Brain–Computer Interface for Controlling Lower-Limb Exoskeletons

Pino, Angie; Tovar, Nicolás; Barria, Patricio; Baleta, Karim; Múnera, Marcela; Cifuentes, Carlos A.

doi:10.1007/978-3-030-79630-3_9

Interfacing Humans and Robots for Gait Assistance and Rehabilitation 2021

DOI: 10.1007/978-3-030-79630-3_9

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Brain–Computer Interface for Controlling Lower-Limb Exoskeletons

Angie Pino

Nicolás Tovar

Patricio Barria

et al.

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2023

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Cited by 3 publications

References 45 publications

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Analysis of Cerebral and Muscle Activity during Control of a Corticospinal Neural Interface

Bobrova,

Reshetnikova,

Grishin

et al. 2023

Neurosci Behav Physi

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Analysis of Cerebral and Muscle Activity during Control of a Corticospinal Neural Interface

Bobrova,

Reshetnikova,

Grishin

et al. 2023

Neurosci Behav Physi

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Brain–computer interface: trend, challenges, and threats

Maiseli,

Abdalla,

Massawe

et al. 2023

Brain Inf.

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Brain–computer interface (BCI), an emerging technology that facilitates communication between brain and computer, has attracted a great deal of research in recent years. Researchers provide experimental results demonstrating that BCI can restore the capabilities of physically challenged people, hence improving the quality of their lives. BCI has revolutionized and positively impacted several industries, including entertainment and gaming, automation and control, education, neuromarketing, and neuroergonomics. Notwithstanding its broad range of applications, the global trend of BCI remains lightly discussed in the literature. Understanding the trend may inform researchers and practitioners on the direction of the field, and on where they should invest their efforts more. Noting this significance, we have analyzed 25,336 metadata of BCI publications from Scopus to determine advancement of the field. The analysis shows an exponential growth of BCI publications in China from 2019 onwards, exceeding those from the United States that started to decline during the same period. Implications and reasons for this trend are discussed. Furthermore, we have extensively discussed challenges and threats limiting exploitation of BCI capabilities. A typical BCI architecture is hypothesized to address two prominent BCI threats, privacy and security, as an attempt to make the technology commercially viable to the society.

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Analysis of Brain and Muscle Activity During Control of Brain-Spine Neurointerface

Bobrova,

Reshetnikova,

Grishin

et al. 2023

Zhurnal Vysshei Nervnoi Deyatelnosti Imeni I.P. Pavlova

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A brain-spine neurointerface based on the kinesthetic imagination of foot dorsiflexion with additional activation of foot movement by Biokin robotic device (mechanotherapy), and transcutaneous electrical spinal cord stimulation (TESCS) has been developed. Accuracy of classification of EEG-signals during the neurointerface control was on average 68% and significantly increases with the addition of mechanotherapy and TESCS by 9%. The EMG activity of the tibialis anterior (TA) – the muscle, which performs dorsiflexion of the foot, significantly increased during the instruction to imagine movement compared to that during the instruction to be at rest. The addition of mechanotherapy and TESCS during the neurointerface control has a greater effect not on the increase in TA activity when imagining the movement of the ipsilateral foot, but on the decrease in TA activity at rest. The revealed effects are apparently important for the formation of adequate coordination patterns of control signals from the CNS and of muscle activity during the implementation of movements and can be used in the clinical rehabilitation of motor activity using the cortico-spinal neurointerface.

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Brain–Computer Interface for Controlling Lower-Limb Exoskeletons

Cited by 3 publications

References 45 publications

Analysis of Cerebral and Muscle Activity during Control of a Corticospinal Neural Interface

Analysis of Cerebral and Muscle Activity during Control of a Corticospinal Neural Interface

Brain–computer interface: trend, challenges, and threats

Analysis of Brain and Muscle Activity During Control of Brain-Spine Neurointerface

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