Brain–computer interface robotics for hand rehabilitation after stroke: a systematic review

Journal of NeuroEngineering and Rehabilitation, Journal Year: 2021, Volume and Issue: 18(1)

Published: Jan. 23, 2021

Abstract Background Hand rehabilitation is core to helping stroke survivors regain activities of daily living. Recent studies have suggested that the use electroencephalography-based brain-computer interfaces (BCI) can promote this process. Here, we report first systematic examination literature on BCI-robot systems for fine motor skills associated with hand movement and profile these from a technical clinical perspective. Methods A search January 2010–October 2019 articles using Ovid MEDLINE, Embase, PEDro, PsycINFO, IEEE Xplore Cochrane Library databases was performed. The selection criteria included BCI-hand robotic at different stages development involving tests healthy participants or people who had stroke. Data fields include those related study design, participant characteristics, specifications system, outcome measures. Results 30 were identified as eligible qualitative review among these, 11 involved testing robot chronic subacute patients. Statistically significant improvements in assessment scores relative controls observed three interventions. degree control majority limited triggering device perform grasping pinching movements imagery. Most employed combination kinaesthetic visual response via display screen, respectively, match feedback Conclusion 19 out BCI-robotic prototype pre-clinical development. We large heterogeneity reporting emphasise need develop standard protocol assessing outcomes so necessary evidence base efficiency efficacy be developed.

Language: Английский

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Skin Electronics: Next‐Generation Device Platform for Virtual and Augmented Reality

Advanced Functional Materials, Journal Year: 2021, Volume and Issue: 31(39)

Published: Feb. 25, 2021

Abstract Virtual reality (VR) and augmented (AR) are overcoming the physical limits of real‐life using advances in devices software. In particular, recent restrictions transportation from coronavirus disease 2019 (COVID‐19) pandemic making people more interested these virtual experiences. However, to minimize differences between artificial natural perception, human‐interactive human‐like necessary. The skin is largest organ human body interacts with environment as site interfacing sensing. Recent progress electronics has enabled use mounting object functional signal pathway bridging humans computers, opening its potential future VR AR applications. this review, current summarized one most promising device solutions for VR/AR devices, especially focusing on materials structures. After defining explaining systems components, advantages applications emphasized. Next, detailed functionalities electronic including input, output, energy integrated systems, reviewed

Language: Английский

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Control Strategies for Soft Robot Systems

Advanced Intelligent Systems, Journal Year: 2022, Volume and Issue: 4(5)

Published: Feb. 22, 2022

Soft robots have recently attracted increased attention because their characteristics of low‐cost fabrication, durability, and deformability make them uniquely suited for applications in bio‐integrated systems. Being fundamentally different from traditional rigid robots, soft exhibit properties infinite degrees freedom (DOF) nonlinear materials that require innovations control With the rapid development science, robotics, artificial intelligence, diversification actuator mechanisms algorithms has enabled a wide range unique strategies. This review summarizes basics strategies, including open‐loop control, closed‐loop autonomous discusses implementation diversified perspectives. Control strategies are evaluated based on compatibility with sets, application goals, route. The emerging directions forecasted perspectives interfacing between controller actuator, underactuated intelligence (AI).

Language: Английский

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Wireless EEG: A survey of systems and studies

NeuroImage, Journal Year: 2022, Volume and Issue: 269, P. 119774 - 119774

Published: Dec. 22, 2022

The popular brain monitoring method of electroencephalography (EEG) has seen a surge in commercial attention recent years, focusing mostly on hardware miniaturization. This led to varied landscape portable EEG devices with wireless capability, allowing them be used by relatively unconstrained users real-life conditions outside the laboratory. wide availability and relative affordability these provide low entry threshold for newcomers field research. large device variety at times opaque communication from their manufacturers, however, can make it difficult obtain an overview this landscape. Similarly, given breadth existing (wireless) knowledge research, challenging get started novel ideas. Therefore, paper first provides list 48 along number important-sometimes difficult-to-obtain-features characteristics enable side-by-side comparison, brief introduction each aspects how they may influence one's decision. Secondly, we have surveyed previous literature focused 110 high-impact journal publications making use EEG, which categorized application analyzed used, channels, sample size, participant mobility. Together, basis informed decision respect experimental precedents when considering new, At same time, background material commentary about pitfalls caveats regarding increasingly accessible line

Language: Английский

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Electrooculography and Tactile Perception Collaborative Interface for 3D Human–Machine Interaction

ACS Nano, Journal Year: 2022, Volume and Issue: 16(4), P. 6687 - 6699

Published: April 6, 2022

The human–machine interface (HMI) previously relied on a single perception that cannot realize three-dimensional (3D) interaction and convenient accurate in multiple scenes. Here, we propose collaborative including electrooculography (EOG) tactile for fast 3D interaction. EOG signals are mainly used fast, convenient, contactless 2D (XY-axis) interaction, the sensing is utilized complex movement control Z-axis honeycomb graphene electrodes signal acquisition array prepared by laser-induced process. Two pairs of ultrathin breathable attached around eyes monitoring nine different eye movements. A machine learning algorithm designed to train classify movements with an average prediction accuracy 92.6%. Furthermore, (90 μm), stretchable (∼1000%), flexible assembled pair 4 × planar electrode arrays arm which can single-point, multipoint sliding touch functions. Consequently, achieve eight directions even more trajectory control. Meanwhile, sensor exhibits ultrahigh sensitivity 1.428 kPa–1 pressure range 0–300 Pa long-term response stability repeatability. Therefore, collaboration between will play important role rapid

Language: Английский

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Surface Electromyography as a Natural Human–Machine Interface: A Review

IEEE Sensors Journal, Journal Year: 2022, Volume and Issue: 22(10), P. 9198 - 9214

Published: April 8, 2022

Surface electromyography (sEMG) is a non-invasive method of measuring neuromuscular potentials generated when the brain instructs body to perform both fine and coarse locomotion. This technique has seen extensive investigation over last two decades, with significant advances in hardware signal processing methods used collect analyze sEMG signals. While early work focused mainly on medical applications, there been growing interest utilizing as sensing modality enable next-generation, high-bandwidth, natural human-machine interfaces. In first part this review, we briefly overview human skeletomuscular physiology that gives rise signals followed by review developments acquisition hardware. Special attention paid towards fidelity these devices well form factor, recent have pushed limits user comfort high-bandwidth acquisition. second half article, explore quantifying information content gestures then various machine learning developed extract Finally, discuss future outlook field, highlighting key gaps current seamless interactions between humans machines.

Language: Английский

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Cognitive neuroscience and robotics: Advancements and future research directions

Robotics and Computer-Integrated Manufacturing, Journal Year: 2023, Volume and Issue: 85, P. 102610 - 102610

Published: July 24, 2023

In recent years, brain-based technologies that capitalise on human abilities to facilitate human–system/robot interactions have been actively explored, especially in brain robotics. Brain–computer interfaces, as applications of this conception, set a path convert neural activities recorded by sensors from the scalp via electroencephalography into valid commands for robot control and task execution. Thanks advancement sensor technologies, non-invasive invasive headsets designed developed achieve stable recording brainwave signals. However, robust accurate extraction interpretation signals robotics are critical reliable task-oriented opportunistic such brainwave-controlled robotic interactions. response need, pervasive advanced analytical approaches translating merging functions, behaviours, tasks, environmental information focus brain-controlled applications. These methods composed signal processing, feature extraction, representation activities, command conversion control. Artificial intelligence algorithms, deep learning, used classification, recognition, identification patterns intent underlying brainwaves form electroencephalography. Within context, paper provides comprehensive review past current status at intersection robotics, neuroscience, artificial highlights future research directions.

Language: Английский

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A deep CNN approach to decode motor preparation of upper limbs from time–frequency maps of EEG signals at source level

Neural Networks, Journal Year: 2020, Volume and Issue: 124, P. 357 - 372

Published: Jan. 31, 2020

Language: Английский

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A human skin-inspired self-powered flex sensor with thermally embossed microstructured triboelectric layers for sign language interpretation

Nano Energy, Journal Year: 2020, Volume and Issue: 76, P. 105071 - 105071

Published: June 30, 2020

Language: Английский

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Noninvasive Electroencephalography Equipment for Assistive, Adaptive, and Rehabilitative Brain–Computer Interfaces: A Systematic Literature Review

Sensors, Journal Year: 2021, Volume and Issue: 21(14), P. 4754 - 4754

Published: July 12, 2021

Humans interact with computers through various devices. Such interactions may not require any physical movement, thus aiding people severe motor disabilities in communicating external The brain–computer interface (BCI) has turned into a field involving new elements for assistive and rehabilitative technologies. This systematic literature review (SLR) aims to help BCI investigator investors decide which devices select or studies support based on the current market examination. examination of noninvasive EEG is published different research areas. In this SLR, area BCIs using electroencephalography (EEG) was analyzed by examining types equipment used assistive, adaptive, BCIs. For candidate were selected from IEEE digital library, PubMed, Scopus, ScienceDirect. inclusion criteria (IC) limited focusing applications technology. data herein IC exclusion ensure quality assessment. articles divided four main areas: education, engineering, entertainment, medicine. Overall, 238 papers IC. Moreover, 28 companies identified that developed wired wireless as means findings indicate implications technologies are encouraging healthy people. With an increasing number BCIs, other areas, such motivation players when participating games security soldiers observing certain can be studied collaborated However, systems must simple (wearable), convenient (sensor fabrics self-adjusting abilities), inexpensive.

Language: Английский

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