We have developed a one-of-a-kind hand exoskeleton, called Maestro, which can power finger movements of those surviving severe disabilities to complete daily tasks using compliant joints. In this paper, we present results from an electromyography (EMG) control strategy conducted with spinal cord injury (SCI) patients (C5, C6, and C7) in which the subjects completed daily tasks controlling Maestro with EMG signals from their forearm muscles. With its compliant actuation and its degrees of freedom that match the natural finger movements, Maestro is capable of helping the subjects grasp and manipulate a variety of daily objects (more than 15 from a standardized set). To generate control commands for Maestro, an artificial neural network algorithm was implemented along with a probabilistic control approach to classify and deliver four hand poses robustly with three EMG signals measured from the forearm and palm. Increase in the scores of a standardized test, called the Sollerman hand function test, and enhancement in different aspects of grasping such as strength shows feasibility that Maestro can be capable of improving the hand function of SCI subjects.

In accordance with strict requirements of portability, cheapness, and modularity, an innovative assistive device for hand disabilities has been developed and validated. This robotic orthosis is designed to be a low-cost, portable hand exoskeleton to assist people with physical disabilities in their everyday lives. Referring to hand opening disabilities, the authors have developed a methodology which, by starting from the geometrical characteristics of the patient's hand, defines the novel kinematic mechanism that better fits to the finger trajectories. The authors have validated the proposed novel mechanism by carrying out a Hand Exoskeleton System (HES) prototype, based on a single-phalanx mechanism, cable driven. The testing phase of the real prototype with a patient is currently on going.