years have seen significant advances in neuromotor rehabilitation technologies, such as robotics and virtual reality. Rehabilitation robotics primarily focuses on devices, control strategies, scenarios and protocols aimed at recovering sensory, motor and cognitive impairments often experienced by stroke victims. Remote rehabilitation can be adopted to relieve stress in healthcare facilities by limiting the movement of patients to clinics, mainly in the current COVID-19 pandemic. In this context, we have developed a remote controlled intelligent robot for elbow rehabilitation. The proposed system offers real-time monitoring and ultimately provides an electronic health record (EHR). Rehabilitation is an area of medical practice that treats patients with pain. However, this pain can prevent a person from positively interacting with therapy. To cope with this matter, the proposed solution incorporates a cascading fuzzy decision system to estimate patient pain. Indeed, as a safety measure, when the pain exceeds a certain threshold, the robot must stop the action even if the desired angle has not yet been reached. A fusion of sensors incorporating an electromyography (EMG) signal, feedback from the current sensor and feedback from the position encoder provides the fuzzy controller with the data needed to estimate pain. This measured pain is fed back into the control loop and processed to generate safe robot actions. The main contribution was to integrate vision-based gesture control, a cascade fuzzy logic-based decision system and IoT (Internet of Things) to help therapists remotely take care of patients efficiently and reliably. Tests carried out on three different subjects showed encouraging results.

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Intelligent bimanual rehabilitation robot with fuzzy logic based adaptive assistance

Cited by 9 publications

References 23 publications

A robot-assisted bilateral upper limb training strategy with subject-specific workspace: A pilot study

A robot-assisted bilateral upper limb training strategy with subject-specific workspace: A pilot study

A Fuzzy Logic Architecture for Rehabilitation Robotic Systems

Development of an IoT-Based Solution Incorporating Biofeedback and Fuzzy Logic Control for Elbow Rehabilitation

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