Next Generation Microscale Wireless Implant System for High-Density, Multi-areal, Closed-Loop Brain Computer Interfaces

2021 ◽  
pp. 39-51
Author(s):  
Farah Laiwalla ◽  
Vincent W. Leung ◽  
Jihun Lee ◽  
Patrick Mercier ◽  
Peter Asbeck ◽  
...  
Keyword(s):  
Closed Loop ◽  
High Density ◽  
Brain Computer Interfaces ◽  
Next Generation ◽  
Computer Interfaces ◽  
Implant System

The Effects of Closed-Loop Medical Devices on the Autonomy and Accountability of Persons and Systems

2016 ◽  
Vol 25 (4) ◽  
pp. 623-633 ◽  
Author(s):  
PHILIPP KELLMEYER ◽  
THOMAS COCHRANE ◽  
OLIVER MÜLLER ◽  
CHRISTINE MITCHELL ◽  
TONIO BALL ◽  
...  
Keyword(s):  
Medical Devices ◽  
Closed Loop ◽  
Personal Autonomy ◽  
Task Force ◽  
Legal Framework ◽  
Brain Computer Interfaces ◽  
Medical Systems ◽  
The Public ◽  
Computer Interfaces ◽  
Patient Advocacy Groups

Abstract:Closed-loop medical devices such as brain-computer interfaces are an emerging and rapidly advancing neurotechnology. The target patients for brain-computer interfaces (BCIs) are often severely paralyzed, and thus particularly vulnerable in terms of personal autonomy, decisionmaking capacity, and agency. Here we analyze the effects of closed-loop medical devices on the autonomy and accountability of both persons (as patients or research participants) and neurotechnological closed-loop medical systems. We show that although BCIs can strengthen patient autonomy by preserving or restoring communicative abilities and/or motor control, closed-loop devices may also create challenges for moral and legal accountability. We advocate the development of a comprehensive ethical and legal framework to address the challenges of emerging closed-loop neurotechnologies like BCIs and stress the centrality of informed consent and refusal as a means to foster accountability. We propose the creation of an international neuroethics task force with members from medical neuroscience, neuroengineering, computer science, medical law, and medical ethics, as well as representatives of patient advocacy groups and the public.

Predicting Motor Intentions with Closed-Loop Brain-Computer Interfaces

2017 ◽  
pp. 79-90
Author(s):  
Matthias Schultze-Kraft ◽  
Mario Neumann ◽  
Martin Lundfall ◽  
Patrick Wagner ◽  
Daniel Birman ◽  
...  
Keyword(s):  
Closed Loop ◽  
Brain Computer Interfaces ◽  
Computer Interfaces

scholarly journals Advantages of closed-loop calibration in intracortical brain–computer interfaces for people with tetraplegia

2013 ◽  
Vol 10 (4) ◽  
pp. 046012 ◽  
Author(s):  
Beata Jarosiewicz ◽  
Nicolas Y Masse ◽  
Daniel Bacher ◽  
Sydney S Cash ◽  
Emad Eskandar ◽  
...  
Keyword(s):  
Closed Loop ◽  
Brain Computer Interfaces ◽  
Computer Interfaces

scholarly journals On the suitability of near-infrared (NIR) systems for next-generation brain–computer interfaces

2004 ◽  
Vol 25 (4) ◽  
pp. 815-822 ◽  
Author(s):  
Shirley Coyle ◽  
Tomás Ward ◽  
Charles Markham ◽  
Gary McDarby
Keyword(s):  
Near Infrared ◽  
Brain Computer Interfaces ◽  
Next Generation ◽  
Computer Interfaces

A Study of Frontal Signals in Brain Computer Interfaces: Interpretation of EEG & FNIRS

2020 ◽  
pp. 136-142
Author(s):  
S. Srilekha ◽  
B. Vanathi
Keyword(s):  
Infrared Spectroscopy ◽  
Healthy Subject ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Economic Conditions ◽  
Brain Computer Interfaces ◽  
Functional Near Infrared Spectroscopy ◽  
Computer Interfaces ◽  
Rehabilitation Devices

This paper focuses on electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) comparison to help the rehabilitation patients. Both methods have unique techniques and placement of electrodes. Usage of signals are different in application based on the economic conditions. This study helps in choosing the signal for the betterment of analysis. Ten healthy subject datasets of EEG & FNIRS are taken and applied to plot topography separately. Accuracy, Sensitivity, peaks, integral areas, etc are compared and plotted. The main advantages of this study are to prompt their necessities in the analysis of rehabilitation devices to manage their life as a typical individual.

Automated System for Epileptic Seizures Prediction based on Multi-Channel Recordings of Electrical Brain Activity

2018 ◽  
pp. 115-122 ◽  
Author(s):  
V. A. Maksimenko ◽  
A. A. Harchenko ◽  
A. Lüttjohann
Keyword(s):  
Epileptic Seizure ◽  
Brain Activity ◽  
Epileptic Seizures ◽  
Automated System ◽  
Brain Computer Interfaces ◽  
Electrical Brain Activity ◽  
Computer Interfaces ◽  
Prediction And Prevention ◽  
The Brain

Introduction: Now the great interest in studying the brain activity based on detection of oscillatory patterns on the recorded data of electrical neuronal activity (electroencephalograms) is associated with the possibility of developing brain-computer interfaces. Braincomputer interfaces are based on the real-time detection of characteristic patterns on electroencephalograms and their transformation  into commands for controlling external devices. One of the important areas of the brain-computer interfaces application is the control of the pathological activity of the brain. This is in demand for epilepsy patients, who do not respond to drug treatment.Purpose: A technique for detecting the characteristic patterns of neural activity preceding the occurrence of epileptic seizures.Results:Using multi-channel electroencephalograms, we consider the dynamics of thalamo-cortical brain network, preceded the occurrence of an epileptic seizure. We have developed technique which allows to predict the occurrence of an epileptic seizure. The technique has been implemented in a brain-computer interface, which has been tested in-vivo on the animal model of absence epilepsy.Practical relevance:The results of our study demonstrate the possibility of epileptic seizures prediction based on multichannel electroencephalograms. The obtained results can be used in the development of neurointerfaces for the prediction and prevention of seizures of various types of epilepsy in humans. 

Sign in / Sign up

Export Citation Format

Share Document