Development of a Hand Exoskeleton System for Quantitative Analysis of Hand Functions

Lee, Jeong-Soo; Lee, Minhyuk; Bae, Joonbum

doi:10.1007/s42235-018-0066-0

Cited by 8 publications

(5 citation statements)

References 28 publications

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“…The system developed by Lee et al (2018) is capable of independently actuating the MCP and PIP joints of the fingers and therefore provides two active degrees of freedom. A rigid kinematic structure comprised of two coupled linkages, a four-bar and a six-bar linkage, allows direct transmission of the actuation force to the proximal and medial finger phalanges.…”

Section: State Of the Art Wearable Hand Interaction Systemsmentioning

confidence: 99%

An Adaptive Mechatronic Exoskeleton for Force-Controlled Finger Rehabilitation

et al. 2021

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This paper presents a novel mechatronic exoskeleton architecture for finger rehabilitation. The system consists of an underactuated kinematic structure that enables the exoskeleton to act as an adaptive finger stimulator. The exoskeleton has sensors for motion detection and control. The proposed architecture offers three main advantages. First, the exoskeleton enables accurate quantification of subject-specific finger dynamics. The configuration of the exoskeleton can be fully reconstructed using measurements from three angular position sensors placed on the kinematic structure. In addition, the actuation force acting on the exoskeleton is recorded. Thus, the range of motion (ROM) and the force and torque trajectories of each finger joint can be determined. Second, the adaptive kinematic structure allows the patient to perform various functional tasks. The force control of the exoskeleton acts like a safeguard and limits the maximum possible joint torques during finger movement. Last, the system is compact, lightweight and does not require extensive peripherals. Due to its safety features, it is easy to use in the home. Applicability was tested in three healthy subjects.

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Section: State Of the Art Wearable Hand Interaction Systemsmentioning

confidence: 99%

An Adaptive Mechatronic Exoskeleton for Force-Controlled Finger Rehabilitation

et al. 2021

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“…The design with 2 DOFs could help the patient realize multiple training trajectories. Lee developed an exoskeleton with two driving modules [10] . The exoskeleton will provide two forces on the middle phalange and proximal phalange, while has the functions to measure the finger joint forces and angles.…”

Section: Analysis Of Current Mechanical Structures Of Finger Rehabilimentioning

confidence: 99%

Research on mechanical design of a multi-function finger rehabilitation robot

Yan

Vlădăreanu

Chen

et al. 2019

PEN

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Training with robots for injured fingers has achieved the efficacy of treatment. However, most of finger rehabilitation robots just have bending/extending movement. This paper presents a new multi-function finger rehabilitation robot with a simple mechanical structure, which could help fingers and thumb realize bending/extending movement and stretch/adduction movement. The paper firstly analyzes the hand physiological movement mechanism, confirming the motion range of each finger's joint. Based on the fingers movement rules, the robot driving structure has been developed, which includes thumb training module and fingers training module and frame. In order to prove the rationality of mechanism design, an experiment was conducted. The experiment proved that the mechanism can run smoothly, and its rope wheels also drive well without skidding phenomenon as well as its tension is appropriate.

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“…The exoskeleton hand comprises six linear actuators (two for the thumb and the other four for the fingers) and canrealizes both independent movements of each digit and coordinative movement involving multiple fingers for grasp and pinch. Bae et al [22][23][24][25] described the mechatronic design and development of four novel rehabilitation robotic exoskeleton hands. It presented a full range of motion for all hand phalanges and was specifically designed to carry out position and force-position control for passive and active rehabilitation routines.…”

Section: Introductionmentioning

confidence: 99%

sEMG signal-based portable hand and wrist integrated rehabilitation robot for hand dysfunction

Wang

Liang

Chen

et al. 2023

Preprint

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For patients with hand movement dysfunction caused by diseases such as stroke and hemiplegia, a portable hand and wrist integrated rehabilitation robot is presented based on the human factor engineering. The rehabilitation robot can achieve rehabilitation training of 14 DOFs of fingers and 2 DOFs of wrist. The four-channel sEMG signals of finger and wrist movements are collected by DELSYS equipment, and the pre-processing operations such as denoising and segmentation are carried out by MATLAB. Three kinds of time domain signal features are extracted and combined. The classification training model is obtained by LDA, CNN and LSTM classification method, respectively for different hand movements. Comparisons of the accuracy and learning speed of the three methods show that the CNN method has the highest accuracy and the fastest learning speed. The prototype model of the rehabilitation robot is generated by 3D printing, then the CPM rehabilitation and sEMG control experiments are carried out. Experiment results verify the effectiveness and efficiency of the proposed multi-function rehabilitation robot.

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Development of a Hand Exoskeleton System for Quantitative Analysis of Hand Functions

Cited by 8 publications

References 28 publications

An Adaptive Mechatronic Exoskeleton for Force-Controlled Finger Rehabilitation

An Adaptive Mechatronic Exoskeleton for Force-Controlled Finger Rehabilitation

Research on mechanical design of a multi-function finger rehabilitation robot

sEMG signal-based portable hand and wrist integrated rehabilitation robot for hand dysfunction

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