Ard Westerveld

Selectivity and Resolution of Surface Electrical Stimulation for Grasp and Release

Electrical stimulation of arm and hand muscles can be a functional tool for patients with motor dysfunction. Sufficient stimulation of finger and thumb musculature can support natural grasping function. Yet it remains unclear how different grasping movements can be selectively supported by electrical stimulation. The goal of this study is to determine to what extent activation of individual fingers is possible with surface electrical stimulation for the purpose of rehabilitation following stroke. The extensor digitorum communis (EDC) muscle, flexor pollicis longus (FPL) muscle, and the thenar muscle group, all involved in grasp and release, were selected for stimulation. The evoked forces in individual fingers were measured. Stimulation thresholds and selective ranges were determined for each subject. Electrode locations where the highest selective range occurred were compared between subjects and influences of different isometric wrist positions were assessed. In all subjects selective stimulation of middle finger extension and thumb flexion was possible. In addition, selective stimulation of index and ring finger extension was possible in most cases. In nine out of the ten EDC subjects we were able to stimulate three or all four fingers selectively. However, large variability in electrode locations for high selectivity was observed between the subjects. Within the designs of grasping prostheses and grasping rehabilitation devices, the variability of electrode locations should be taken into account. The results of our study facilitate the optimization of such designs and favour a design which allows individualized stimulation locations.

A Damper Driven Robotic End-Point Manipulator for Functional Rehabilitation Exercises After Stroke

Stroke survivors may benefit from robotic assistance for relearning of functional movements. Current assistive devices are either passive, limited to only two dimensions or very powerful. However, for reach training, weight compensation and a little assistance with limited power is sufficient. We designed and evaluated a novel three-dimensional robotic manipulator, which is able to support the arm weight and assist functional reaching movements. Key points of the design are a damper-based drive train, giving an inherently safe system and its compact and lightweight design. The system is force actuated with a bandwidth of up to 2.3 Hz, which is sufficient for functional arm movements. Maximal assistive forces are 15 N for the up/down and forward/backward directions and 10 N for the left/right direction. Force tracking errors are smaller than 1.5 N for all axes and the total weight of the robot is 25 kg. Furthermore, the device has shown its benefit for increasing reaching distance in a single-case study with a stroke subject. The newly developed system has the technical ability to assist the arm during movement, which is a prerequisite for successful training of stroke survivors. Therapeutic effects of the applied assistance need to be further evaluated. However, with its inherent safety and ease of use, this newly developed system even has the potential for home-based therapeutic training after stroke.

Design of a self-aligning 3-DOF actuated exoskeleton for diagnosis and training of wrist and forearm after stroke

Rehabilitation robotics provides a means of objectively quantifying patient condition before, during and after treatment. This paper describes the design and preliminary validation results of a novel rehabilitation device for the human wrist and forearm. The design features two key aspects: 1) it performs dynamical self-alignment to compensate for misalignment of the human limb and 2) it assists movements within almost the full natural range of motion. Self-alignment is performed by a linkage of parallelograms that allows torque-driven actuation. Advantages are decreased user-device interaction forces and lower don/doff-and setup-times. The full natural range of motion in Flexion/Extension, Radial/Ulnar-deviation and Pronation/Supination allows patients to perform ADL-like exercises during training. Furthermore, in the current design the hand and fingers remain free to perform grabbing activities and the open structure provides simple connection to the patients limb.

Grasp and release with surface functional electrical stimulation using a Model Predictive Control approach

Stroke often has a disabling effect on the ability to use the hand in a functional manner. Accurate finger and thumb positioning is necessary for many activities of daily living. In the current study, the feasibility of novel FES based approaches for positioning the thumb and fingers for grasp and release of differently sized objects is evaluated. Assistance based on these approaches may be used in rehabilitation of grasp and release after stroke.

Control of thumb force using surface functional electrical stimulation and muscle load sharing

BackgroundStroke survivors often have difficulties in manipulating objects with their affected hand. Thumb control plays an important role in object manipulation. Surface functional electrical stimulation (FES) can assist movement. We aim to control the 2D thumb force by predicting the sum of individual muscle forces, described by a sigmoidal muscle recruitment curve and a single force direction.MethodsFive able bodied subjects and five stroke subjects were strapped in a custom built setup. The forces perpendicular to the thumb in response to FES applied to three thumb muscles were measured. We evaluated the feasibility of using recruitment curve based force vector maps in predicting output forces. In addition, we developed a closed loop force controller. Load sharing between the three muscles was used to solve the redundancy problem having three actuators to control forces in two dimensions. The thumb force was controlled towards target forces of 0.5 N and 1.0 N in multiple directions within the individual’s thumb work space. Hereby, the possibilities to use these force vector maps and the load sharing approach in feed forward and feedback force control were explored.ResultsThe force vector prediction of the obtained model had small RMS errors with respect to the actual measured force vectors (0.22±0.17 N for the healthy subjects; 0.17±0.13 N for the stroke subjects). The stroke subjects showed a limited work range due to limited force production of the individual muscles. Performance of feed forward control without feedback, was better in healthy subjects than in stroke subjects. However, when feedback control was added performances were similar between the two groups. Feedback force control lead, especially for the stroke subjects, to a reduction in stationary errors, which improved performance.ConclusionsThumb muscle responses to FES can be described by a single force direction and a sigmoidal recruitment curve. Force in desired direction can be generated through load sharing among redundant muscles. The force vector maps are subject specific and also suitable in feedforward and feedback control taking the individual’s available workspace into account. With feedback, more accurate control of muscle force can be achieved.

Passive reach and grasp with functional electrical stimulation and robotic arm support

Rehabilitation of arm and hand function is crucial to increase functional independence of stroke subjects. Here, we investigate the technical feasibility of an integrated training system combining robotics and functional electrical stimulation (FES) to support reach and grasp during functional manipulation of objects. To support grasp and release, FES controlled the thumb and fingers using Model Predictive Control (MPC), while a novel 3D robotic manipulator provided reach support. The systems performance was assessed in both stroke and blindfolded healthy subjects, where the subjects passive arm and hand made functional reach, grasp, move and release movements while manipulating objects. The success rate of complete grasp, move and release tasks with different objects ranged from 33% to 87% in healthy subjects. In severe chronic stroke subjects especially the hand opening had a low success rate (<;25%) and no complete movements could be made. We demonstrated that our developed integrated training system can move the passive arm and hand for functional pick and place movements. In the current setup, the positioning accuracy of the robot with respect to the object position was critical for the overall performance. The use of a higher virtual stiffness and including feedback of object position in the robot control would likely improve the relative position accuracy. The system has potential for post-stroke rehabilitation, where support could be reduced based on patient performance which is needed to aid motor relearning of reach, grasp and release.