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1. Wrist speed feedback improves elbow compensation and reaching accuracy for myoelectric transradial prosthesis users in hybrid virtual reaching task

   https://doi.org/10.1186/s12984-023-01138-3  

   Earley, Eric J. ; Johnson, Reva E. ; Sensinger, Jonathon W. ; Hargrove, Levi J. ( January 2023 , Journal of NeuroEngineering and Rehabilitation)

   Myoelectric prostheses are a popular choice for restoring motor capability following the loss of a limb, but they do not provide direct feedback to the user about the movements of the device—in other words, kinesthesia. The outcomes of studies providing artificial sensory feedback are often influenced by the availability of incidental feedback. When subjects are blindfolded and disconnected from the prosthesis, artificial sensory feedback consistently improves control; however, when subjects wear a prosthesis and can see the task, benefits often deteriorate or become inconsistent. We theorize that providing artificial sensory feedback about prosthesis speed, which cannot be precisely estimated via vision, will improve the learning and control of a myoelectric prosthesis.

   In this study, we test a joint-speed feedback system with six transradial amputee subjects to evaluate how it affects myoelectric control and adaptation behavior during a virtual reaching task.

   Our results showed that joint-speed feedback lowered reaching errors and compensatory movements during steady-state reaches. However, the same feedback provided no improvement when control was perturbed.

   These outcomes suggest that the benefit of joint speed feedback may be dependent on the complexity of the myoelectric control and the context of the task.

    

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2. Neuromorphic vision and tactile fusion for upper limb prosthesis control

   https://doi.org/10.1109/NER.2019.8716890  

   Hays, Mark ; Osborn, Luke ; Ghosh, Rohan ; Iskarous, Mark ; Hunt, Christopher ; Thakor, Nitish V. ( March 2019 , IEEE Transactions on Biomedical Circuits and Systems)

   null (Ed.)

   A major issue with upper limb prostheses is the disconnect between sensory information perceived by the user and the information perceived by the prosthesis. Advances in prosthetic technology introduced tactile information for monitoring grasping activity, but visual information, a vital component in the human sensory system, is still not fully utilized as a form of feedback to the prosthesis. For able-bodied individuals, many of the decisions for grasping or manipulating an object, such as hand orientation and aperture, are made based on visual information before contact with the object. We show that inclusion of neuromorphic visual information, combined with tactile feedback, improves the ability and efficiency of both able-bodied and amputee subjects to pick up and manipulate everyday objects.We discovered that combining both visual and tactile information in a real-time closed loop feedback strategy generally decreased the completion time of a task involving picking up and manipulating objects compared to using a single modality for feedback. While the full benefit of the combined feedback was partially obscured by experimental inaccuracies of the visual classification system, we demonstrate that this fusion of neuromorphic signals from visual and tactile sensors can provide valuable feedback to a prosthetic arm for enhancing real-time function and usability. 

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3. Biomimetic sensory feedback through peripheral nerve stimulation improves dexterous use of a bionic hand

   https://doi.org/10.1126/scirobotics.aax2352  

   George, J. A. ; Kluger, D. T. ; Davis, T. S. ; Wendelken, S. M. ; Okorokova, E. V. ; He, Q. ; Duncan, C. C. ; Hutchinson, D. T. ; Thumser, Z. C. ; Beckler, D. T. ; et al ( July 2019 , Science Robotics)

   We describe use of a bidirectional neuromyoelectric prosthetic hand that conveys biomimetic sensory feedback. Electromyographic recordings from residual arm muscles were decoded to provide independent and proportional control of a six-DOF prosthetic hand and wrist—the DEKA LUKE arm. Activation of contact sensors on the prosthesis resulted in intraneural microstimulation of residual sensory nerve fibers through chronically implanted Utah Slanted Electrode Arrays, thereby evoking tactile percepts on the phantom hand. With sensory feedback enabled, the participant exhibited greater precision in grip force and was better able to handle fragile objects. With active exploration, the participant was also able to distinguish between small and large objects and between soft and hard ones. When the sensory feedback was biomimetic—designed to mimic natural sensory signals—the participant was able to identify the objects significantly faster than with the use of traditional encoding algorithms that depended on only the present stimulus intensity. Thus, artificial touch can be sculpted by patterning the sensory feedback, and biologically inspired patterns elicit more interpretable and useful percepts. 

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4. Haptic shared control improves neural efficiency during myoelectric prosthesis use

   https://doi.org/10.1038/s41598-022-26673-2  

   Thomas, Neha ; Miller, Alexandra J. ; Ayaz, Hasan ; Brown, Jeremy D. ( January 2023 , Scientific Reports)

   Clinical myoelectric prostheses lack the sensory feedback and sufficient dexterity required to complete activities of daily living efficiently and accurately. Providing haptic feedback of relevant environmental cues to the user or imbuing the prosthesis with autonomous control authority have been separately shown to improve prosthesis utility. Few studies, however, have investigated the effect of combining these two approaches in a shared control paradigm, and none have evaluated such an approach from the perspective of neural efficiency (the relationship between task performance and mental effort measured directly from the brain). In this work, we analyzed the neural efficiency of 30 non-amputee participants in a grasp-and-lift task of a brittle object. Here, a myoelectric prosthesis featuring vibrotactile feedback of grip force and autonomous control of grasping was compared with a standard myoelectric prosthesis with and without vibrotactile feedback. As a measure of mental effort, we captured the prefrontal cortex activity changes using functional near infrared spectroscopy during the experiment. It was expected that the prosthesis with haptic shared control would improve both task performance and mental effort compared to the standard prosthesis. Results showed that only the haptic shared control system enabled users to achieve high neural efficiency, and that vibrotactile feedback was important for grasping with the appropriate grip force. These results indicate that the haptic shared control system synergistically combines the benefits of haptic feedback and autonomous controllers, and is well-poised to inform such hybrid advancements in myoelectric prosthesis technology.

    

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5. Reinforcement-Learning-Based Risk-Sensitive Optimal Feedback Mechanisms of Biological Motor Control

   https://doi.org/10.1109/CDC49753.2023.10384286  

   Cui, Leilei ; Pang, Bo ; Jiang, Zhong-Ping ( December 2023 , IEEE)

   Risk sensitivity is a fundamental aspect of biological motor control that accounts for both the expectation and variability of movement cost in the face of uncertainty. However, most computational models of biological motor control rely on model-based risk-sensitive optimal control, which requires an accurate internal representation in the central neural system to predict the outcomes of motor commands. In reality, the dynamics of human-environment interaction is too complex to be accurately modeled, and noise further complicates system identification. To address this issue, this paper proposes a novel risk-sensitive computational mechanism for biological motor control based on reinforcement learning (RL) and adaptive dynamic programming (ADP). The proposed ADP-based mechanism suggests that humans can directly learn an approximation of the risk-sensitive optimal feedback controller from noisy sensory data without the need for system identification. Numerical validation of the proposed mechanism is conducted on the arm-reaching task under divergent force field. The preliminary computational results align with the experimental observations from the past literature of computational neuroscience. 

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