Introduction
A wide diversity of robotic devices, which can actuate/assist the movements of the human hand, can be found in the current scientific literature.1 Depending on the application, a hand exoskeleton may require uneven features. For example, a rehabilitation-aimed exoskeleton needs to be fairly backdrivable and allows a wide range of movement, so it is flexible enough to perform different rehabilitation exercises.2 In contrast, an assistance exoskeleton must be stiff enough to ensure a firm grasping of objects present during activities of daily living and can sacrifice flexibility of movement in favor of predefined grasping patterns.
These different requirements result on diverse force transmission architectures:
- Some devices use linkages in order to transmit the force from the actuator to the human joints.3–5 This is a stiff architecture that requires a proper alignment between kinematic centers of the linkage and human joints, but allows a good control of the hand pose. Due to the flexibility of the design, with the correct sizing, these mechanisms can achieve complex movement patterns with simple actuators.
- Another extended architecture is the cable-driven glove.6–8 These are more flexible and simpler alternatives that rely on the own human joints to direct the movement, so they are less prone to uncomfortable poses. In contrast, they require pulleys to achieve high forces and are harder to control in intermediate positions. Additionally, this kind of exoskeletons need a pair of cables in antagonist configuration in order to assist both extension and flexion movements.
- Finally, some devices use deformable actuators, like pneumatic muscles or shape-memory alloys, attached directly to the hand by means of a glove.9,10 They result in very light and simple devices, but actuators are not placed in the most advantageous place to achieve great forces.
Regarding the exoskeletons based on linkages, especially those which rely on electric actuators, having a measurement of the interaction force between user and device may result an interesting feature in order to ease control tasks and improve safety. In certain devices, different sensor technologies have been implemented, such as torque sensors,11 strain gauges,12 flexion sensors,13 and miniature load cells.14 These sensors may be effective in their respective applications but present some shortcomings for their integration in exoskeletons. In particular, torque sensors measure loads in the motor shaft so, in over-constrained mechanisms, they might not measure all the interaction forces. Strain gauges are complex to fix in the proper place and shorter ones may not perform correctly, so for being usable they require geometries with size comparable to human phalanxes. Another miniature sensors, like load cells or force-sensitive resistors, normally can measure force in only one sense (compression or extension) and those that can measure both directions are too big for the scale of the human hand.
In our previous paper,15 we studied the feasibility of using multimodal systems in order to assist post-stroke patients during the execution of rehabilitation therapies with real objects. In this context, we evaluated the suitability of using a hand exoskeleton device,16 such as the aforementioned ones, for assisting an impaired person during the grasping of objects present in activities of daily living. This device has experienced substantial improvements with respect to the previous design in order to be able to interact safely with disabled users.
In that previous experimentation, the electromyographic (EMG) signal of the forearm muscles was proposed as a method to estimate user’s intention and consequently trigger the open/close movement of the hand exoskeleton. This method proved to be effective, but it can be used only for users with a coherent and relatively strong EMG signal, which might not be the case for most patients.17 From these results, there is a need for additional technologies that can detect the movement intention of the subject in order to cope with a wider range of user profiles.
Despite that the presented device will also be used in assistive context, the objective of the exposed research is to show whether the proposed improvements of the hand exoskeleton, including a miniature optical force sensor, allow its use in a real rehabilitation environment. Special attention will be given to the development of a force sensing method in order to measure the human–robot interaction forces and therefore to estimate user’s intention in rehabilitation scenarios.
Hardware description
Among the different existing architectures, we have decided to implement an exoskeleton based on the linkage approximation, since we consider that this is the most flexible solution in order to achieve a good compromise between the requirements of both rehabilitation and assistance scenarios. The motion transmission is based on a bar mechanism that allows the possibility of coupling the motion of phalanxes, so a natural hand movement is achievable using only one active degree of freedom per finger. Additionally, bars can transmit both tensile and compressive loads so the same mechanism is able to perform extension (most demanding movement in rehabilitation) and flexion (mandatory for assistance) movement of the fingers.
In detail, the designed exoskeleton is composed by three identical finger modules that drive index, middle and the pair formed by ring and little fingers. Each finger module has a single degree of freedom actively driven by a linear actuator. Unlike many of the referenced exoskeletons, due to the inherent uncertainty introduced by the human–exoskeleton interface (modeled as a slide along the phalanx longitudinal axis in Figure 1), we have decided not to rely on the human finger as the element that closes the kinematic chain. Conversely, we have adopted an approach similar to the one adopted by Ho et al.5 This way, adding a pair of circular guides whose centers are coincident with the joints of a reference finger, the mechanism is kinematically determinate without needing the human finger. Ho’s device uses slots with flange bearings to implement the guides; this may result effective but requires precision machining and miniature elements to achieve a compact solution. In contrast, we have designed a double-edged guide that slides between four V-shaped bearings (Figure 2). These elements allow the optimization of the required space and may be easily manufactured by prototyping technologies or plastic molding. To make up for the additional constraints, we have decided to actuate only medial and proximal phalanxes.
Figure 1. Kinematics scheme of the finger linkage attached to the human finger. Metacarpophalangeal (MCP), proximal interphalangeal (PIP), and distal interphalangeal (DIP) joints have been modeled as revolute joints. Additionally, the interface between the module and the phalanxes has been modeled by means of slide.
Figure 2. Left: Finger module represented in its extreme positions. Right: Detailed view of the designed circular guide to minimize mechanical clearances with minimum friction.
TBI Rehabilitation 