An overview of robotic/mechanical devices for post-stroke thumb rehabilitation

Hand Exoskeleton Design and Human–Machine Interaction Strategies for Rehabilitation

Stroke and related complications such as hemiplegia and disability create huge burdens for human society in the 21st century, which leads to a great need for rehabilitation and daily life assistance. To address this issue, continuous efforts are devoted in human–machine interaction (HMI) technology, which aims to capture and recognize users’ intentions and fulfil their needs via physical response. Based on the physiological structure of the human hand, a dimension-adjustable linkage-driven hand exoskeleton with 10 active degrees of freedom (DoFs) and 3 passive DoFs is proposed in this study, which grants high-level synergy with the human hand. Considering the weight of the adopted linkage design, the hand exoskeleton can be mounted on the existing up-limb exoskeleton system, which greatly diminishes the burden for users. Three rehabilitation/daily life assistance modes are developed (namely, robot-in-charge, therapist-in-charge, and patient-in-charge modes) to meet specific personal needs. To realize HMI, a thin-film force sensor matrix and Inertial Measurement Units (IMUs) are installed in both the hand exoskeleton and the corresponding controller. Outstanding sensor–machine synergy is confirmed by trigger rate evaluation, Kernel Density Estimation (KDE), and a confusion matrix. To recognize user intention, a genetic algorithm (GA) is applied to search for the optimal hyperparameters of a 1D Convolutional Neural Network (CNN), and the average intention-recognition accuracy for the eight actions/gestures examined reaches 97.1% (based on K-fold cross-validation). The hand exoskeleton system provides the possibility for people with limited exercise ability to conduct self-rehabilitation and complex daily activities.

Hand Rehabilitation Devices: A Comprehensive Systematic Review

A cerebrovascular accident, or a stroke, can cause significant neurological damage, inflicting the patient with loss of motor function in their hands. Standard rehabilitation therapy for the hand increases demands on clinics, creating an avenue for powered hand rehabilitation devices. Hand rehabilitation devices (HRDs) are devices designed to provide the hand with passive, active, and active-assisted rehabilitation therapy; however, HRDs do not have any standards in terms of development or design. Although the categorization of an injury’s severity can guide a patient into seeking proper assistance, rehabilitation devices do not have a set standard to provide a solution from the beginning to the end stages of recovery. In this paper, HRDs are defined and compared by their mechanical designs, actuation mechanisms, control systems, and therapeutic strategies. Furthermore, devices with conducted clinical trials are used to determine the future development of HRDs. After evaluating the abilities of 35 devices, it is inferred that standard characteristics for HRDs should include an exoskeleton design, the incorporation of challenge-based and coaching therapeutic strategies, and the implementation of surface electromyogram signals (sEMG) based control.

Current State of Robotics in Hand Rehabilitation after Stroke: A Systematic Review

Among the methods of hand function rehabilitation after stroke, robot-assisted rehabilitation is widely used, and the use of hand rehabilitation robots can provide functional training of the hand or assist the paralyzed hand with activities of daily living. However, patients with hand disorders consistently report that the needs of some users are not being met. The purpose of this review is to understand the reasons why these user needs are not being adequately addressed, to explore research on hand rehabilitation robots, to review their current state of research in recent years, and to summarize future trends in the hope that it will be useful to researchers in this research area. This review summarizes the techniques in this paper in a systematic way. We first provide a comprehensive review of research institutions, commercial products, and literature. Thus, the state of the art and deficiencies of functional hand rehabilitation robots are sought and guide the development of subsequent hand rehabilitation robots. This review focuses specifically on the actuation and control of hand functional rehabilitation robots, as user needs are primarily focused on actuation and control strategies. We also review hand detection technologies and compare them with patient needs. The results show that the trends in recent years are more inclined to pursue new lightweight materials to improve hand adaptability, investigating intelligent control methods for human-robot interaction in hand functional rehabilitation robots to improve control robustness and accuracy, and VR virtual task positioning to improve the effectiveness of active rehabilitation training.

Mechanical Design and Analysis of the End-Effector Finger Rehabilitation Robot (EFRR) for Stroke Patients

Most existing finger rehabilitation robots are structurally complex and cannot be adapted to multiple work conditions, such as clinical and home. In addition, there is a lack of attention to active adduction/abduction (A/A) movement, which prevents stroke patients from opening the joint in time and affects the rehabilitation process. In this paper, an end-effector finger rehabilitation robot (EFRR) with active A/A motion that can be applied to a variety of applications is proposed. First, the natural movement curve of the finger is analyzed, which is the basis of the mechanism design. Based on the working principle of the cam mechanism, the flexion/extension (F/E) movement module is designed and the details used to ensure the safety and reliability of the device are introduced. Then, a novel A/A movement module is proposed, using the components that can easily individualized design to achieve active A/A motion only by one single motor, which makes up for the shortcomings of the existing devices. As for the control system, a fuzzy proportional-derivative (PD) adaptive impedance control strategy based on the position information is proposed, which can make the device more compliant, avoid secondary injuries caused by excessive muscle tension, and protect the fingers effectively. Finally, some preliminary experiments of the prototype are reported, and the results shows that the EFRR has good performance, which lays the foundation for future work.

Design, Modeling, and Evaluation of Fabric-Based Pneumatic Actuators for Soft Wearable Assistive Gloves

Textile fabrics are compliant, lightweight, and inherently anisotropic, making them promising for the design of soft pneumatic actuators. In this article, we present the design, modeling, and evaluation of a class of soft fabric-based pneumatic actuators (SFPAs) for soft wearable assistive gloves that can simultaneously assist the thumb abduction and finger flexion and extension motions for brachial plexus injury patients. We investigate the mechanical behaviors of various woven fabrics and rib weft-knitted fabric structures, guiding us to design a thumb-abduction SFPA, a finger-flexion SFPA, and a finger-extension SFPA. We further develop a mathematical model to evaluate the influence of the geometric parameters on the blocked tip forces of the finger-flexion SFPAs and extension torques of the finger-extension SFPAs, which are also verified by the experimental results. We then integrate our SFPAs into a soft wearable assistive glove with a portable control system. The glove is finally tested on a healthy volunteer and a brachial plexus injury patient. The clinical evaluation results demonstrate the effectiveness of our designed glove in assisting hand motions and grasping tasks.

A Modular Hybrid Exoskeletal-Soft Glove for High Degree of Freedom Monitoring Capability

In this paper, we present a hybrid exoskeletal-soft glove for the application of on-axis angle sensors that can be placed close to the center of rotation of the digit joints. 3D printed exoskeletal digit segments that run medially on most digits connect to low friction bearings. Exoskeletal segments and bearings provide rigid fixation points for a variety of traditional angle sensors, while a combination of textile and rigid structure fixate exoskeletal digits to the digits and hand. Exoskeletal digits are designed modularly so that only required digits are used and to reduce difficulty in donning and doffing. On-axis measurement may prove useful in control or assessment tasks in rehabilitation. The articulation of the digits while wearing the glove is demonstrated, albeit without sensors, showing little restriction at an early stage of the design process. Exoskeletal metacarpophalangeal joints of the 3rd and 4th digits require more work as the flexion/extension joint axis is inaccessible and moves when he digits are articulated. The proposed device must be customized for an individual and will facilitate an alternative approach to existing hand posture monitoring techniques.