Abstract
BackgroundTo effectively replace the human hand, a prosthesis should seamlessly respond to user intentions but also convey sensory information back to the user. Restoration of sensory feedback is rated highly by the prosthesis users, and feedback is critical for grasping in able-bodied subjects. Nonetheless, the benefits of feedback in prosthetics are still debated. The lack of consensus is likely due to the complex nature of sensory feedback during prosthesis control, so that its effectiveness depends on multiple factors (e.g., task complexity, user learning).MethodsWe evaluated the impact of these factors with a longitudinal assessment in six amputee subjects, using a clinical setup (socket, embedded control) and a range of tasks (box and blocks, block turn, clothespin and cups relocation). To provide feedback, we have proposed a novel vibrotactile stimulation scheme capable of transmitting multiple variables from a multifunction prosthesis. The subjects wore a bracelet with four by two uniformly placed vibro-tactors providing information on contact, prosthesis state (active function), and grasping force. The subjects also completed a questionnaire for the subjective evaluation of the feedback.ResultsThe tests demonstrated that feedback was beneficial only in the complex tasks (block turn, clothespin and cups relocation), and that the training had an important, task-dependent impact. In the clothespin relocation and block turn tasks, training allowed the subjects to establish successful feedforward control, and therefore, the feedback became redundant. In the cups relocation task, however, the subjects needed some training to learn how to properly exploit the feedback. The subjective evaluation of the feedback was consistently positive, regardless of the objective benefits. These results underline the multifaceted nature of closed-loop prosthesis control as, depending on the context, the same feedback interface can have different impact on performance. Finally, even if the closed-loop control does not improve the performance, it could be beneficial as it seems to improve the subjective experience.ConclusionsTherefore, in this study we demonstrate, for the first time, the relevance of an advanced, multi-variable feedback interface for dexterous, multi-functional prosthesis control in a clinically relevant setting.
Highlights
To effectively replace the human hand, a prosthesis should seamlessly respond to user intentions and convey sensory information back to the user
The time to complete the task was significantly lower in the FB condition compared to No Feedback (NFB) condition in the first session for Block Turn (TURN, 9 s faster, p = 0.031) and Clothespin Relocation Task (PIN, 33 s faster, p = 0.031) as well as in the last session for Cups Relocation Task (CUP, 9 s faster, p = 0.031)
In all these cases, the run completion time decreased without a significant increase in the number of retries, i.e., there was no significant difference in retries between FB and NFB and, the retries decreased in most cases
Summary
To effectively replace the human hand, a prosthesis should seamlessly respond to user intentions and convey sensory information back to the user. The human hands are an essential and sophisticated instrument for stable grasping, dexterous manipulation, haptic exploration as well as social contact and communication. These functions are possible thanks to a rich network of feedforward (motor) and feedback (sensory) pathways connecting the brain and the hand. To restore the missing functions, patients are often equipped with myoelectric prostheses, which aim at replacing the human hand morphologically and functionally. Such prostheses are controlled by translating muscle signals, e.g., the contraction of wrist flexors and extensors, into closing and opening of the prosthetic hand. While state-of-the-art (SoA) commercial myoelectric prostheses do provide control of a dexterous, multi degrees of freedom (DoF) hand, thereby restoring the motor function, an effective method to provide sensory feedback is still missing [1,2,3]
Published Version
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