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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. [ABSTRACT FROM AUTHOR]

The ability to make predictive saccadic eye movements is dependent on neural signals that anticipate the onset of a visual target. We used a novel paradigm—based on the saccade-countermanding task—as a tool to investigate rhythm saccade pacing and to provide information on the mechanisms of predictive timing. In particular, we examined the ability of normal subjects to stop a sequence of periodically paced eye movements when cued by a stop signal that was presented at different times with respect to the last target of the sequence (stop signal delay, SSD). The timing of the stop signal affected the ability to stop the saccadic sequence (make a saccade to a central target rather than to the peripheral alternating targets) in different ways, depending on the preceding tracking behavior. For the same SSD, subjects cancelled fewer trials during predictive tracking (promoted by tracking targets alternating at a fast pacing rate, 1.0 Hz) than during reactive tracking (tracking alternating targets at a low pacing rate, 0.2 Hz). In addition, on non-canceled trials, there was an increase in the delay of the corrective saccade to the central target with increasing SSD for pacing at 0.2 Hz, but the timing of the corrective saccade remained near constant for 1.0 Hz pacing. In examining the timing between movements, we estimate that the repetitive GO process that drives the saccades during predictive tracking begins earlier and has a shorter duration than the repetitive GO process during reactive tracking. These behavioral results provide further insight into the initiation process of predictive responses. In particular, the reduced reaction time and the corresponding short duration of the predictive process may result from a faster accumulation of neuronal discharge to a relatively fixed threshold. [ABSTRACT FROM AUTHOR]

Humans readily make predictive saccades to periodic alternating targets. This predictive behavior depends on internal monitoring of timing error of past saccades in order to determine the time of initiation of future saccades; our earlier studies have confirmed this by finding correlations between latencies of consecutive predictive saccades. It is natural to consider that timing error is determined by visual detection of the difference between the time the target appears and the time the eyes arrive at the target; this in turn implies that saccades must actually be produced in order for their timing errors to be determined and predictive saccade timing to be established. We tested this hypothesis by having subjects view alternating visual targets while fixating a central target in order to eliminate saccade production. After six alternating target presentations, subjects began tracking the alternating targets. Tracking performance was assessed with an error measure that compared saccade latency and inter-saccade interval with desired values (zero and inter-stimulus interval, respectively). Errors in this Prior Viewing paradigm were compared to those from a conventional De Novo paradigm in which saccades began as soon as the alternating targets were presented. Saccades under Prior Viewing reached a low-error steady predictive state more rapidly than under De Novo tracking. The initial saccade under Prior Viewing had a higher latency than the others, suggesting that this saccade was reactive even though the paradigm is predictable; other reasons for this higher latency include time to disengage from the fixation target and time required to pre-program the initial set of saccades. The results show that visual detection of timing error from an actual motor act (saccades) is not necessary to establish predictive saccadic pacing: sensory-only information from viewing the moving targets can help to establish this predictive state. [ABSTRACT FROM AUTHOR]

Previously we demonstrated the presence of a behavioral phase transition between reactive and predictive eye tracking of alternating targets. Prior studies of repetitive movements have proposed that an “internal clock” is the neural mechanism by which interval timing is achieved. In the present report we tested whether predictive oculomotor (saccade) tracking is based on an internal time reference (clock) by examining the effect of transient perturbations to the periodic pacing stimulus. These perturbations consisted of altering the timing of the stimulus (abruptly increasing or decreasing the inter-stimulus interval) or extinguishing the targets altogether. Although reactive tracking (at low pacing rates) was greatly affected by these timing perturbations, once predictive tracking was established subjects continued to time their eye movement responses at the pre-existing rate despite the perturbation. As expected from certain clock models, inter-stimulus intervals for predictive tracking followed Weber’s law and the scalar property (timing variability increases in proportion to interval duration), but this was not true for reactive tracking. In addition, the perturbation results show that subjects can establish an internal representation of target pacing (the internal clock) in as little as two eye-movement intervals, which suggests that this mechanism is relevant for real-world situations. These findings are consistent with the presence of an internal clock for the generation of these predictive movements, and demonstrate that the neural mechanism responsible for this behavior is temporally accurate and flexible. [ABSTRACT FROM AUTHOR]

Data from previous human and primate studies on saccadic and smooth pursuit eye movements suggest that there are shared internal inputs (for example, perception, attention, expectation, and memory) for the initiation of the two types of movements. Additional reports examining the effect of preparation time on movement responses have shown that when ample time is allowed subjects usually generate long-latency “reactive” responses. When the time allowed to prepare a movement is short, however, subjects respond with reduced latency and often anticipate the stimulus (“predictive” response). Based on these findings, we believe that the shared internal inputs at early stages of movement preparation may result in saccade and pursuit eye movements demonstrating the same dependence on preparation time despite acting through different neural pathways further downstream. Previously we demonstrated a behavioral “phase transition” when normal subjects tracked alternating targets with saccades. When preparation time was long (low-frequency pacing) subjects made reactive saccades (latency ~180 ms). As preparation time monotonically decreased (pacing frequency increased), there was an abrupt transition to a predictive response (latency <100 ms). In the present study we show that a similar transition exists in smooth pursuit tracking and that the point of transition between the two behaviors is the same for both systems. In other words, the same behavior (reactive versus predictive) is selected when pursuit and saccade tracking are tested under the same time constraints. This provides further evidence that the two types of movements are different motor outcomes of a common decision process. [ABSTRACT FROM AUTHOR]

In recent years, commercially available dexterous upper limb prostheses for children have begun to emerge. These devices derive control signals from surface electromyography (measure of affected muscle electrical activity, sEMG) to drive a variety of grasping motions. However, the ability for children with congenital upper limb deficiency to actuate their affected muscles to achieve naturalistic prosthetic control is not well understood, as compared to adults or children with acquired hand loss. To address this gap, we collected sEMG data from 9 congenital one-handed participants ages 8–20 years as they envisioned and attempted to perform 10 different movements with their missing hands. Seven sEMG electrodes were adhered circumferentially around the participant's affected and unaffected limbs and participants mirrored the attempted missing hand motions with their intact side. To analyze the collected sEMG data, we used time and frequency domain analyses. We found that for the majority of participants, attempted hand movements produced detectable and consistent muscle activity, and the capacity to achieve this was not dissimilar across the affected and unaffected sides. These data suggest that children with congenital hand absence retain a degree of control over their affected muscles, which has important implications for translating and refining advanced prosthetic control technologies for children. [ABSTRACT FROM AUTHOR]

Technological advances in multi-articulated prosthetic hands have outpaced the development of methods to intuitively control these devices. In fact, prosthetic users often cite "difficulty of use" as a key contributing factor for abandoning their prostheses. To overcome the limitations of the currently pervasive myoelectric control strategies, namely unintuitive proportional control of multiple degrees-of-freedom, we propose a novel approach: proprioceptive sonomyographiccontrol. Unlike myoelectric control strategies which measure electrical activation of muscles and use the extracted signals to determine the velocity of an end-effector; our sonomyography-based strategy measures mechanical muscle deformation directly with ultrasound and uses the extracted signals to proportionally control the position of an end-effector. Therefore, our sonomyography-based control is congruent with a prosthetic user's innate proprioception of muscle deformation in the residual limb. In this work, we evaluated proprioceptive sonomyographic control with 5 prosthetic users and 5 able-bodied participants in a virtual target achievement and holding task for 5 different hand motions. We observed that with limited training, the performance of prosthetic users was comparable to that of able-bodied participants and thus conclude that proprioceptive sonomyographic control is a robust and intuitive prosthetic control strategy. [ABSTRACT FROM AUTHOR]