Design of a Two-DOFs Driving Mechanism for a Motion-Assisted Finger Exoskeleton

Design Optimization of a Soft Robotic Rehabilitation Glove Based on Finger Workspace Analysis

The finger workspace is crucial for performing various grasping tasks. Thus, various soft rehabilitation gloves have been developed to assist individuals with paralyzed hands in activities of daily living (ADLs) or rehabilitation training. However, most soft robotic glove designs are insufficient to assist with various hand postures because most of them use an underactuated mechanism for design simplicity. Therefore, this paper presents a methodology for optimizing the design of a high-degree-of-freedom soft robotic glove while not increasing the design complexity. We defined the required functional workspace of the index finger based on ten frequently used grasping postures in ADLs. The design optimization was achieved by simulating the proposed finger-robot model to obtain a comparable workspace to the functional workspace. In particular, the moment arm length for extension was optimized to facilitate the grasping of large objects (precision disk and power sphere), whereas a torque-amplifying routing design was implemented to aid the grasping of small objects (lateral pinch and thumb-two-finger pinch). The effectiveness of the optimized design was validated through testing with a stroke survivor and comparing the assistive workspace. The observed workspace demonstrated that the optimized glove design could assist with nine out of the ten targeted grasping posture functional workspaces. Furthermore, the assessment of the grasping speed and force highlighted the glove's usability for various rehabilitation activities. We also present and discuss a generalized methodology to optimize the design parameters of a soft robotic glove that uses an underactuated mechanism to assist the targeted workspace. Overall, the proposed design optimization methodology serves as a tool for developing advanced hand rehabilitation robots, as it offers insight regarding the importance of routing optimization in terms of the workspace.

Dynamic Analysis and Experimental Study of Lasso Transmission for Hand Rehabilitation Robot

Lasso transmission is a method for realizing long-distance flexible transmission and lightweight robots. However, there are transmission characteristic losses of velocity, force, and displacement during the motion of lasso transmission. Therefore, the analysis of transmission characteristic losses of lasso transmission has become the focus of research. For this study, at first, we developed a new flexible hand rehabilitation robot with a lasso transmission method. Second, the theoretical analysis and simulation analysis of the dynamics of the lasso transmission in the flexible hand rehabilitation robot were carried out to calculate the force, velocity, and displacement losses of the lasso transmission. Finally, the mechanism and transmission models were established for experimental studies to measure the effects of different curvatures and speeds on the lasso transmission torque. The experimental data and image analysis results show torque loss in the process of lasso transmission and an increase in torque loss with the increase in the lasso curvature radius and transmission speed. The study of the lasso transmission characteristics is important for the design and control of hand functional rehabilitation robots, providing an important reference for the design of flexible rehabilitation robots and also guiding the research on the lasso regarding the compensation method for transmission losses.

Experimental Characterization of A-AFiM, an Adaptable Assistive Device for Finger Motions

Robot rehabilitation devices are attracting significant research interest, aiming at developing viable solutions for increasing the patient’s quality of life and enhancing clinician’s therapies. This paper outlines the design and implementation of a low-cost robotic system that can assist finger motion rehabilitation by controlling and adapting both the position and velocity of fingers to the users′ needs. The proposed device consists of four slider-crank mechanisms. Each slider-crank is fixed and moves one finger (from the index to the little finger). The finger motion is adjusted through the regulation of a single link length of the mechanism. The trajectory that is generated corresponds to the natural flexion and extension trajectory of each finger. The functionality of this mechanism is validated by experimental image processing. Experimental validation is performed through tests on healthy subjects to demonstrate the feasibility and user-friendliness of the proposed solution.

Requirements and Solutions for Motion Limb Assistance of COVID-19 Patients

COVID-19 patients are strongly affected in terms of limb motion when imbedded during the acute phase of the infection, but also during the course of recovery therapies. Peculiarities are investigated for design requirements for medical devices in limb motion assistance for those patients. Solutions are analyzed from existing medical devices to outline open issues to provide guidelines for the proper adaption or for new designs supporting patients against COVID-19 effects. Examples are reported from authors’ activities with cable driven assisting devices.

Design and Prototyping of an Underactuated Hand Exoskeleton With Fingers Coupled by a Gear-Based Differential

Exoskeletons and more in general wearable mechatronic devices represent a promising opportunity for rehabilitation and assistance to people presenting with temporary and/or permanent diseases. However, there are still some limits in the diffusion of robotic technologies for neuro-rehabilitation, notwithstanding their technological developments and evidence of clinical effectiveness. One of the main bottlenecks that constrain the complexity, weight, and costs of exoskeletons is represented by the actuators. This problem is particularly evident in devices designed for the upper limb, and in particular for the hand, in which dimension limits and kinematics complexity are particularly challenging. This study presents the design and prototyping of a hand finger exoskeleton. In particular, we focus on the design of a gear-based differential mechanism aimed at coupling the motion of two adjacent fingers and limiting the complexity and costs of the system. The exoskeleton is able to actuate the flexion/extension motion of the fingers and apply bidirectional forces, that is, it is able to both open and close the fingers. The kinematic structure of the finger actuation system has the peculiarity to present three DoFs when the exoskeleton is not worn and one DoF when it is worn, allowing better adaptability and higher wearability. The design of the gear-based differential is inspired by the mechanism widely used in the automotive field; it allows actuating two fingers with one actuator only, keeping their movements independent.

Design, modeling and control of an index finger exoskeleton for rehabilitation

With diverse areas of applications, wearable robotic exoskeleton devices have gained attention in the past decade. These devices cover one or more human limbs/joints and have been presented for rehabilitation, strength augmentation and interaction with virtual reality. This research is focused towards design, modeling and control of a novel series elastic actuation (SEA) based index finger exoskeleton with a targeted torque rendering capability of 0.3 Nm and a force control bandwidth of 3 Hz. The proposed design preserves the natural range of motion of the finger by incorporating five passive and two actively actuated joints and provides active control of metacarpophalangeal and proximal interphalangeal joints. Forward and inverse kinematics for both position and velocity have been solved using closed loop vector analysis by including human finger as an integral part of the system. For accurate force control, a cascaded control structure has been presented. Force controlled trajectories have been proposed to guide the finger along preprogrammed virtual paths. Such trajectories serve to gently guide the finger towards the correct rehabilitation protocol, thus acting as an effective replacement of intervention by a human therapist. Extensive computer simulations have been performed before fabricating a prototype and performing experimental validation. Results show accurate modeling and control of the proposed design.

Numerical and experimental performance estimation for a ExoFing - 2 DOFs finger exoskeleton

This paper presents a numerical and experimental validation of ExoFing, a two-degrees-of-freedom finger mechanism exoskeleton. The main functionalities of this device are investigated by focusing on its kinematic model and by computing its main operation characteristics via numerical simulations. Experimental tests are designed and carried out for validating both the engineering feasibility and effectiveness of the ExoFing system aiming at achieving a human index finger motion assistance with cost-oriented and user-friendly features.

Operation Safety of a 2-DoF Planar Mechanism for Arm Rehabilitation

The operation safety of rehabilitation devices must be addressed early in the development process and before being tested on people. In this paper, the operation safety of a 2-DoF (degrees of freedom) planar mechanism for arm rehabilitation is addressed. Then, the safety and efficiency of the device operation is assessed through the Transmission Index (TI) distribution in its workspace. Furthermore, the produced stresses on the human arm are assessed via the FEM (finite element method) when the rehabilitation device reaches five critical positions within its workspace. The TI distribution showed that the proposed design has a proper behaviour from a force transmission point of view, avoiding any singular configuration that might cause a control failure and subsequent risk for the user and supporting the user’s motion with a good efficiency throughout its operational workspace. The FEM analysis showed that Nurse operation is safe for the human arm since a negligible maximum stress of 6.55 × 103 N/m2 is achieved by the human arm when the device is located on the evaluated critical positions.

Design of sensing system for experimental modeling of soft actuator applied for finger rehabilitation

Safe interaction and inherent compliance with soft robots have motivated the evolution of soft rehabilitation robots. Among these, soft robotic gloves are known as an effective tool for stroke rehabilitation. This research proposed a pneumatically actuated soft robotic for index finger rehabilitation. The proposed system consists of a soft bending actuator and a sensing system equipped with four inertial measurement unit sensors to generate kinematic data of the index finger. The designed sensing system can estimate the range of motion (ROM) of the finger’s joints by combining angular velocity and acceleration values with the standard Kalman filter. The sensing system is evaluated regarding repeatability and reliability through static and dynamic experiments in the first step. The root mean square error attained in static and dynamic states are 2 $^\circ$ and 3 $^\circ$ , sequentially, representing an efficient function of the fusion algorithm. In the next step, experimental models have been developed to analyze and predict a soft actuator’s behavior in free and constrained states using the sensing system’s data. Thus, parametric system identification methods, artificial neural network—multilayer perceptron (ANN-MLP), and artificial neural network—radial basis function algorithms (ANN-RBF) have been compared to achieve an optimal model. The results reveal that ANN models, particularly RBF ones, can predict the actuator behavior with reasonable accuracy in the free and constrained state (<1 $^\circ$ ). Hence, the need for intricate analytical modeling and material characterization will be eliminated, and controlling the soft actuator will be more practical. Besides, it assesses the ROM and finger functionality.

An Adaptive Mechatronic Exoskeleton for Force-Controlled Finger Rehabilitation

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.

A prototype characterization of ExoFinger, a finger exoskeleton

This article presents an experimental characterization of ExoFinger, a finger exoskeleton for finger motion assistance. The exoskeletal device is analyzed in experimental lab activities that have been conducted with different users to characterize the operation performance and to demonstrate the adaptability of the proposed device. The behavior of this device is characterized in detail using sensors to measure finger motion and power consumption. Sensor measures also demonstrate the given motion assistance performance in terms of an electrical finger response and finger temperature by resulting in an efficient solution with a large motion range of a finger in assistance of recovering finger motion.

Design and evaluation of a surface electromyography-controlled lightweight upper arm exoskeleton rehabilitation robot

Nowadays, the rehabilitation robot has been developed for rehabilitation therapy. However, there are few studies on upper arm exoskeletons for rehabilitation training of muscle strength. This article aims to design a surface electromyography-controlled lightweight exoskeleton rehabilitation robot for home-based progressive resistance training. The exoskeleton’s lightweight structure is designed based on the kinematic model of the elbow joint and ergonomics sizes of the arm. At the same time, the overall weight of the exoskeleton is controlled at only 3.03 kg. According to the rehabilitation training task, we use torque limit mode to ensure stable torque output at variable velocity. We also propose a surface electromyography-based control method, which uses k- Nearest Neighbor algorithm to classify surface electromyographic signals under progressive training loads, and utilizes principal component analysis to improve the recognition accuracy to control the exoskeleton to provide muscle strength compensation. The assessment experiment of the exoskeleton rehabilitation robot shows that the dynamic recognition accuracy of this control method is 80.21%. Muscle activity of biceps brachii and triceps brachii under each training load decreases significantly when subjects with the exoskeleton robot. The results indicate that the exoskeleton rehabilitation robot can output the corresponding torque to assist in progressive resistance training. This study provides a solution to potential problems in the family-oriented application of exoskeleton rehabilitation robots.

Modelling and Control of Mechatronic and Robotic Systems

Nowadays, the modelling and control of mechatronic and robotic systems is an open and challenging field of investigation in both industry and academia [...]

A fairly simple mechatronic device for training human wrist motion

This article proposes a novel device for wrist motion rehabilitation. The proposed mechatronic architecture is based on a simple user-friendly design, which includes a mobile platform for hand support, which is operated by a single actuator. A dedicated assist-as-needed control is designed to operate the device for the required movements. The proposed control strategy is also integrated into a gaming software for stimulating the exercising by means of various interactions with patients. Experimental tests are carried out with 14 healthy subjects at the Physiotherapy Clinical Hospital of the Federal University of Uberlandia. Also, three patients with stroke have been enrolled in a pilot clinical testing. Each of the patients has been involved in four sessions per month with 15 min of assisted treatment. Results of experimental tests are analyzed in terms of improvements and amplitude gains for the flexion and extension wrist movements. Experimental results are reported as evidence for the feasibility and soundness of the proposed device as a tool to assist professionals in procedures of wrist rehabilitation.