Task space exploration improves adaptation after incompatible virtual surgeries

Berger, Denise; Borzelli, Daniele; d’Avella, Andrea

doi:10.1152/jn.00356.2021

Cited by 15 publications

(11 citation statements)

References 90 publications

(54 reference statements)

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“…Our null-space reaching results suggest that while users possess variability in their null-space behaviour, most lack the flexibility and control necessary for using all of the mechanical degrees of redundancy present in the wrist complex. This apparent inability to exploit novel muscle activation patterns differs from findings considering the entire upper limb 15 , where it has been observed that with sufficient time to make online motion corrections participants could learn to exploit atypical arm-wide muscle activation patterns for end-point reaching tasks. This suggests that while there is some potential for the use of musculoskeletal redundancy across an entire limb as a source of commands for movement augmentation it does not appear to be suitable at the level of the wrist joint, at least not within a short practice period on a single day.…”

Section: Discussionmentioning

confidence: 57%

“…This indicates that at least over the time-scale of the experiment that there was no learning effect in the range of null-space activation behaviours. While it has been previously observed that atypical muscle activation patterns can be observed only with larger time for adaptation 15 , it is worth noting that both the motion efficiency and number of corrections (Fig. 3B,D) suggest that participants did not make use of extensive online adaptation when they were successful.…”

Section: Discussionmentioning

confidence: 66%

“…This redundancy could potentially provide natural and measurable signals for human movement augmentation. Here, it has been shown that after remapping muscle activation to new muscle synergies, humans can (with sufficient exploration time) adapt their muscle activation behaviour in response to either simple remappings requiring combinations of existing muscle synergies, or the more challenging case requiring completely new synergies 15 . Moreover, it has been found that muscle activation patterns that fall into the muscle-to-force ‘null-space’ during isometric movement can be used as an additional control signal that is regulated simultaneously to the generation of isometric force 16 .…”

Section: Introductionmentioning

confidence: 99%

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Control limitations in the null-space of the wrist muscle system

Lee,

Eden,

Gurgone

et al. 2023

Preprint

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The redundancy present within the musculoskeletal system may offer a non-invasive source of signals for movement augmen tation, where the muscle-to-force null-space could be controlled simultaneously to the natural limbs. Here, we investigated the viability of extracting movement augmentation control signals from the muscles of the wrist complex. Our study assessed i) if controlled variation of the muscle activation patterns in the wrist joint’s null-space is possible; and ii) whether force and null-space targets could be reached simultaneously. During the null-space target reaching condition, participants used EMG-to-force null-space muscle activation to move their cursor towards a displayed target while minimising the exerted force as visualised through the cursor’s size. Initial targets were positioned to require natural co-contraction in the null-space and if participants showed a consistent ability to reach for their current target, they would rotate 5° incrementally to generate muscle activation patterns further away from their natural co-contraction. In contrast, during the concurrent target reaching condition participants were required to match a target position and size, where their cursor position was instead controlled by their exerted flexion-extension and radial-ulnar deviation, while its size was changed by their natural co-contraction magnitude. The results collected from 10 participants suggest that while there was variation in each participant’s co-contraction behaviour, most did not possess the ability to control this variation for muscle-to-force null-space reaching. In contrast, participants did show a direction and target size dependent ability to vary isometric force and co-contraction activity concurrently. Our results show the limitations of using null-space activity in joints with a low level of redundancy.

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Section: Discussionmentioning

confidence: 57%

Section: Discussionmentioning

confidence: 66%

Section: Introductionmentioning

confidence: 99%

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Control limitations in the null-space of the wrist muscle system

Lee,

Eden,

Gurgone

et al. 2023

Preprint

Self Cite

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“…Different approaches for the estimation of the EMG-to-force mapping have been proposed in the literature. During isometric tasks, in which the non-linearities due to muscle contraction velocity and muscle length can be neglected, an approximation of the EMG-to-force relation via linear mapping, as performed in this study, may be acceptable [ 52 , 53 , 54 ], and it may be eventually improved by introducing foreknown anatomical constraints [ 13 , 30 , 55 , 56 , 57 ]. Moreover, an interesting recent study [ 58 ] proposed an innovative approach for the rapid estimation of the joint torque or velocity from the muscle activations.…”

Section: Discussionmentioning

confidence: 99%

Virtual Stiffness: A Novel Biomechanical Approach to Estimate Limb Stiffness of a Multi-Muscle and Multi-Joint System

Borzelli

Pastorelli

d’Avella

et al. 2023

Sensors

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In recent years, different groups have developed algorithms to control the stiffness of a robotic device through the electromyographic activity collected from a human operator. However, the approaches proposed so far require an initial calibration, have a complex subject-specific muscle model, or consider the activity of only a few pairs of antagonist muscles. This study described and tested an approach based on a biomechanical model to estimate the limb stiffness of a multi-joint, multi-muscle system from muscle activations. The “virtual stiffness” method approximates the generated stiffness as the stiffness due to the component of the muscle-activation vector that does not generate any endpoint force. Such a component is calculated by projecting the vector of muscle activations, estimated from the electromyographic signals, onto the null space of the linear mapping of muscle activations onto the endpoint force. The proposed method was tested by using an upper-limb model made of two joints and six Hill-type muscles and data collected during an isometric force-generation task performed with the upper limb. The null-space projection of the muscle-activation vector approximated the major axis of the stiffness ellipse or ellipsoid. The model provides a good approximation of the voluntary stiffening performed by participants that could be directly implemented in wearable myoelectric controlled devices that estimate, in real-time, the endpoint forces, or endpoint movement, from the mapping between muscle activation and force, without any additional calibrations.

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“…In a different kind of tasks, the position of objects in a virtual environment can be controlled as a function of EMG. The function can be defined so that successful completion of the task requires decorrelating the activity of two or more muscles (Wright et al, 2014;Mugler et al, 2019), or learning entirely new muscle activations patterns (Berger et al, 2021). Therefore, whereas learning in these tasks may reshape muscle activation patterns, it is unclear whether the newly learned patterns are transferable to more ecological tasks.…”

Section: Discussionmentioning

confidence: 99%

EMG space similarity feedback promotes learning of expert-like muscle activation patterns in a complex motor skill

Barradas

Cho²,

Koike³

2023

Front. Hum. Neurosci.

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Augmented feedback provided by a coach or augmented reality system can facilitate the acquisition of a motor skill. Verbal instructions and visual aids can be effective in providing feedback about the kinematics of the desired movements. However, many skills require mastering not only kinematic, but also complex kinetic patterns, for which feedback is harder to convey. Here, we propose the electromyography (EMG) space similarity feedback, which may indirectly convey kinematic and kinetic feedback by comparing the muscle activations of the learner and an expert in the task. The EMG space similarity feedback is a score that reflects how well a set of muscle synergies extracted from the expert can reconstruct the learner’s EMG when performing the task. We tested the EMG space similarity feedback in a virtual bimanual polishing task that uses a robotic system to simulate the dynamics of a real polishing operation. We measured the expert’s and learner’s EMG from eight muscles in each arm during the real and virtual polishing tasks, respectively. The goal of the virtual task was to smoothen the surface of a virtual object. Therefore, we defined performance in the task as the smoothness of the object at the end of a trial. We separated learners into real feedback and null feedback groups to assess the effects of the EMG space similarity feedback. The real and null feedback groups received veridic and no EMG space similarity feedback, respectively. Subjects participated in five training sessions on different days, and we evaluated their performance on each day. Subjects in both groups were able to increase smoothness throughout the training sessions, with no significant differences between groups. However, subjects in the real feedback group were able to improve in the EMG space similarity score to a significantly greater extent than the null feedback group. Additionally, subjects in the real feedback group produced muscle activations that became increasingly consistent with an important muscle synergy found in the expert. Our results indicate that the EMG space similarity feedback promotes acquiring expert-like muscle activation patterns, suggesting that it may assist in the acquisition of complex motor skills.

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Task space exploration improves adaptation after incompatible virtual surgeries

Cited by 15 publications

References 90 publications

Control limitations in the null-space of the wrist muscle system

Control limitations in the null-space of the wrist muscle system

Virtual Stiffness: A Novel Biomechanical Approach to Estimate Limb Stiffness of a Multi-Muscle and Multi-Joint System

EMG space similarity feedback promotes learning of expert-like muscle activation patterns in a complex motor skill

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