Motor Restoration Based on the Brain–Machine Interface Using Brain Surface Electrodes: Real-Time Robot Control and a Fully Implantable Wireless System

The brain-machine interface (BMI) enables us to control machines and to communicate with others, not with the use of input devices, but through the direct use of brain signals. This chapter describes the integrative approach the authors used to develop a BMI system with brain surface electrodes for real-time robotic arm control in severely disabled people, such as amyotrophic lateral sclerosis patients. This integrative BMI approach includes effective brain signal recording, accurate neural decoding, robust robotic control, a wireless and fully implantable device, and a noninvasive evaluation of surgical indications.

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Electroencephalography-Based Real-Time Cortical Monitoring System That Uses Hierarchical Bayesian Estimations for the Brain–Machine Interface

Journal of Clinical Neurophysiology ◽

10.1097/wnp.0000000000000064 ◽

2014 ◽

Vol 31 (3) ◽

pp. 218-228 ◽

Cited By ~ 1

Author(s):

Kyuwan Choi

Keyword(s):

Real Time ◽

Monitoring System ◽

Brain Machine Interface ◽

Hierarchical Bayesian ◽

Machine Interface ◽

Bayesian Estimations ◽

The Brain

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Brain–Machine Interface Using Brain Surface Electrodes

Technological Advancements in Biomedicine for Healthcare Applications - Advances in Bioinformatics and Biomedical Engineering ◽

10.4018/978-1-4666-2196-1.ch036 ◽

2012 ◽

pp. 362-374

Author(s):

Masayuki Hirata ◽

Takufumi Yanagisawa ◽

Kojiro Matsushita ◽

Hisato Sugata ◽

Yukiyasu Kamitani ◽

...

Keyword(s):

Integrative Approach ◽

Noninvasive Evaluation ◽

Brain Machine Interface ◽

Input Devices ◽

Surface Electrodes ◽

Brain Surface ◽

Brain Signals ◽

Machine Interface ◽

Robotic Arm Control ◽

Direct Use

The brain-machine interface (BMI) enables us to control machines and to communicate with others, not with the use of input devices, but through the direct use of brain signals. This chapter describes the integrative approach the authors used to develop a BMI system with brain surface electrodes for real-time robotic arm control in severely disabled people, such as amyotrophic lateral sclerosis patients. This integrative BMI approach includes effective brain signal recording, accurate neural decoding, robust robotic control, a wireless and fully implantable device, and a noninvasive evaluation of surgical indications.

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New Frontier: The Brain Machine Interface

Neuromodulation Technology at the Neural Interface ◽

10.1111/ner.12021 ◽

2013 ◽

Vol 16 (1) ◽

pp. 6-7 ◽

Cited By ~ 2

Author(s):

Andre Machado

Keyword(s):

Brain Machine Interface ◽

New Frontier ◽

Machine Interface ◽

The Brain

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Multi-Command Real-Time Brain Machine Interface Using SSVEP: Feasibility Study for Occipital and Forehead Sensor Locations

Advances in Cognitive Neurodynamics ICCN 2007 ◽

10.1007/978-1-4020-8387-7_135 ◽

2008 ◽

pp. 783-786 ◽

Cited By ~ 1

Author(s):

Pablo Martinez ◽

Hovagim Bakardjian ◽

Andrzej Cichocki

Keyword(s):

Real Time ◽

Feasibility Study ◽

Brain Machine Interface ◽

Machine Interface ◽

Sensor Locations

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NeuroRoots, a bio-inspired, seamless Brain Machine Interface device for long-term recording

10.1101/460949 ◽

2018 ◽

Cited By ~ 4

Author(s):

Marc D. Ferro ◽

Christopher M. Proctor ◽

Alexander Gonzalez ◽

Eric Zhao ◽

Andrea Slezia ◽

...

Keyword(s):

Neurological Diseases ◽

Signal Amplitude ◽

Brain Machine Interface ◽

Behavioral Experiments ◽

Adult Rats ◽

Integrative Level ◽

Machine Interface ◽

Freely Moving ◽

The Brain

AbstractMinimally invasive electrodes of cellular scale that approach a bio-integrative level of neural recording could enable the development of scalable brain machine interfaces that stably interface with the same neural populations over long period of time.In this paper, we designed and created NeuroRoots, a bio-mimetic multi-channel implant sharing similar dimension (10µm wide, 1.5µm thick), mechanical flexibility and spatial distribution as axon bundles in the brain. A simple approach of delivery is reported based on the assembly and controllable immobilization of the electrode onto a 35µm microwire shuttle by using capillarity and surface-tension in aqueous solution. Once implanted into targeted regions of the brain, the microwire was retracted leaving NeuroRoots in the biological tissue with minimal surgical footprint and perturbation of existing neural architectures within the tissue. NeuroRoots was implanted using a platform compatible with commercially available electrophysiology rigs and with measurements of interests in behavioral experiments in adult rats freely moving into maze. We demonstrated that NeuroRoots electrodes reliably detected action potentials for at least 7 weeks and the signal amplitude and shape remained relatively constant during long-term implantation.This research represents a step forward in the direction of developing the next generation of seamless brain-machine interface to study and modulate the activities of specific sub-populations of neurons, and to develop therapies for a plethora of neurological diseases.

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