Use of an electromyographically driven hand orthosis for training after stroke

Design and experimental testing of a force-augmenting exoskeleton for the human hand

Background

Many older Americans suffer from long-term upper limb dysfunction, decreased grip strength, and/or a reduced ability to hold objects due to injuries and a variety of age-related illnesses. The objective of this study was to design and build a five-fingered powered assistive exoskeleton for the human hand, and to validate its ability to augment the gripping and pinching efforts of the wearer and assist in performing ADLs.

Methods

The exoskeleton device was designed using CAD software and 3-D printed in ABS. Each finger’s movement efforts were individually monitored by a force sensing resistor at each fingertip, and proportionally augmented via the microcontroller-based control scheme, linear actuators, and rigid exoskeleton structure. The force production of the device and the force augmenting capability were assessed on ten healthy individuals with one 5-digit grasping test, three pinching tests, and two functional tests.

Results

Use of the device significantly decreased the forearm muscle activity necessary to maintain a grasping effort (67%, p < 0.001), the larger of two pinching efforts (30%, p < 0.05), and the palmer pinching effort (67%, p < 0.001); however, no benefit by wearing the device was identified while maintaining a minimal pinching effort or attempting one of the functional tests.

Conclusion

The exoskeleton device allowed subjects to maintain independent control of each digit, and while wearing the exoskeleton, in both the unpowered and powered states, subjects were able to grasp, hold, and move objects such as a water bottle, bag, smartphone, or dry-erase marker.

A Novel Point-in-Polygon-Based sEMG Classifier for Hand Exoskeleton Systems

In the early 2000s, data from the latest World Health Organization estimates paint a picture where one-seventh of the world population needs at least one assistive device. Fortunately, these years are also characterized by a marked technological drive which takes the name of the Fourth Industrial Revolution. In this terrain, robotics is making its way through more and more aspects of everyday life, and robotics-based assistance/rehabilitation is considered one of the most encouraging applications. Providing high-intensity rehabilitation sessions or home assistance through low-cost robotic devices can be indeed an effective solution to democratize services otherwise not accessible to everyone. However, the identification of an intuitive and reliable real-time control system does arise as one of the critical issues to unravel for this technology in order to land in homes or clinics. Intention recognition techniques from surface ElectroMyoGraphic (sEMG) signals are referred to as one of the main ways-to-go in literature. Nevertheless, even if widely studied, the implementation of such procedures to real-case scenarios is still rarely addressed. In a previous work, the development and implementation of a novel sEMG-based classification strategy to control a fully-wearable Hand Exoskeleton System (HES) have been qualitatively assessed by the authors. This paper aims to furtherly demonstrate the validity of such a classification strategy by giving quantitative evidence about the favourable comparison to some of the standard machine-learning-based methods. Real-time action, computational lightness, and suitability to embedded electronics will emerge as the major characteristics of all the investigated techniques.

Investigating the performance of an amplitude-independent algorithm for detecting the hand muscle activity of stroke survivors

To make robotic hand devices controlled by surface electromyography (sEMG) signals feasible and practical tools for assisting patients with hand impairments, the problems that prevent these devices from being widely used have to be overcome. The most significant problem is the involuntary amplitude variation of the sEMG signals due to the movement of electrodes during forearm motion. Moreover, for patients who have had a stroke or another neurological disease, the muscle activity of the impaired hand is weak and has a low signal-to-noise ratio (SNR). Thus, muscle activity detection methods intended for controlling robotic hand devices should not depend mainly on the amplitude characteristics of the sEMG signal in the detection process, and they need to be more reliable for sEMG signals that have a low SNR. Since amplitude-independent muscle activity detection methods meet these requirements, this paper investigates the performance of such a method on people who have had a stroke in terms of the detection of weak muscle activity and resistance to false alarms caused by the involuntary amplitude variation of sEMG signals; these two parameters are very important for achieving the reliable control of robotic hand devices intended for people with disabilities. A comparison between the performance of an amplitude-independent muscle activity detection algorithm and three amplitude-dependent algorithms was conducted by using sEMG signals recorded from six hemiparesis stroke survivors and from six healthy subjects. The results showed that the amplitude-independent algorithm performed better in terms of detecting weak muscle activity and resisting false alarms.

Moving toward Soft Robotics: A Decade Review of the Design of Hand Exoskeletons

Soft robotics is a branch of robotics that deals with mechatronics and electromechanical systems primarily made of soft materials. This paper presents a summary of a chronicle study of various soft robotic hand exoskeletons, with different electroencephalography (EEG)- and electromyography (EMG)-based instrumentations and controls, for rehabilitation and assistance in activities of daily living. A total of 45 soft robotic hand exoskeletons are reviewed. The study follows two methodological frameworks: a systematic review and a chronological review of the exoskeletons. The first approach summarizes the designs of different soft robotic hand exoskeletons based on their mechanical, electrical and functional attributes, including the degree of freedom, number of fingers, force transmission, actuation mode and control strategy. The second approach discusses the technological trend of soft robotic hand exoskeletons in the past decade. The timeline analysis demonstrates the transformation of the exoskeletons from rigid ferrous materials to soft elastomeric materials. It uncovers recent research, development and integration of their mechanical and electrical components. It also approximates the future of the soft robotic hand exoskeletons and some of their crucial design attributes.

Soft robotic devices for hand rehabilitation and assistance: a narrative review

INTRODUCTION

The debilitating effects on hand function from a number of a neurologic disorders has given rise to the development of rehabilitative robotic devices aimed at restoring hand function in these patients. To combat the shortcomings of previous traditional robotics, soft robotics are rapidly emerging as an alternative due to their inherent safety, less complex designs, and increased potential for portability and efficacy. While several groups have begun designing devices, there are few devices that have progressed enough to provide clinical evidence of their design's therapeutic abilities. Therefore, a global review of devices that have been previously attempted could facilitate the development of new and improved devices in the next step towards obtaining clinical proof of the rehabilitative effects of soft robotics in hand dysfunction.

METHODS

A literature search was performed in SportDiscus, Pubmed, Scopus, and Web of Science for articles related to the design of soft robotic devices for hand rehabilitation. A framework of the key design elements of the devices was developed to ease the comparison of the various approaches to building them. This framework includes an analysis of the trends in portability, safety features, user intent detection methods, actuation systems, total DOF, number of independent actuators, device weight, evaluation metrics, and modes of rehabilitation.

RESULTS

In this study, a total of 62 articles representing 44 unique devices were identified and summarized according to the framework we developed to compare different design aspects. By far, the most common type of device was that which used a pneumatic actuator to guide finger flexion/extension. However, the remainder of our framework elements yielded more heterogeneous results. Consequently, those results are summarized and the advantages and disadvantages of many design choices as well as their rationales were highlighted.

CONCLUSION

The past 3 years has seen a rapid increase in the development of soft robotic devices for hand rehabilitative applications. These mostly preclinical research prototypes display a wide range of technical solutions which have been highlighted in the framework developed in this analysis. More work needs to be done in actuator design, safety, and implementation in order for these devices to progress to clinical trials. It is our goal that this review will guide future developers through the various design considerations in order to develop better devices for patients with hand impairments.

EMG pattern classification to control a hand orthosis for functional grasp assistance after stroke

Wearable orthoses can function both as assistive devices, which allow the user to live independently, and as rehabilitation devices, which allow the user to regain use of an impaired limb. To be fully wearable, such devices must have intuitive controls, and to improve quality of life, the device should enable the user to perform Activities of Daily Living. In this context, we explore the feasibility of using electromyography (EMG) signals to control a wearable exotendon device to enable pick and place tasks. We use an easy to don, commodity forearm EMG band with 8 sensors to create an EMG pattern classification control for an exotendon device. With this control, we are able to detect a user's intent to open, and can thus enable extension and pick and place tasks. In experiments with stroke survivors, we explore the accuracy of this control in both non-functional and functional tasks. Our results support the feasibility of developing wearable devices with intuitive controls which provide a functional context for rehabilitation.

A structured overview of trends and technologies used in dynamic hand orthoses

The development of dynamic hand orthoses is a fast-growing field of research and has resulted in many different devices. A large and diverse solution space is formed by the various mechatronic components which are used in these devices. They are the result of making complex design choices within the constraints imposed by the application, the environment and the patient's individual needs. Several review studies exist that cover the details of specific disciplines which play a part in the developmental cycle. However, a general collection of all endeavors around the world and a structured overview of the solution space which integrates these disciplines is missing. In this study, a total of 165 individual dynamic hand orthoses were collected and their mechatronic components were categorized into a framework with a signal, energy and mechanical domain. Its hierarchical structure allows it to reach out towards the different disciplines while connecting them with common properties. Additionally, available arguments behind design choices were collected and related to the trends in the solution space. As a result, a comprehensive overview of the used mechatronic components in dynamic hand orthoses is presented.

Design and fabrication of a three dimensional printable non-assembly articulated hand exoskeleton for rehabilitation

Robotic rehabilitation has proven to be cost-effective in accelerating the rehabilitation process by eliminating the constant need for supervision by a therapist. This work aimed to design and develop a novel three-dimensional (3D) printable non-assembly five-fingered robotic hand exoskeleton for rehabilitation. A single degree-of-freedom (DOF) linkage was designed to actuate each finger with 3 output links that correspond to the three phalanxes of the human finger. We used a parametric modelling approach that suits the dimensions of individual's hand. The fabrication of this dynamic model was achieved by printing the complete assembly including all the driving links, output links, and joints. We manufactured a prototype and developed real-time actuation and control. The reported unique linkage design, combined with parametric modelling and 3D printing technology, will pave the way for mass customization of active assistive and resistive hand exoskeletons.