Finger Exoskeleton Research Articles

Investigations of motor performance with neuromodulation and exoskeleton using leader-follower modality: a tDCS study.

This study investigates how the combination of robot-mediated haptic interaction and cerebellar neuromodulation can improve task performance and promote motor skill development in healthy individuals using a robotic exoskeleton worn on the index finger. The authors propose a leader-follower type of mirror game where participants can follow a leader in a two-dimensional virtual reality environment while the exoskeleton tracks the index finger motion using an admittance filter. The game requires two primary learning phases: the initial phase focuses on mastering the pinching interface, while the second phase centers on predicting the leader's movements. Cerebral transcranial direct current stimulation (tDCS) with anodal polarity is applied to the subjects during the game. It is shown that the subjects' performance improves as they play the game. The combination of tDCS with finger exoskeleton significantly enhances task performance. Our research indicates that modulation of the cerebellum during the mirror game improves the motor skills of healthy individuals. The results also indicate potential uses for motor neurorehabilitation in hemiplegia patients.

Trajectory Synthesis and Linkage Design of Single-Degree-of-Freedom Finger Rehabilitation Device

For injured and after-stroke patients who temporarily lose their hand’s grasping abilities, assisting them in regaining their index finger mobility is very important in the rehabilitation process. In this paper, a finger rehabilitation device based on one degree-of-freedom (DOF) linkage mechanism is designed, aiming to lead the index finger through the flexion–extension trajectory during grasping tasks. Two types of one-DOF mechanisms, a four-bar linkage and a Watt-I six-bar linkage, are synthesized for the task trajectory. Various algorithms such as PSO, GA, and GA–BFGS are adopted and compared for the synthesis of these two types of mechanisms, among which the Watt-I six-bar linkage obtained with GA–BFGS shows the optimal performance in accuracy. Clinical biomechanical data are utilized to perform static analyses of the mechanisms, and the feasibility of the Watt-I six-bar linkage models is tested, compared, and demonstrated. Finally, the prototype of the six-bar linkage as well as a wearable exoskeleton finger rehabilitation device are designed to show how they are applied in the finger rehabilitation scenario.

Design, modeling and analysis of a novel index finger exoskeleton for stroke rehabilitation

Inpatient rehabilitation The rehabilitation of hand function in stroke patients is greatly aided by exoskeleton robots, which have become a new focus of research. However, there are still many defects in the existing research, for example, the Exoskeleton model is fixed and needs to be customized. The purpose of this study is to design and model an adjustable size Exoskeleton robot for hand rehabilitation of stroke patients. Hand dysfunction after stroke has a serious impact on the quality of life and daily activity ability of patients, so effective rehabilitation measures are crucial. As an innovative rehabilitation tool, Exoskeleton robot has the potential to assist movement and provide strength support. Through the biomechanical modeling of the hand and the exploration of the design principle of the Exoskeleton robot, this research proposes a design scheme that meets the requirements of functionality, safety and comfort. In the design process, we modeled the Kinematics of the exoskeleton robot based on the principles of hand biomechanics modeling. By establishing a simulation model, we verified the effectiveness and stability of the design. In conclusion, this study designed and modeled a Exoskeleton robot for hand rehabilitation of stroke patients. Through simulation and experimental verification, we proved the potential of the Exoskeleton robot in providing force support, Restoration Movement function and adapting to different hand sizes. This study provides a new tool for hand rehabilitation in stroke patients and provides reference for future design and improvement.

A Low Cost of an Exoskeleton Finger for Stroke Patient

Hand motor impairment poses a significant obstacle for stroke survivors, profoundly affecting their capacity to perform crucial daily tasks. This impairment frequently includes an inability to flex fingers effectively. This research is dedicated to the development of a low-cost exoskeleton finger tailored for stroke patient rehabilitation. The proposed exoskeleton finger boasts characteristics of being lightweight, affordable, and straightforward to manufacture. Moreover, it prioritizes portability and user-friendliness. The design integrates PLA material, springs, servo motors, and Arduino Uno technology. The study introduces two distinct exoskeleton finger designs, with one of them incorporating a glove component. Both exoskeleton finger variations comprise three degrees of freedom (DOF), three links, and two joints. The findings show that the exoskeleton finger's ability to effectively maneuver a paralyzed finger into different positions as commanded, facilitating the rehabilitation process. Furthermore, both designs exhibit reliability in aiding the opening and closing exercises of impaired fingers.

A Robotic Exoskeleton Assistive Device: Design and Kinematic Analysis of a Hand Exoskeleton for Assistance

Addressing the challenges faced by individuals with motor disabilities, which impedes ease in movement, coordination, or sensation, a low-weight hand exoskeleton was developed considering accessibility, low cost, adaptability, and mass manufacturing to overcome the impact of hand functioning disorders on people's physical and social well-being. In this paper, a 12-DOF Hand exoskeleton consisting of a 6-DOF Arm and 6-DOF finger exoskeleton was designed and later its kinematic analysis was performed. By taking into consideration the constraints provided by the exoskeleton to human hand motion, the Forward kinematics, using Denavit- Hartenberg (D-H) parameters were conducted to determine its workspace.

Study and implementation of fluxgate current sensor with wireless connectivity for finger exoskeleton rehabilitation

SummaryA fully integrated fluxgate magnetometer has been developed to monitor motor current in a finger exoskeleton device. The use of a fluxgate sensor can provide more accurate and natural movement of the fingers, as well as reducing the weight and complexity of the exoskeleton design. The sensor we developed incorporates several advanced features that provide enhanced sensitivity and accuracy compared to existing state‐of‐the‐art sensors. These features include a fluxgate frontend readout circuit with chopping stabilization technology, which achieves a gain of 14.3 V/T, a low noise density of 4.5 nT/√Hz, and a wide measurement range of ±1.5 mT. The gain variation of the sensor is only 1.5% at an 850 kHz bandwidth, and it has a wide dynamic current range from 0.005 mA to 100 A. The sensor also features an integrated 2.4 GHz wireless circuit for easy data transmission. The use of a fluxgate sensor in monitoring motor torque in the proximal interphalangeal joint can provide more precise and natural finger movement and reduce the weight and complexity of the exoskeleton design.

An Adaptive Hand Exoskeleton for Teleoperation System

Teleoperation can assist people to complete various complex tasks in inaccessible or high-risk environments, in which a wearable hand exoskeleton is one of the key devices. Adequate adaptability would be available to enable the master hand exoskeleton to capture the motion of human fingers and reproduce the contact force between the slave hand and its object. This paper presents a novel finger exoskeleton based on the cascading four-link closed-loop kinematic chain. Each finger has an independent closed-loop kinematic chain, and the angle sensors are used to obtain the finger motion including the flexion/extension and the adduction/abduction. The cable tension is changed by the servo motor to transmit the contact force to the fingers in real time. Based on the finger exoskeleton, an adaptive hand exoskeleton is consequently developed. In addition, the hand exoskeleton is tested in a master–slave system. The experiment results show that the adaptive hand exoskeleton can be worn without any mechanical constraints, and the slave hand can follow the motions of each human finger. The accuracy and the real-time capability of the force reproduction are validated. The proposed adaptive hand exoskeleton can be employed as the master hand to remotely control the humanoid five-fingered dexterous slave hand, thus, enabling the teleoperation system to complete complex dexterous manipulation tasks.

Application of Wearable Gloves for Assisted Learning of Sign Language Using Artificial Neural Networks

This study proposes the design and application of wearable gloves that can recognize sign language expressions from input images via long short-term memory (LSTM) network models and can learn sign language through finger movement generation and vibration motor feedback. It is difficult for nondisabled people who do not know sign language to express sign language accurately. Therefore, we suggest the use of wearable gloves for sign language education to help nondisabled people learn and accurately express sign language. The wearable glove consists of a direct current motor, a link (finger exoskeleton) that can generate finger movements, and a flexible sensor that recognizes the degree of finger bending. When the coordinates of the hand move in the input image, the sign language motion is fed back through the vibration motor attached to the wrist. The proposed wearable glove can learn 20 Korean sign language words, and the data used for learning are configured to represent the joint coordinates and joint angles of both the hands and body for these 20 sign language words. Prototypes were produced based on the design, and it was confirmed that the angle of each finger could be adjusted. Through experiments, a sign language recognition model was selected, and the validity of the proposed method was confirmed by comparing the generated learning results with the data sequence. Finally, we compared and verified the accuracy and learning loss using a recurrent neural network and confirmed that the test results of the LSTM model showed an accuracy of 85%.

Gear-based Multimodal Underdriven Index Finger Exoskeleton Rehabilitation Device

With the increase of stroke patients, wearable hand rehabilitation exoskeleton devices used to do mechanical rehabilitation training have received attention from researchers. Most of the rigid hand exoskeletons can only perform simple flexion and extension training of the finger as a whole, and not single joint training. Therefore, the subject of this paper is to develop a new multimodal underdriven index finger exoskeleton based on gear drive. The data analysis is compared to achieve the desired specific gesture. This device allows the user to further train the finger and also helps the medical practitioner to better determine the individual joint function of the patient.

Design and Optimization of a New Index Finger Exoskeleton Robot with Underactuated Mechanism

Spinal cord injury and stroke are the main diseases that lead to loss or decline of hand function, and hand rehabilitation exoskeletons can be used to help restore hand function. Due to the problems of traditional hand exoskeletons such as heavier weight, higher cost and limited mobility, this project aims to improve an index finger exoskeleton robot with an underactuated mechanism, improve its bending and extension angles, and optimize the robot to a certain extent. flexibility. At the same time, the genetic algorithm is combined in the control system to make all the control indexes reach excellent. This project establishes a 3D model through Solidworks, and at the same time proves the feasibility of improvement by establishing a kinematic model. In terms of design, the mechanism is adjusted according to the range of activities of MCP(metacarpophalangian joint) and PIP(proximal interphalangeal joint) to optimize the flexibility of the design model. In the aspect of control system, the genetic algorithm is combined with system identification and PID(Proportion Integration Differentiation)control, in order to reach the objective of establishing a more precise training model and finding appropriate PID parameters. This project has a positive effect on the medical efficiency of the underactuated hand exoskeleton.

Optimal Synthesis of the Stephenson-II Linkage for Finger Exoskeleton Using Swarm-based Optimization Algorithms

Optimal Synthesis of the Stephenson-II Linkage for Finger Exoskeleton Using Swarm-based Optimization Algorithms

Design and Optimization of an Index Finger Exoskeleton With Semi-Wrapped Fixtures and Series Elastic Actuators.

This paper proposes a novel index finger exoskeleton with semi-wrapped fixtures and elastomer-based clutched series elastic actuators. The semi-wrapped fixture is similar to a clip, which improves the convenience of donning/doffing and connection stability. The elastomer-based clutched series elastic actuator can limit the maximum transmission torque and improve passive safety. Second, the kinematic compatibility of the exoskeleton mechanism for the proximal interphalangeal joint is analyzed, and its kineto-statics model is built. To avoid the damage caused by the force along the phalanx, considering the individual difference in the size of the finger segment, a two-level optimization method is proposed to minimize the force along the phalanx. Finally, the performance of the proposed index finger exoskeleton is tested. Statistical results indicate that the donning/doffing time of the semi-wrapped fixture is significantly less than that of the Velcro. Compared with the Velcro, the average value of the maximum relative displacement between the fixture and the phalanx is reduced by 59.7%. Compared with the exoskeleton before optimization, the maximum force along the phalanx generated by the exoskeleton after optimization is reduced by 23.65%. The experimental results show that the proposed index finger exoskeleton can improve the convenience of donning/doffing, connection stability, comfort, and passive safety.

Bowden-line Foot-controlled Finger Exoskeleton Device Driven by Pneumatic Muscles

With the world being increasingly reliant on computers, hand disorders have become prevalent amongst the general population. To help patients with hand disorders better recover while still allowing them to live their normal lives, glove-like wearable robotic de-vices were developed. Most of those robotic devices, however, generate motion through electric motors, which is heavy and inconvenient. Soft body robots are popular nowadays because they are versatile, safe, low in cost, and comfortable to wear. Thus, a pneumatic muscle hand device is presented in this paper to provide aid to those with impaired hands in their daily lives. This system features 10 pneumatic muscles connected with strings attached to the inner and outer sides of every finger powered by an air valve which allows the retraction of the patient’s fingers. The patient is introduced to 5 pressure sensors able to be controlled by foot. To enable the patient to use the device on their own, the system is designed in a back-pack-like style.

Mechanical design and feasibility of a finger exoskeleton to support finger extension of severely affected stroke patients.

In this paper we presented the mechanical design and evaluation of a low-profile and lightweight exoskeleton that supports the finger extension of stroke patients during daily activities without applying axial forces to the finger. The exoskeleton consists of a flexible structure that is secured to the index finger of the user while the thumb is fixed in an opposed position. Pulling on a cable will extend the flexed index finger joint such that objects can be grasped. The device can achieve a grasp size of at least 7 cm. Technical tests confirmed that the exoskeleton was able to counteract the passive flexion moments corresponding to the index finger of a severely affected stroke patient (with an MCP joint stiffness of k = 0.63Nm/rad), requiring a maximum cable activation force of 58.8N. A feasibility study with stroke patients (n=4) revealed that the body-powered operation of the exoskeleton with the contralateral hand caused a mean increase of 46° in the range of motion of the index finger MCP joint. The patients (n=2) who performed the Box & Block Test were able to grasp and transfer maximally 6 blocks in 60 sec. with exoskeleton, compared to 0 blocks without exoskeleton. Our results showed that the developed exoskeleton has the potential to partially restore hand function of stroke patients with impaired finger extension capabilities. An actuation strategy that does not involve the contralateral hand should be implemented during further development to make the exoskeleton suitable for bimanual daily activities.

Design and Performance Analysis of a Bioelectronic Controlled Hybrid Serial-Parallel Wrist Exoskeleton.

Wrist exoskeletons are increasingly being used in the rehabilitation of stroke and hand dysfunction because of its ability to assist patients in high intensity, repetitive, targeted and interactive rehabilitation training. However, the existing wrist exoskeletons cannot effectively replace the work of therapist and improve hand function, mainly because the existing exoskeletons cannot assist patients to perform natural hand movement covering the entire physiological motor space (PMS). Here, we present a bioelectronic controlled hybrid serial-parallel wrist exoskeleton HrWr-ExoSkeleton (HrWE) which is based on the PMS design guidance, the gear set can carry out forearm pronation/supination (P/S) and the 2-DoF parallel configuration fixed on the gear set can carry out wrist flexion/extension (F/E) and radial/ulnar deviation (R/U). This special configuration not only provides enough range of motion (RoM) for rehabilitation training (85F/85E, 55R/55U, and 90P/90S), but also makes it easier to provide the interface for finger exoskeletons and be adapted to upper limb exoskeletons. In addition, to further improve the rehabilitation effect, we propose a HrWE-assisted active rehabilitation training platform based on surface electromyography signals.

Development of Two-Way Self-Adaptive Gripper Using Differential Gear

In this paper, a two-way self-adaptive gripper that has adaptability to external disturbance loads during linear opening/closing pinch actions and adaptability to encompass a variety of shapes during grasping using a single actuator is proposed, unlike the previous self-adaptive robotic grippers capable of only shape adaptation. Therefore, both linear motion adaptability and shape adaptability during parallel grasping situations are enabled by the proposed design of the gripper. Adaptation to the linear pinch motion is provided through the use of a differential gear, the two outputs of which drive the two tips of the gripper. If facing uneven external loads, the differential gear adaptively alters the speeds of the two outputs, resulting in different closing speeds of the two gripper tips. Despite asymmetric closing, very stable grasping can be guaranteed for such a situation. The differential gear can even complete the grasping by intentionally or unintentionally fixing one of the gripper tips. The proposed design is also capable of shape adaptation in the encompassing grasping mode by adopting a parallel-linkage gripper mechanism, consisting of an exoskeleton and 6 internal joints with a spring element. The finger exoskeleton facilitates pinch and spread actions, while the encompassing action is carried out by adjusting the internal linkage. Based on the kinematic analysis and modeling of the proposed gripper, a prototype of the two-way adaptive gripper hardware was developed. Several experiments were performed to verify the feasibility and validity of the proposed gripper system. The actuator using the proposed differential gear was shown to be able to grasp objects in jammed conditions. In addition, the gripper was able to perform grasping actions, such as pinch, spread, and encompassing grasp.

Design, modeling, and characteristic analysis of an index finger exoskeleton for rehabilitation

Since the rehabilitation hand exoskeleton robot is the current research hotspot, it can play a great role in patients’ hand rehabilitation and can replace the rehabilitation physician to treat the patient. Many of today’s rehabilitation hand exoskeleton robots can not achieve a good rehabilitation effect. In order to improve the treatment effect of the rehabilitation hand exoskeleton robot on patients and alleviate the pressure of insufficient human hands in China’s rehabilitation physicians, this paper, on the basis of analyzing the biological characteristics of the human hand, focuses on the functional analysis of the rehabilitation exoskeleton hand, the mechanical structure design of the exoskeleton hand, Kinematic analysis, Modeling and simulation to design an exoskeleton hand using a one-wheel-two way combining sliding guide rod and SEA tandem elastic drive to achieve the mechanism that can adjust the stretch according to the length of the finger and the rehabilitation force perpendicular for the purpose of the finger surface. A closed-loop structure is established to analyze the mechanism of plane motion of the structure and the coupling of the structure and the range of motion of the human hand. Through simulation analysis of the motion trajectory of the structure and the stability of the dynamic model analysis system based on the force source control method to establish a dynamic model of the tandem elastic drive, the results show that the DIP joint rotation angle is 16-73 degrees, the PIP joint rotation angle is 0-108 degrees, and the MP joint is 0-86 degrees, which is basically consistent with the human hand, and the series elastic drive should choose a smaller stiffness and larger damping to ensure the stability of the system.

Design and Prototyping of an Underactuated Index Finger Exoskeleton

At present, the rehabilitation treatment methods for hand dysfunction caused by stroke are mainly to reconstruct or improve the hand motor function of stroke patients through motor learning. To realize smooth motion without the interference of the underactuated hand exoskeleton system, this paper designs and manufactures an exoskeleton system in which a single motor drives the index finger MCP and PIP to rotate. The simulation results show that the system can realize 0-90° motion of MCP and 0-110° motion of PIP, and the motion is smooth and without interference. The system is prototyping by 3D printing. By testing the prototype, the actual movement range of the prototype is slightly smaller than the design index, and it can achieve the 0-90° movement of the MCP, but the PIP can only achieve the 0-90° movement. Through further research and analysis, it is determined that this phenomenon is caused by unreasonable motion coupling between MCP and PIP, inaccurate axial positioning, and offset of the rotation center of each joint. The system will be used as the basis for follow-up research and will continue to be optimized in combination with the problems shown in the actual wearing, and finally design and manufacture a complete set of underactuated hand exoskeleton systems that can move smoothly without interference.

A Rigid and Flexible Combined Finger Exoskeleton Design with Variable Curvature

Some hand exoskeletons have been used in the rehabilitation treatment of paralyzed patients caused by stroke and cerebral apoplexy as a result of research into hand exoskeletons. However, how to make the patient more comfortable to use and how to make the exoskeleton more precise are still key issues that need to be studied. Aiming at the motion law and skeletal characteristics of the human hand, this paper proposes a soft exoskeleton machine for hand rehabilitation training that combines rigidity and flexibility. Using a simplified two-layer sliding spring mechanism, the device combines the comfort and fit of a flexible device with the accurate kinematics of a rigid device. The mechanism requires only one degree of freedom to drive the normal flexion and expansion of the three finger joints. By changing the section thickness of the spring sheet to change its section moment of inertia, the bending effect of the mechanism is optimized to better fit the bending characteristics of the finger joints. To simplify the simulation of the mechanism, the method of the pseudo-rigid-body model is used to target the spring leaf’s nonlinear deformation, to achieve intuitively understandable kinematics. Finally, the accuracy of the design is demonstrated through simulation and prototype models.

Design and Control of an Underactuated Finger Exoskeleton for Assisting Activities of Daily Living

In this article, a novel underactuated finger exoskeleton is designed to assist grasping tasks for the elderly with weak muscle strength. In mechanical design, the human finger’s phalanges and joints are considered as part of the kinematic chains to realize the human-robot kinematic compatibility. The proposed finger exoskeleton achieves the finger preshaping and grasps objects with generic shapes. The proposed exoskeleton is both actively and passively backdriveable. Moreover, the weight of the wearable part of the proposed exoskeleton is 127 g, and the overall weight is 476 g, which indicates the proposed exoskeleton is lightweight and portable. To improve the grasping performance, the multiobjective genetic algorithm is implemented to optimize contact forces, which is to maximize the sum of the forces exerted on the index finger phalanges by the exoskeleton and to minimize the difference between the contact forces. After optimization, the sum of contact forces is risen by 15%, and the difference between forces is decreased by 53%. Furthermore, the admittance control is applied to make the proposed finger exoskeleton more compliant in the preshaping phase, and the admittance control is also implemented to achieve the fingertip grasping force control in the grasping phase. Finally, experiments have been conducted to verify the range of motion, grasping forces, and feasibility of the proposed index finger exoskeleton. The effectiveness of the control algorithm has also been verified by experiments.