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1. Joint Speed Discrimination and Augmentation For Prosthesis Feedback

   https://doi.org/10.1038/s41598-018-36126-4  

   Earley, Eric J. ; Johnson, Reva E. ; Hargrove, Levi J. ; Sensinger, Jon W. ( December 2018 , Scientific Reports)

   Sensory feedback is critical in fine motor control, learning, and adaptation. However, robotic prosthetic limbs currently lack the feedback segment of the communication loop between user and device. Sensory substitution feedback can close this gap, but sometimes this improvement only persists when users cannot see their prosthesis, suggesting the provided feedback is redundant with vision. Thus, given the choice, users rely on vision over artificial feedback. To effectively augment vision, sensory feedback must provide information that vision cannot provide or provides poorly. Although vision is known to be less precise at estimating speed than position, no work has compared speed precision of biomimetic arm movements. In this study, we investigated the uncertainty of visual speed estimates as defined by different virtual arm movements. We found that uncertainty was greatest for visual estimates of joint speeds, compared to absolute rotational or linear endpoint speeds. Furthermore, this uncertainty increased when the joint reference frame speed varied over time, potentially caused by an overestimation of joint speed. Finally, we demonstrate a joint-based sensory substitution feedback paradigm capable of significantly reducing joint speed uncertainty when paired with vision. Ultimately, this work may lead to improved prosthesis control and capacity for motor learning.

    

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2. 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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3. A neuromuscular model of human locomotion combines spinal reflex circuits with voluntary movements

   https://doi.org/10.1038/s41598-022-11102-1  

   Ramadan, Rachid ; Geyer, Hartmut ; Jeka, John ; Schöner, Gregor ; Reimann, Hendrik ( May 2022 , Scientific Reports)

   Existing models of human walking use low-level reflexes or neural oscillators to generate movement. While appropriate to generate the stable, rhythmic movement patterns of steady-state walking, these models lack the ability to change their movement patterns or spontaneously generate new movements in the specific, goal-directed way characteristic of voluntary movements. Here we present a neuromuscular model of human locomotion that bridges this gap and combines the ability to execute goal directed movements with the generation of stable, rhythmic movement patterns that are required for robust locomotion. The model represents goals for voluntary movements of the swing leg on the task level of swing leg joint kinematics. Smooth movements plans towards the goal configuration are generated on the task level and transformed into descending motor commands that execute the planned movements, using internal models. The movement goals and plans are updated in real time based on sensory feedback and task constraints. On the spinal level, the descending commands during the swing phase are integrated with a generic stretch reflex for each muscle. Stance leg control solely relies on dedicated spinal reflex pathways. Spinal reflexes stimulate Hill-type muscles that actuate a biomechanical model with eight internal joints and six free-body degrees of freedom. The model is able to generate voluntary, goal-directed reaching movements with the swing leg and combine multiple movements in a rhythmic sequence. During walking, the swing leg is moved in a goal-directed manner to a target that is updated in real-time based on sensory feedback to maintain upright balance, while the stance leg is stabilized by low-level reflexes and a behavioral organization switching between swing and stance control for each leg. With this combination of reflex-based stance leg and voluntary, goal-directed control of the swing leg, the model controller generates rhythmic, stable walking patterns in which the swing leg movement can be flexibly updated in real-time to step over or around obstacles.

    

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4. Using principles of motor control to analyze performance of human machine interfaces

   https://doi.org/10.1038/s41598-023-40446-5  

   Patwardhan, Shriniwas ; Gladhill, Keri Anne ; Joiner, Wilsaan M. ; Schofield, Jonathon S. ; Lee, Ben Seiyon ; Sikdar, Siddhartha ( August 2023 , Scientific Reports)

   There have been significant advances in biosignal extraction techniques to drive external biomechatronic devices or to use as inputs to sophisticated human machine interfaces. The control signals are typically derived from biological signals such as myoelectric measurements made either from the surface of the skin or subcutaneously. Other biosignal sensing modalities are emerging. With improvements in sensing modalities and control algorithms, it is becoming possible to robustly control the target position of an end-effector. It remains largely unknown to what extent these improvements can lead to naturalistic human-like movement. In this paper, we sought to answer this question. We utilized a sensing paradigm called sonomyography based on continuous ultrasound imaging of forearm muscles. Unlike myoelectric control strategies which measure electrical activation and use the extracted signals to determine the velocity of an end-effector; sonomyography measures muscle deformation directly with ultrasound and uses the extracted signals to proportionally control the position of an end-effector. Previously, we showed that users were able to accurately and precisely perform a virtual target acquisition task using sonomyography. In this work, we investigate the time course of the control trajectories derived from sonomyography. We show that the time course of the sonomyography-derived trajectories that users take to reach virtual targets reflect the trajectories shown to be typical for kinematic characteristics observed in biological limbs. Specifically, during a target acquisition task, the velocity profiles followed a minimum jerk trajectory shown for point-to-point arm reaching movements, with similar time to target. In addition, the trajectories based on ultrasound imaging result in a systematic delay and scaling of peak movement velocity as the movement distance increased. We believe this is the first evaluation of similarities in control policies in coordinated movements in jointed limbs, and those based on position control signals extracted at the individual muscle level. These results have strong implications for the future development of control paradigms for assistive technologies.

    

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5. Infants rationally infer the goals of other people's reaches in the absence of first‐person experience with reaching actions

   https://doi.org/10.1111/desc.13453  

   Woo, Brandon M. ; Liu, Shari ; Spelke, Elizabeth S. ( November 2023 , Developmental Science)

   Does knowledge of other people's minds grow from concrete experience to abstract concepts? Cognitive scientists have hypothesized that infants’ first‐person experience, acting on their own goals, leads them to understand others’ actions and goals. Indeed, classic developmental research suggests that before infants reach for objects, they do not see others’ reaches as goal‐directed. In five experiments (N = 117), we test an alternative hypothesis: Young infants view reaching as undertaken for a purpose but are open‐minded about the specific goals that reaching actions are aimed to achieve. We first show that 3‐month‐old infants, who cannot reach for objects, lack the expectation that observed acts of reaching will be directed to objects rather than to places. Infants at the same age learned rapidly, however, that a specific agent's reaching action was directed either to an object or to a place, after seeing the agent reach for the same object regardless of where it was, or to the same place regardless of what was there. In a further experiment, 3‐month‐old infants did not demonstrate such inferences when they observed an actor engaging in passive movements. Thus, before infants have learned to reach and manipulate objects themselves, they infer that reaching actions are goal‐directed, and they are open to learning that the goal of an action is either an object or a place.

   In the present experiments, 3‐month‐old prereaching infants learned to attribute either object goals or place goals to other people's reaching actions.

   Prereaching infants view agents’ actions as goal‐directed, but do not expect these acts to be directed to specific objects, rather than to specific places.

   Prereaching infants are open‐minded about the specific goal states that reaching actions aim to achieve.

    

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