An exoskeleton is defined as a distinctive kind of robot to be worn as an overall or frame, effectively supporting, or in some cases substituting for, the user’s own movements. Numerous hand exoskeletons have been proposed so far, but their technology readiness level has been limited . No doubt that only a few studies have been conducted to investigate, improve, and observe the effect of rehabilitation therapy using hand exoskeletons. The main limitation is the complex nature of hand movements – there is difficulty in installing plenty of sensors and actuators to the hand because of limited space around the fingers, taking into consideration finger flexion and extension, finger independence, and simultaneous multi-digit synergy within grasps as well as computational intelligence based algorithms to control, evaluate, and develop the aforementioned functions. Early solutions have been proposed by Kim et al.  and Zhang et al. . But no doubt hand exoskeleton should be personalized because of diverse antropometric and biomechanical features not only in healthy people but also in those with disease/injury that varies from patient to patient. Ergonomic constraints, workspace, workload, speed, etc., are also important. Another challenge constitutes activities requiring two hands, simultaneous mobility of the trunk or whole body, or even the use of any specialized tools (even such simple activities as locking the door using the key). Thus, the design of the three-dimensional (3D) printed hand exoskeleton seems to be the only reliable solution as the traditional development of the family of numerous prototypes progressively fitted to an individual person’s hand may be not possible, not even taking into consideration the cost-effect ratio .
In this paper a new 3D printed bydgostian hand exoskeleton is introduced and biomedically characterized.
Hand exoskeleton in rehabilitation
The hand exoskeleton constitutes a technical tool that expands and improves the selected functional abilities of the user’s hand. It also may serve as a multi-purpose medical device improving a patient’s function in a way closest to the natural hand mobility. As a 24/7 rehabilitation device, it may be more effective than traditional rehabilitation, and moreover, the partial effect may be observed immediately. Hand exoskeletons are progressively reaching various kinds and levels of deficits, allowing not only diagnosis and activity but also communication and control within the smart home and internet of things environments.
Human hands are very precise, complex, and versatile. There is a strong relationship between the hand function and the ability to perform activities of daily living.
Every deficit in hand function may significantly impact the health-related quality of life; thus, there are demands on the hand motor therapy, despite that its outcomes are limited because of low effectivity. Clinicians and scientists still look for novel, more effective therapeutic approaches, including assistive technology devices such as exoskeletons.
The limitation of the current therapeutic concepts lies partly in the fact that the hand has over 20 degrees of freedom, which makes it flexible, but there is a difficulty for engineers and therapists to meet the needs for training/supporting devices, including both the diversity of movements (directions, forces, and angles/ranges of motion) and its safety. Some problems may not be met elsewhere; e.g. a single finger can be flexibly controlled with four DOS, but various grasps may require diverse and complex joint coordination. Moreover, motor deficit may differ from person to person, and furthermore, patient’s health status and function may vary in the course of recovery. Thus, even the types of muscle state, phases of recovery (e.g. acute, subacute, or chronic), kinds and levels of impairment (from mild to severe), and multiple deficits co-existing simultaneously should all be taken into consideration for continuous planning of the individualized treatment (patient-tailored therapy) , .
There is an important fact that there seems to be a lot of neuroplastical reserve for both spontanic and controlled recovery of function: the area of sensory and motor cortex corresponding with the hand is much larger than the other motor cortex areas, associated with other limbs and body parts. Flexibility and power rely on generating a variety of hand movement patterns (see, e.g. piano or guitar chords) and in the control of the individual joints of the hand, including finger movements.
Robot-assisted therapy for neurorehabilitation purposes has been developed over the past three decades with the advances of exoskeletons and other robot-based devices supplementing traditional physical therapy. The aforementioned solutions may enrich the spectrum of the traditional repetitive exercises stimulating recovery, are more dexterous and precise in it, and can be controlled by the patients’ thanks to, e.g. the analysis of electromyographic signals. More advanced solutions can have advanced control systems based on biosignal analysis or even supported by computational intelligence systems, taking into consideration diverse factors such as motivation, mood, and possible depression , , . The main advantage of the aforementioned systems is not only increased efficacy in recovery but also improved possibility to transfer its outcomes to the normal life/environment, partly without further use of the assistive technology.
Current solutions concerning hand rehabilitation robotics seems to be insufficient, as they do not meet the requirements of the patients (including poststroke survivors). Even the most efficient robotic system only makes the foundation, which should be supported by the proper, flexible, and safe training paradigm – the functional part within the whole motor recovery strategy.
We should take into consideration that application of the hand exoskeleton may be both permanent and temporary (e.g. during recovery), and the area of particular risk is the application of this tool in children with developing hand function, where support has both advantages and disadvantages.
The described concept constitutes the next step of the previous research on the concept of 3D printed passive exoskeleton for children with weakness in upper limbs and its (separate) module concerning hand function.
Our exoskeleton is controlled by the user’s movements and does not need any external control terminal. Its main parts are as follows: the frame, the power system (engines, actuators, and batteries), and the control system (with sensors included). We started from passive exoskeleton and then develop it toward an active exoskeleton. Stages of the work were the following:
Detailed description of the hand anatomy and biomechanics, including experimental studies on healthy people and patients
Computational model of the hand of healthy people
Families of computational models of the hand with various kinds and levels of deficit (based on neurodegenerative disorders)
Construction of the hand exoskeleton based on own project
Creating digital template of the exoskeleton taking into consideration shape, dimensions, and angles of the both hands (left and right), handedness, kind and level of the deficit, and the other particular features within patient-tailored solutions
Creating real exoskeleton for the particular real patients
Testing the efficacy of the aforementioned exoskeleton
Testing if the kinematic chain of the exoskeleton added to the musculoskeletal models does not comply with the hand movements (e.g. influence fingers’ joints angles) .
Our studies on control systems concern adaptation of computational intelligence based technologies to the requirements of novel application: precise, smooth movements challenging in modeling and replication, based partially on pre-prepared templates, according to the possibilities and needs of the particular user, both healthy and with hand disorders. Our current research is focused on the following:
Procedure of hand(s) medical assessment toward indications and contraindications to hand exoskeleton application in the particular patient
Procedure of scanning and imaging toward description of the ability of the hand exoskeleton use (technical and biomechanical) and its technical parameters
Procedure of hand exoskeleton design based on pre-programmed patterns (Figure 1)
Objective assessment of efficacy of the hand exoskeleton in homogenous group of patients (cooperation to the Department of Physiotherapy, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, Poland)
Development of the whole family of solutions (templates) dedicated to the particular homogenous groups of patients (kinds and levels of deficit) .
The hand exoskeleton itself is composed of the digit-bar parts (three for each finger, but two for thumb) with sensors, motors, and loadcells for each finger providing ability to flex/extend the metacarpal and proximal interphalangeal joints independently. Moreover, each exoskeleton finger may be regarded as a mechanism composed of three joints in series. From a biomechanical point of view, the design of the hand exoskeleton is reasonable, and its kinematic analysis is correct (Figure 2 and Figure 3).
Despite many studies concerning hand exoskeleton, only a few presents similar approach. A study by Burns et al. on 3D printed soft hand exoskeleton named HEXOES (Hand Exoskeleton with Embedded Synergies) showed that the mechanical design has ROM and angular velocity meeting requirements for synergy-based control . In the study by Kim et al., a hand exoskeleton was developed to satisfy the requirements for evaluating the hand functions including spasticity of finger flexors, finger independence, and multi-digit synergy . The exoskeleton design should be an iterative process, taking into consideration the user perspective , . Ngeo et al. proposed finger exoskeleton continuously controlled by a user’s surface electromyographic signals. The aforementioned approach obtains the intended positions of the device, and the subject feels the appropriate motion support from the device . Diversity of solutions is high: even up to 165 individual dynamic hand orthoses were identified, and their mechatronic components were categorized depending on signal, energy, and mechanics , as well as training paradigm , high intensity, long-duration targeted therapeutic interventions , even the modification of pathological patterns of coordination of the upper limb , and the improvement of movement smoothness over the course of the therapy. To unify the description of such phenomena, the Standardization and Terminology Committee of the International Society of Biomechanics proposed the definition of a joint coordinate system for shoulder, elbow, wrist, and hand . Three-dimensional reaching is described by many arm motion parameters including global hand position or velocity, joint angles, joint angular velocities, and joint torques or muscle activations, taking into consideration intrinsic, extrinsic, kinematic, and kinetic variables .
Similar to our mathematical model of the human, the upper limb was developed based on high-resolution medical images of the muscles and bones obtained from the Visible Human Male project, including the following:
The 3D surfaces of the muscles and bones were reconstructed using computed tomography images, and color cryosection images were obtained from the Visible Human Male project cadaver
A total of 13 degrees of freedom were used to describe the orientations of seven bones in the model: clavicle, scapula, humerus, radius, ulna, carpal bones, and hand
The model was actuated by 42 muscle bundles, which represented the actions of the 26 muscle groups in the upper limb
The paths of the muscles were modeled using a new approach called the Obstacle-Set Method .
The hand exoskeleton should meet the requirements for both active and passive rehabilitation motions for the thumb and all fingers . Wrist movements are essential for increased hand usefulness but do not influence the grasps itself, because functional hand use is not the same as the grasp only (see, e.g. graphomotoric abilities). Bi-directional movement for all joints of the finger with four degrees of freedom seems be the basis for further development of hand exoskeleton kinematics. Exact kinematic relation between the exoskeleton joint angles and the corresponding finger joint angles simplifies the high level motion control, but ROM may change along with the rehabilitation progress . Movement variability and its time course are a key process to understand the principles of hand exoskeleton control, especially in the area of repetitive handling . However, we should be aware that generally the evaluation of the upper limb joint function may be performed without the use of specialized tools , .
The main limitations of this research constitute the following:
The limited number of patients’ diseases and associated hand function deficits assessed and modeled so far
The preliminary phase of research on flexible procedures of modeling, taking into consideration many clinical and biomechanical factors
The preliminary phase of research on mechanical and material properties of hand exoskeleton
Thus, we regard our study as preliminary. The main directions for further studies are as follows:
Ultimate procedures of 3D hand scanning, data gathering, processing and analysis, and turning it into preset patterns of exoskeleton
Providing a version that is ready to commercialization, characterized by high level of the technological readiness
Providing highly efficient therapy support with repetitive success ratio
Taking into consideration individual factors such as various function of the left and right hands in selected activities
The proposed concept is promising, and the described approach combining biomechanical factors and 3D modeling driven by detailed hand exoskeleton patterns may constitute a key future method of ergonomic hand exoskeleton design and validation prior to manufacturing.
Despite the aforementioned approach, we should be aware that the hand exoskeleton constitutes hand support and rehabilitation robot system developing with the user; thus, certain coordination and continuity of the “hardware” part of the whole system and the training paradigm are essential for therapy efficacy.
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About the article
Published Online: 2019-03-22
Ethical Approval: The conducted research is not related to either human or animal use.
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: None declared.
Employment or leadership: None declared.
Honorarium: None declared.
Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.