Neurorobotic fusion of prosthetic touch, kinesthesia, and movement in bionic upper limbs promotes intrinsic brain behaviors

Science Robotics, Journal Year: 2021, Volume and Issue: 6(58)

Published: Sept. 2, 2021

Bionic prostheses have restorative potential. However, the complex interplay between intuitive motor control, proprioception, and touch that represents hallmark of human upper limb function has not been revealed. Here, we show neurorobotic fusion touch, grip kinesthesia, control promotes levels behavioral performance are stratified toward able-bodied away from standard-of-care prosthetic users. This was achieved through targeted sensory reinnervation, a closed-loop neural-machine interface, coupled to noninvasive robotic architecture. Adding improves ability reach intended target grasp forces, find durometers among distractors, promote ownership. Touch, restore balanced decision strategies when identifying intrinsic visuomotor behaviors reduce need watch hand during object interactions, which frees eyes look ahead next planned action. The combination these three modalities also enhances error correction performance. We applied our unified theoretical, functional, clinical analyses, enabling us define relative contributions operating simultaneously in this interface. multiperspective framework provides necessary evidence bionic attain more human-like with effective sensory-motor restoration.

Language: Английский

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EMG-driven control in lower limb prostheses: a topic-based systematic review

Journal of NeuroEngineering and Rehabilitation, Journal Year: 2022, Volume and Issue: 19(1)

Published: May 7, 2022

Abstract Background The inability of users to directly and intuitively control their state-of-the-art commercial prosthesis contributes a low device acceptance rate. Since Electromyography (EMG)-based has the potential address those inabilities, research flourished on investigating its incorporation in microprocessor-controlled lower limb prostheses (MLLPs). However, despite proposed benefits doing so, there is no clear explanation regarding absence product, contrast upper counterparts. Objective methodologies This manuscript aims provide comparative overview EMG-driven methods for MLLPs, identify prospects limitations, formulate suggestions future development. done by systematically reviewing academical studies EMG MLLPs. In particular, this review structured considering four major topics: (1) type neuro-control, which discusses that allow nervous system prosthetic devices through muscles; (2) controllers, defines different classes controllers literature; (3) neural input processing, describes how are implemented; (4) performance assessment, reports current state art controllers. Results conclusions obtained results show lack quantitative standardized measures hinders possibility analytically compare performances relation issue, real efficacy MLLPs have yet be validated. Nevertheless, anticipation development approach validating literature suggests combining multiple neuro-controller types develop more seamless reliable control. solution promise retain high currently employed non-EMG-driven rhythmic activities such as walking, whilst improving volitional task switching or non-repetitive movements. Although suffer from many drawbacks, sensitivity noise, recent progress invasive interfaces (bionics) will build connection between user Therefore, advancements powered with integrated strongly reduce effects psychosomatic conditions musculoskeletal degenerative pathologies affecting amputees.

Language: Английский

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Bioelectronic medicine: Preclinical insights and clinical advances

Neuron, Journal Year: 2022, Volume and Issue: 110(21), P. 3627 - 3644

Published: Sept. 28, 2022

Language: Английский

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Simultaneous and Proportional Real-Time Myocontrol of Up to Three Degrees of Freedom of the Wrist and Hand

IEEE Transactions on Biomedical Engineering, Journal Year: 2022, Volume and Issue: 70(2), P. 459 - 469

Published: July 26, 2022

Achieving robust, intuitive, simultaneous and proportional control over multiple degrees of freedom (DOFs) is an outstanding challenge in the development myoelectric prosthetic systems. Since priority prosthesis solutions robustness stability, their number functions usually limited. Objective: Here, we introduce a system for intuitive concurrent hand wrist control, based on robust feature-extraction protocol machine-learning. xmlns:xlink="http://www.w3.org/1999/xlink">Methods: Using mean absolute value high-density EMG, train ridge-regressor (RR) only sustained portions single-DOF contractions leverage regressor's inherent ability to provide multi-DOF estimates. In this way, robustly capture amplitude information inputs while harnessing power RR extrapolate otherwise noisy often overfitted estimations dynamic movements. xmlns:xlink="http://www.w3.org/1999/xlink">Results: The real-time evaluation 13 able-bodied participants amputee shows that almost all tasks could be reached (96% success rate), at same time users were able complete most two-DOF (62%) even some very challenging three-DOF (37%). To further investigate translational potential approach, reduced original 192-channel setup 16-channel configuration observed performance did not deteriorate. Notably, performed similarly well other participants, according considered metrics. xmlns:xlink="http://www.w3.org/1999/xlink">Conclusion: This first operated myocontrol consistently provides 3-DOFs hand, relying surface EMG signals from forearm. xmlns:xlink="http://www.w3.org/1999/xlink">Significance: Focusing complexity, test inclusion study demonstrate future applications control.

Language: Английский

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Active upper limb prostheses: a review on current state and upcoming breakthroughs

Progress in Biomedical Engineering, Journal Year: 2022, Volume and Issue: 5(1), P. 012001 - 012001

Published: Dec. 16, 2022

Abstract The journey of a prosthetic user is characterized by the opportunities and limitations device that should enable activities daily living (ADL). In particular, experiencing bionic hand as functional (and, advantageously, embodied) limb constitutes premise for promoting practice in using device, mitigating risk its abandonment. order to achieve such result, different aspects need be considered making artificial an effective solution accomplish ADL. According perspective, this review aims at presenting current issues envisioning upcoming breakthroughs upper devices. We first define sources input feedback involved system control (at user-level device-level), alongside related algorithms used signal analysis. Moreover, paper focuses on user-centered design challenges strategies guide implementation novel solutions area terms technology acceptance, embodiment, and, general, human-machine integration based co-adaptive processes. here provide readers (belonging target communities researchers, designers, developers, clinicians, industrial stakeholders, end-users) with overview state-of-the-art potential innovations hands features, hopefully interdisciplinary efforts solving prostheses. perspectives transdisciplinary intertwining leading truly holistic comprehension improvement design. Overall, move boundaries innovation beyond development tool toward engineering human-centered limbs.

Language: Английский

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Application of Min-Max Normalization on Subject-Invariant EMG Pattern Recognition

IEEE Transactions on Instrumentation and Measurement, Journal Year: 2022, Volume and Issue: 71, P. 1 - 12

Published: Jan. 1, 2022

Surface electromyography (EMG) is one of the promising signals for recognition intended hand movement an amputee. Nevertheless, there are several barriers to its successful implementation in advanced prosthetic hand. Subject-dependent EMG pattern them, which limits use a training model specific subject others. So, this study aims explore invariant method that performed by extracting features. To extract features, we have created feature space using extraction method, and dimensionality reduced employing spectral regression discriminant analysis (SRDA). Finally, each SRDA normalized min-max normalization, confines scale from 0 1. The proposed achieves F1 score 97.26%, 96.47%, 95.42%, 93.71% with linear classifier (LDA) electrode array 8×16, 8×8, 8×4, 8×2, respectively. achieved performances almost equal or sometimes better than those independent subject-dependent recognition. Also, simple, independent, time complexity free, does not require any customization fine-tuning classifiers. would be option overcome barrier without compromising performance.

Language: Английский

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Larger and Denser: An Optimal Design for Surface Grids of EMG Electrodes to Identify Greater and More Representative Samples of Motor Units

eNeuro, Journal Year: 2023, Volume and Issue: 10(9), P. ENEURO.0064 - 23.2023

Published: Sept. 1, 2023

The spinal motor neurons are the only neural cells whose individual activity can be noninvasively identified. This is usually done using grids of surface electromyographic (EMG) electrodes and source separation algorithms; an approach called EMG decomposition. In this study, we combined computational experimental analyses to assess how design parameters influence number properties identified units. We first computed percentage units that could theoretically discriminated within a pool 200 simulated when decomposing signals recorded with various sizes interelectrode distances (IEDs). Increasing density, electrodes, size grids, increased our decomposition algorithm discriminate, i.e., up 83.5% (range across conditions: 30.5-83.5%). then from in six participants (range: 2-36 cm

Language: Английский

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Angle-programmed tendril-like trajectories enable a multifunctional gripper with ultradelicacy, ultrastrength, and ultraprecision

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: Aug. 2, 2023

Achieving multicapability in a single soft gripper for handling ultrasoft, ultrathin, and ultraheavy objects is challenging due to the tradeoff between compliance, strength, precision. Here, combining experiments, theory, simulation, we report utilizing angle-programmed tendril-like grasping trajectories an ultragentle yet ultrastrong ultraprecise gripper. The can delicately grasp fragile liquids with minimal contact pressure (0.05 kPa), lift 16,000 times its own weight, precisely flexible like 4-μm-thick sheets 2-μm-diameter microfibers on flat surfaces, all high success rate. Its scalable material-independent design allows biodegradable noninvasive grippers made from natural leaves. Explicitly controlled facilitate integration robotic arms prostheses tasks, including picking grapes, opening zippers, folding clothes, turning pages. This work showcases excelling extreme scenarios potential applications agriculture, food processing, prosthesis, biomedicine, minimally invasive surgeries, deep-sea exploration.

Language: Английский

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A myoelectric digital twin for fast and realistic modelling in deep learning

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: March 23, 2023

Abstract Muscle electrophysiology has emerged as a powerful tool to drive human machine interfaces, with many new recent applications outside the traditional clinical domains, such robotics and virtual reality. However, more sophisticated, functional, robust decoding algorithms are required meet fine control requirements of these applications. Deep learning shown high potential in meeting demands, but requires large amount high-quality annotated data, which is expensive time-consuming acquire. Data augmentation using simulations, strategy applied other deep applications, never been attempted electromyography due absence computationally efficient models. We introduce concept Myoelectric Digital Twin - highly realistic fast computational model tailored for training algorithms. It enables simulation arbitrary perfectly datasets signals, allowing approaches muscular signal decoding, accelerating development human-machine interfaces.

Language: Английский

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On human-in-the-loop optimization of human–robot interaction

Nature, Journal Year: 2024, Volume and Issue: 633(8031), P. 779 - 788

Published: Sept. 25, 2024

Language: Английский

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