EEG Analysis in Coincident Timing Task Towards Motor Rehabilitation

Melo, Gabriel Chaves de; Sternlicht, Vitor Martes; Forner-Cordero, Arturo

doi:10.1109/embc44109.2020.9175851

Cited by 2 publications

(2 citation statements)

References 25 publications

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“…The dynamic evolution of EEG signal power over time within a specific frequency band is assessed using event-related desynchronization (ERD) and event-related synchronization (ERS). The ERD(S) phenomenon is notably observed in the alpha (8)(9)(10)(11)(12)(13) and beta (13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) frequency bands during the execution of movements [14][15][16][17][18][19]. Moreover, functional brain connectivity reveals the process of information transmission among brain regions during movement.…”

Section: Introductionmentioning

confidence: 99%

Decoding Electroencephalography Underlying Natural Grasp Tasks across Multiple Dimensions

Gu,

Wang,

Jiao

et al. 2023

Electronics

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Individuals suffering from motor dysfunction due to various diseases often face challenges in performing essential activities such as grasping objects using their upper limbs, eating, writing, and more. This limitation significantly impacts their ability to live independently. Brain–computer interfaces offer a promising solution, enabling them to interact with the external environment in a meaningful way. This exploration focused on decoding the electroencephalography of natural grasp tasks across three dimensions: movement-related cortical potentials, event-related desynchronization/synchronization, and brain functional connectivity, aiming to provide assistance for the development of intelligent assistive devices controlled by electroencephalography signals generated during natural movements. Furthermore, electrode selection was conducted using global coupling strength, and a random forest classification model was employed to decode three types of natural grasp tasks (palmar grasp, lateral grasp, and rest state). The results indicated that a noteworthy lateralization phenomenon in brain activity emerged, which is closely associated with the right or left of the executive hand. The reorganization of the frontal region is closely associated with external visual stimuli and the central and parietal regions play a crucial role in the process of motor execution. An overall average classification accuracy of 80.3% was achieved in a natural grasp task involving eight subjects.

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Section: Introductionmentioning

confidence: 99%

Decoding Electroencephalography Underlying Natural Grasp Tasks across Multiple Dimensions

Gu,

Wang,

Jiao

et al. 2023

Electronics

View full text Add to dashboard Cite

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“…ERD/ERS pattern has been widely studied in MI-BCI modalities as a potentially effective strategy for detecting and measuring commands to control a system [21,22]. For instance, the beta cortical oscillations control signals were effective to actuate an upper-limb exoskeleton with motor execution and motor imagination [23], and to trigger a robot-assisted action during lower limb motor imagery tasks [24,25]. In particular, one of the inspirational developments in the BCI-based beta rebound system was used to control a virtual spaceship takeoff using real or imaginary foot movements.…”

Section: Introductionmentioning

confidence: 99%

BCI-Based Control for Ankle Exoskeleton T-FLEX: Comparison of Visual and Haptic Stimuli with Stroke Survivors

Barria

Pino

Tovar

et al. 2021

Sensors

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Brain–computer interface (BCI) remains an emerging tool that seeks to improve the patient interaction with the therapeutic mechanisms and to generate neuroplasticity progressively through neuromotor abilities. Motor imagery (MI) analysis is the most used paradigm based on the motor cortex’s electrical activity to detect movement intention. It has been shown that motor imagery mental practice with movement-associated stimuli may offer an effective strategy to facilitate motor recovery in brain injury patients. In this sense, this study aims to present the BCI associated with visual and haptic stimuli to facilitate MI generation and control the T-FLEX ankle exoskeleton. To achieve this, five post-stroke patients (55–63 years) were subjected to three different strategies using T-FLEX: stationary therapy (ST) without motor imagination, motor imagination with visual stimulation (MIV), and motor imagination with visual-haptic inducement (MIVH). The quantitative characterization of both BCI stimuli strategies was made through the motor imagery accuracy rate, the electroencephalographic (EEG) analysis during the MI active periods, the statistical analysis, and a subjective patient’s perception. The preliminary results demonstrated the viability of the BCI-controlled ankle exoskeleton system with the beta rebound, in terms of patient’s performance during MI active periods and satisfaction outcomes. Accuracy differences employing haptic stimulus were detected with an average of 68% compared with the 50.7% over only visual stimulus. However, the power spectral density (PSD) did not present changes in prominent activation of the MI band but presented significant variations in terms of laterality. In this way, visual and haptic stimuli improved the subject’s MI accuracy but did not generate differential brain activity over the affected hemisphere. Hence, long-term sessions with a more extensive sample and a more robust algorithm should be carried out to evaluate the impact of the proposed system on neuronal and motor evolution after stroke.

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EEG Analysis in Coincident Timing Task Towards Motor Rehabilitation

Cited by 2 publications

References 25 publications

Decoding Electroencephalography Underlying Natural Grasp Tasks across Multiple Dimensions

Decoding Electroencephalography Underlying Natural Grasp Tasks across Multiple Dimensions

BCI-Based Control for Ankle Exoskeleton T-FLEX: Comparison of Visual and Haptic Stimuli with Stroke Survivors

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