Power Assist Rehabilitation Robot and Motion Intention Estimation

Adeola-Bello, Zulikha Ayomikun; Azlan, Norsinnira Zainul

doi:10.31763/ijrcs.v2i2.650

Cited by 4 publications

(2 citation statements)

References 97 publications

(103 reference statements)

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“…For the motion intention controller, the impedance control is adopted [21]. Impedance control is defined as the relationship between the motion state of the endpoint and applied force.…”

Section: Motion Intention Controllermentioning

confidence: 99%

Control Strategy for Power Assist Upper Limb Rehabilitation Robot with the Therapist’s Motion Intention Prediction

Adeola-Bello

Azlan

Hassan

2023

IIUMEJ

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Currently, fully automated rehabilitation robots can assist therapists in providing rehabilitation therapy, hence the patients could get hurt. On the other hand, manual treatment may cause less patient injury but it is tiresome, and there are not enough therapists in most countries. Power assist rehabilitation robots can support the therapists in conducting the treatment and may help to alleviate this problem. The goal of this study is to develop a control strategy for the robot to assist the therapist’s movement in a power assist upper limb rehabilitation treatment. The system combines the advantages of robotic and manual rehabilitation therapy. Torque and position sensors fitted on the power assist upper limb rehabilitation robot arm are used for motion intention estimation. The amount of angular velocity necessary to be delivered to the feedback controller will be determined by predicting the therapist‘s motion intention using the impedance control method. The resulting velocity from the motion intention estimator is incorporated into the Sliding Mode Control - Function Approximation Technique (SMC-FAT) based adaptive controller. The SMC-FAT based adaptive controller in the feedback loop, overcomes the uncertain parameters in the combination of the robot and the human arm. The motion intention estimator forecasts the movement of therapists. The proposed controller is used to regulate elbow flexion and extension motion on a power assist upper limb rehabilitation robot with one degree of freedom (DOF). The proposed control system has been tested using MATLAB simulation and hardware experimental tests. The outcomes demonstrate the effectiveness of the proposed controller in directing the rehabilitation robot to follow the desired trajectory based on the therapist's motion intention, with maximum errors of 0.002rad/sec, 0.005rad/sec and 0.02rad/sec for sinusoidal, constant torque values, and hardware experiment respectively. ABSTRAK: Pada masa ini, robot rehabilitasi automatik sepenuhnya dapat membantu ahli terapi dalam menyediakan terapi pemulihan, tetapi pesakit berkemungkinan tercedera. Sebaliknya, rawatan manual berkemungkinan mengurangkan kecederaan pesakit tetapi ia memenatkan, dan terdapat kurang ahli terapi yang mencukupi di kebanyakan negara. Robot pembantu rehabilitasi dapat membantu ahli terapi dalam menjalankan pemulihan dan mengurangkan masalah ini. Sistem ini menggabungkan kelebihan terapi pemulihan robotik dan manual. Alat pengesan tork dan kedudukan diletakkan pada anggota atas lengan robot rahabilitasi yang digunakan bagi mengesan anggaran jarak pergerakan ahli terapi. Anggaran halaju sudut diperlukan bagi kawalan gerak balas dan dapat diketahui melalui anggaran niat gerakan ahli terapi menggunakan kaedah kawalan impedans. Halaju yang terhasil daripada anggaran niat gerakan diadaptasi ke dalam pengawal adaptif berasaskan Kawalan Mod Gelongsor - Teknik Anggaran Fungsi (SMC-FAT). Pengawal penyesuaian berasaskan SMC-FAT dalam gelung maklum balas, mengatasi parameter yang tidak pasti dalam gabungan robot dan lengan manusia. Penganggar niat gerakan meramalkan gerakan ahli terapi. Pengawal yang dicadangkan digunakan bagi mengawal lenturan siku dan gerakan lanjutan pada robot rehabilitasi dengan satu darjah kebebasan (DOF). Sistem kawalan yang dicadangkan telah diuji menggunakan simulasi MATLAB dan ujian eksperimen perkakasan. Dapatan kajian menunjukkan keberkesanan pengawal yang dicadangkan dalam mengarahkan robot rehabilitasi mengikut trajektori yang dikehendaki berdasarkan niat gerakan ahli terapi, dengan ralat maksimum masing-masing 0.002rad/s dan 0.005rad/s bagi sinusoidal, nilai tork malar, dan eksperimen perkakasan masing-masing.

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“…For the motion intention controller, the impedance control is adopted [21]. Impedance control is defined as the relationship between the motion state of the endpoint and applied force.…”

Section: Motion Intention Controllermentioning

confidence: 99%

Control Strategy for Power Assist Upper Limb Rehabilitation Robot with the Therapist’s Motion Intention Prediction

Adeola-Bello

Azlan

Hassan

2023

IIUMEJ

Self Cite

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“…Many systems used various grounded device like space balls or joystick to control the operation of the robotic arm [5]- [6], some uses sensors [7] whereas some systems imply artificial intelligence-trained models to mimic the operator's arm positions [8], different approaches have been used for the realization of force feedback using SMA clutch mechanism on distal finger segments [9] and through spikes generated through a neural spiking model on receiving force signal via load cells mounted on the robotic end effector [10]. A power assist system is a human-robot cooperation technology and is mostly used in the rehabilitation and healthcare of disabled or older people [11]. The robotic arms for teleoperation tasks are difficult tasks and require training [12].…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of Force Sensation and Feedback Systems for Telepresence Robotic Arm

Nisa

Samo

Nizamani

et al. 2022

Journal of Robotics and Control

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Humans put their own lives aside to save other human’s life and perform risky and dangerous activities. The risk can be reduced by using new technologies. This research study focuses on telepresence and teleoperation systems with motion and force control systems that replace humans in hazardous workspaces. In telepresence, the system helps humans to visualize the environment in real-time. In teleoperation, the system provides sensation to assist human beings in performing out-of-reach and dangerous operations safely as in real, providing a shadow hand to the operator. In this study, a system is developed that consists of a slave robotic arm and a master wearable device with bidirectional communication between the robotic arm and operator (master wearable device). It also presents a gesture-controlled robotic arm that uses sensors to read and translate human arm movements as commands. The slave robotic arm, senses applied force on an object and a master wearable device develops the force according to sensed force, in a result operator senses/feels the same object in the control room at distance. The slave robotic arm also mimics the operator arm to reach the proper position of an object. Several experiments were conducted with untrained personnel and satisfactory results were yielded, which showed that the motion and force replication is 90-95% accurate.

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