Patients suffering from loss of hand functions caused by stroke and other spinal cord injuries have driven a surge in the development of wearable assistive devices in recent years. In this paper, we present a system made up of a low-profile, optimally designed finger exoskeleton continuously controlled by a user's surface electromyographic (sEMG) signals. The mechanical design is based on an optimal four-bar linkage that can model the finger's irregular trajectory due to the finger's varying lengths and changing instantaneous center. The desired joint angle positions are given by the predictive output of an artificial neural network with an EMG-to-Muscle Activation model that parameterizes electromechanical delay (EMD). After confirming good prediction accuracy of multiple finger joint angles we evaluated an index finger exoskeleton by obtaining a subject's EMG signals from the left forearm and using the signal to actuate a finger on the right hand with the exoskeleton. Our results show that our sEMG-based control strategy worked well in controlling the exoskeleton, obtaining the intended positions of the device, and that the subject felt the appropriate motion support from the device.
SUMMARYThe combined motion of the human thumb, index and middle fingers while rotating a small object across the extended, intermediate and flexed planes with respect to the fingers was analyzed. Auto reflective markers were attached on the fingers to track their motion across three postures and planes via a 3D motion capture system. Central, right and left rotation postures were considered in each plane for investigation and the rotation experiments were performed with 30 healthy subjects. The obtained data were used to compute the finger joint angles. Based on the three criteria of (i) manipulability measure, (ii) major axis direction angle of the manipulability ellipsoid and (iii) ratio of the minor over major axis lengths, the collective behavior of the fingers was studied. It has been found after analysis that the thumb and middle finger were active, while the index finger operated passively when manipulating small objects in cooperative rotational motion across the three planes. Activeness refers to the independence of a digit in controlling the motion of an object whereas passiveness denotes its dependence on other digits. An active finger governs the motion of an object whereas a passive finger simply supports it. The results of this investigation are of great importance in planning treatment for rehabilitation and for designing controllers for robotic therapists, finger exoskeletons and prostheses.
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