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Translating the Brain-Machine Interface
Science Translational Medicine, 2013Brain-machine interfaces hold promise for the recovery of sensory and motor functions, but translational challenges remain.
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International Journal of Applied Research in Bioinformatics, 2020
The main purpose of the article is to provide the solution which allows the muscles to work in a situation when neural connection is corrupted either due to illness or injury, which usually causes paralysis. The research is on the interpretation of the brain signals based on the analysis of neurotransmitters and the transformation of this analysis into
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The main purpose of the article is to provide the solution which allows the muscles to work in a situation when neural connection is corrupted either due to illness or injury, which usually causes paralysis. The research is on the interpretation of the brain signals based on the analysis of neurotransmitters and the transformation of this analysis into
openaire +1 more source
Exploring Cognition with Brain–Machine Interfaces
Annual Review of Psychology, 2022Traditional brain–machine interfaces decode cortical motor commands to control external devices. These commands are the product of higher-level cognitive processes, occurring across a network of brain areas, that integrate sensory information, plan upcoming motor actions, and monitor ongoing movements. We review cognitive signals recently discovered in
Andersen, Richard A. +4 more
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Brain-machine interface: The challenge of neuroethics
The Surgeon, 2010The burning question surrounding the use of Brain-Machine Interface (BMI) devices is not merely whether they should be used, but how widely they should be used, especially in view of some ethical implications that arise concerning the social and legal aspects of human life.
Andreas K, Demetriades +3 more
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Information Capacity of Brain Machine Interfaces
2005 IEEE Engineering in Medicine and Biology 27th Annual Conference, 2005Brain Machine Interfaces (BMIs) are emerging as an important research area in clinical therapy. A large range of potential BMI control signals can be found in the brain. In increasing order of volume of brain tissue being sampled, these signal includes recordings of electric discharges from multi unit activity (MUA), summed population activity of ...
Gregory, Gage +2 more
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Selecting the signals for a brain–machine interface
Current Opinion in Neurobiology, 2004Brain-machine interfaces are being developed to assist paralyzed patients by enabling them to operate machines with recordings of their own neural activity. Recent studies show that motor parameters, such as hand trajectory, and cognitive parameters, such as the goal and predicted value of an action, can be decoded from the recorded activity to provide
Andersen, Richard A. +2 more
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Multiscale brain-machine interface decoders
2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2016Brain-machine interfaces (BMI) have vastly used a single scale of neural activity, e.g., spikes or electrocorticography (ECoG), as their control signal. New technology allows for simultaneous recording of multiple scales of neural activity, from spikes to local field potentials (LFP) and ECoG.
Han-Lin Hsieh, Maryam Modir Shanechi
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Invasive Brain Machine Interface System
2019Because of high spatial-temporal resolution of neural signals obtained by invasive recording, the invasive brain-machine interfaces (BMI) have achieved great progress in the past two decades. With success in animal research, BMI technology is transferring to clinical trials for helping paralyzed people to restore their lost motor functions.
Yile, Jin +4 more
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Prerequesites for symbiotic brain-machine interfaces
2009 IEEE International Conference on Systems, Man and Cybernetics, 2009Recent advancements in the neuroscience and engineering of Brain-Machine Interfaces are providing a blueprint for how new co-adaptive designs based on reinforcement learning change the nature of a user's ability to accomplish tasks that were not possible using static methodologies.
Justin C. Sanchez +1 more
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