Enhancing Selectivity of Minimally Invasive Peripheral Nerve Interfaces Using Combined Stimulation and High Frequency Block: from Design to Application
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Acceptability Study of A3-K3 Robotic Architecture for a Neurorobotics Painting
ORIGINAL RESEARCH published: 10 January 2019 doi: 10.3389/fnbot.2018.00081 Acceptability Study of A3-K3 Robotic Architecture for a Neurorobotics Painting Salvatore Tramonte 1*, Rosario Sorbello 1*, Christopher Guger 2 and Antonio Chella 1,3 1 RoboticsLab, Department of Industrial and Digital Innovation (DIID), Universitá di Palermo, Palermo, Italy, 2 G.tec Medical Engineering GmbH, Schiedlberg, Austria, 3 ICAR-CNR, Palermo, Italy In this paper, authors present a novel architecture for controlling an industrial robot via Brain Computer Interface. The robot used is a Series 2000 KR 210-2. The robotic arm was fitted with DI drawing devices that clamp, hold and manipulate various artistic media like brushes, pencils, pens. User selected a high-level task, for instance a shape or movement, using a human machine interface and the translation in robot movement was entirely demanded to the Robot Control Architecture defining a plan to accomplish user’s task. The architecture was composed by a Human Machine Interface based on P300 Brain Computer Interface and a robotic architecture composed by a deliberative layer and a reactive layer to translate user’s high-level command in a stream of movement for robots joints. To create a real-case scenario, the architecture was Edited by: Ganesh R. Naik, presented at Ars Electronica Festival, where the A3-K3 architecture has been used for Western Sydney University, Australia painting. Visitors completed a survey to address 4 self-assessed different dimensions Reviewed by: related to human-robot interaction: the technology knowledge, the personal attitude, the Calogero Maria Oddo, innovativeness and the satisfaction. The obtained results have led to further exploring the Scuola Sant’Anna di Studi Avanzati, Italy border of human-robot interaction, highlighting the possibilities of human expression in Valery E. -
Biomed Research International Special Issue on Brain Computer
BioMed Research International Special Issue on Brain Computer Interface Systems for Neurorobotics: Methods and Applications CALL FOR PAPERS Brain computer interface (BCI) systems establish a direct communication between Lead Guest Editor the brain and an external device. ese systems can be used for entertainment, to Victor H. C. De Albuquerque, improve the quality of life of patients and to control Virtual Reality applications, Universidade de Fortaleza, Fortaleza, industrial machines, and robots. In the neuroscience eld such as in neuroreha- Brazil bilitation, BCIs are integrated into controlled virtual environments used for the [email protected] treatment of disability, for example, cerebral palsy, Down syndrome, and depression. Its aim is to promote a recovery of brain function lost due to a lesion through Guest Editors noninvasive brain stimulation (brain modulation) in a more accurate and faster Robertas Damaševičius, Kaunas manner than the traditional techniques. Neurorobotics combines BCIs with robotics University of Technology, Kaunas, aiming to develop articial limbs, which can act as real members of human body Lithuania being controlled from a brain-machine interface. With the advancement of a better [email protected] understanding of how our brain works, new realistic computational algorithms are being considered, making it possible to simulate and model specic brain functions Nuno M. Garcia, University of Beira for the development of new Computational Intelligence algorithms and, nally, BCI Interior, Covilhã, Portugal for mobile devices/apps. [email protected] As an augmentative communication channel, BCI has already attracted considerable Plácido R. Pinheiro, Universidade de research interest thanks to recent advances in neurosciences, wearable biosensors, Fortaleza, Fortaleza, Brazil and data mining. -
Ethical and Social Aspects of Neurorobotics
Science and Engineering Ethics https://doi.org/10.1007/s11948-020-00248-8 ORIGINAL RESEARCH/SCHOLARSHIP Ethical and Social Aspects of Neurorobotics Christine Aicardi2 · Simisola Akintoye3 · B. Tyr Fothergill1 · Manuel Guerrero4,5 · Gudrun Klinker6 · William Knight1 · Lars Klüver7 · Yannick Morel8 · Fabrice O. Morin6 · Bernd Carsten Stahl1 · Inga Ulnicane1 © The Author(s) 2020 Abstract The interdisciplinary feld of neurorobotics looks to neuroscience to overcome the limitations of modern robotics technology, to robotics to advance our understand- ing of the neural system’s inner workings, and to information technology to develop tools that support those complementary endeavours. The development of these tech- nologies is still at an early stage, which makes them an ideal candidate for proac- tive and anticipatory ethical refection. This article explains the current state of neu- rorobotics development within the Human Brain Project, originating from a close collaboration between the scientifc and technical experts who drive neurorobotics innovation, and the humanities and social sciences scholars who provide contextu- alising and refective capabilities. This article discusses some of the ethical issues which can reasonably be expected. On this basis, the article explores possible gaps identifed within this collaborative, ethical refection that calls for attention to ensure that the development of neurorobotics is ethically sound and socially acceptable and desirable. Keywords Neurorobotics · Ethics · Responsible Research and Innovation -
Computational Neuroscience Meets Optogenetics: Unlocking the Brain’S Secrets
Health & Medicine ︱ Prof Simon Schultz and Dr Konstantin Nikolic Computational neuroscience meets optogenetics: Unlocking the brain’s secrets Working at the interface omposed of billions of specialised responsible for perception, action Simplified models allow researchers to study how the geometry of a neuron’s “dendritic tree” affects its ability to process information. between engineering and nerve cells (called neurons) wired and memory. But this is changing. neuroscience, Professor Simon C together in complex, intricate Schultz and Dr Konstantin webs, the brain is inherently challenging LET THERE BE LIGHT Nikolic at Imperial College to study. Neurons communicate with A powerful new tool (invented by Boyden of Neurotechnology and Director of SHEDDING LIGHT ON THE BRAIN AN INSIGHT INTO NEURONAL GAIN London are developing tools each other by transmitting electrical and and Deisseroth just a little over a decade the Imperial Centre of Excellence in Their innovative approach uses Using two biophysical models of to help us understand the chemical signals along neural circuits: ago) allows researchers to map the brain’s Neurotechnology, Dr Konstantin Nikolic, sophisticated two-photon microscopy, neurons, genetically-modified to include intricate workings of the brain. signals that vary both in space and time. connections, giving unprecedented Associate Professor in the Department optogenetics and electrophysiology two distinct light-sensitive proteins Combining a revolutionary Until now, technical limitations in the access to the workings of the brain. Its of Electrical and Electronic Engineering, to measure (and disturb) patterns of (called opsins): channelrhodopsin-2 technology – optogenetics available research methods to study the impressive resolution enables precise and Dr Sarah Jarvis are taking a unique neuronal activity in vivo (in living tissue). -
Implantable Microelectrodes on Soft Substrate with Nanostructured Active Surface for Stimulation and Recording of Brain Activities Valentina Castagnola
Implantable microelectrodes on soft substrate with nanostructured active surface for stimulation and recording of brain activities Valentina Castagnola To cite this version: Valentina Castagnola. Implantable microelectrodes on soft substrate with nanostructured active sur- face for stimulation and recording of brain activities. Micro and nanotechnologies/Microelectronics. Universite Toulouse III Paul Sabatier, 2014. English. tel-01137352 HAL Id: tel-01137352 https://hal.archives-ouvertes.fr/tel-01137352 Submitted on 31 Mar 2015 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. THÈSETHÈSE En vue de l’obtention du DOCTORAT DE L’UNIVERSITÉ DE TOULOUSE Délivré par : l’Université Toulouse 3 Paul Sabatier (UT3 Paul Sabatier) Présentée et soutenue le 18/12/2014 par : Valentina CASTAGNOLA Implantable Microelectrodes on Soft Substrate with Nanostructured Active Surface for Stimulation and Recording of Brain Activities JURY M. Frédéric MORANCHO Professeur d’Université Président de jury M. Blaise YVERT Directeur de recherche Rapporteur Mme Yael HANEIN Professeur d’Université Rapporteur M. Pascal MAILLEY Directeur de recherche Examinateur M. Christian BERGAUD Directeur de recherche Directeur de thèse Mme Emeline DESCAMPS Chargée de Recherche Directeur de thèse École doctorale et spécialité : GEET : Micro et Nanosystèmes Unité de Recherche : Laboratoire d’Analyse et d’Architecture des Systèmes (UPR 8001) Directeur(s) de Thèse : M. -
ECE 5070: Neuroengineering and Neuroprosthetics
ECE 5070: Neuroengineering and Neuroprosthetics Course Description An overview of the broad field of Neuroengineering for graduate and senior undergraduate students with engineering or neuroscience backgrounds. Focusing on neural interfaces and prostheses, this course covers from basic neurophysiology and computational neuronal models to advanced neural interfaces and prostheses currently being actively developed in the field. Transcript Abbreviation: Neur Eng & Prosth Grading Plan: Letter Grade Course Deliveries: Classroom Course Levels: Undergrad, Graduate Student Ranks: Junior, Senior, Masters, Doctoral Course Offerings: Autumn Flex Scheduled Course: Never Course Frequency: Even Years Course Length: 14 Week Credits: 3.0 Repeatable: No Time Distribution: 3.0 hr Lec Expected out-of-class hours per week: 6.0 Graded Component: Lecture Credit by Examination: No Admission Condition: No Off Campus: Never Campus Locations: Columbus Prerequisites and Co-requisites: Prereq: 3050 or BME 3703; or Neurosc 3010; or Grad standing in Engineering or Neurosc. Exclusions: Not open to students with credit for 5194.03 or Neurosc 5070. Cross-Listings: Cross-listed in Neurosc. Course Rationale: Introduce students a vibrant, interdisciplinary field which integrates engineering and neuroscience principles for treating neurological disorders. The course is required for this unit's degrees, majors, and/or minors: No The course is a GEC: No The course is an elective (for this or other units) or is a service course for other units: Yes Subject/CIP Code: 14.1001 Subsidy Level: Doctoral Course Programs Abbreviation Description CpE Computer Engineering EE Electrical Engineering Course Goals Master principles of neural interfaces. Be competent with computational neural models. Be competent with design of common neuroprostheses. -
New Technologies for Human Robot Interaction and Neuroprosthetics
University of Plymouth PEARL https://pearl.plymouth.ac.uk Faculty of Science and Engineering School of Engineering, Computing and Mathematics 2017-07-01 Human-Robot Interaction and Neuroprosthetics: A review of new technologies Cangelosi, A http://hdl.handle.net/10026.1/9872 10.1109/MCE.2016.2614423 IEEE Consumer Electronics Magazine All content in PEARL is protected by copyright law. Author manuscripts are made available in accordance with publisher policies. Please cite only the published version using the details provided on the item record or document. In the absence of an open licence (e.g. Creative Commons), permissions for further reuse of content should be sought from the publisher or author. CEMAG-OA-0004-Mar-2016.R3 1 New Technologies for Human Robot Interaction and Neuroprosthetics Angelo Cangelosi, Sara Invitto Abstract—New technologies in the field of neuroprosthetics and These developments in neuroprosthetics are closely linked to robotics are leading to the development of innovative commercial the recent significant investment and progress in research on products based on user-centered, functional processes of cognitive neural networks and deep learning approaches to robotics and neuroscience and perceptron studies. The aim of this review is to autonomous systems [2][3]. Specifically, one key area of analyze this innovative path through the description of some of the development has been that of cognitive robots for human-robot latest neuroprosthetics and human-robot interaction applications, in particular the Brain Computer Interface linked to haptic interaction and assistive robotics. This concerns the design of systems, interactive robotics and autonomous systems. These robot companions for the elderly, social robots for children with issues will be addressed by analyzing developmental robotics and disabilities such as Autism Spectrum Disorders, and robot examples of neurorobotics research. -
Brain-Machine Interface: from Neurophysiology to Clinical
Neurophysiology of Brain-Machine Interface Rehabilitation Matija Milosevic, Osaka University - Graduate School of Engineering Science - Japan. Abstract— Long-lasting cortical re-organization or II. METHODS neuroplasticity depends on the ability to synchronize the descending (voluntary) commands and the successful execution Stimulation of muscles with FES was delivered using a of the task using a neuroprosthetic. This talk will discuss the constant current biphasic waveform with a 300μs pulse width neurophysiological mechanisms of brain-machine interface at 50 Hz frequency via surface electrodes. First, repetitive (BMI) controlled neuroprosthetics with the aim to provide transcranial magnetic stimulation (rTMS) intermittent theta implications for development of technologies for rehabilitation. burst protocol (iTBS) was used to induce cortical facilitation. iTBS protocol consists of pulses delivered intermittently at a I. INTRODUCTION frequency of 50 Hz and 5 Hz for a total of 200 seconds. Functional electrical stimulation (FES) neuroprosthetics Moreover, motor imagery protocol was used to display a can be used to applying short electric impulses over the virtual reality hand opening and closing sequence of muscles or the nerves to generate hand muscle contractions movements (hand flexion/extension) while subject’s hands and functional movements such as reaching and grasping. remained at rest and out of the visual field. Our work has shown that recruitment of muscles using FES goes beyond simple contractions, with evidence suggesting III. RESULTS re-organization of the spinal reflex networks and cortical- Our first results showed that motor imagery can affect level changes after the stimulating period [1,2]. However, a major challenge remains in achieving precise temporal corticospinal facilitation in a phase-dependent manner, i.e., synchronization of voluntary commands and activation of the hand flexor muscles during hand closing and extensor muscles [3]. -
Practical and Ethical Issues at the Intersection of Brain Science and Society
Emerging Neurotechnologies: Practical and Ethical Issues at the Intersection of Brain Science and Society James Giordano PhD Departments of Neurology and Biochemistry Neuroethics Studies Program, Pellegrino Center for Clinical Bioethics Georgetown University Medical Center Washington, DC, USA and EU-Human Brain Project SP-12 Uppsala University, Sweden Neuroscience… • Huge leaps using technology to study and understand how nervous systems and brains are structured and function. Allowed understanding at certain levels of causality: – Formal: Overall “workings” of biological systems – Material: Structure and functional roles of neurons, glia But not at others… – Efficient: How “grey stuff” actually makes “great stuff” – Final: For what? To what “ends”? Core Questions... What do we do with the information and capability we have? What do we do about the information and capability we don’t? Questions toward Innovation • Tools to Theory • Theory to Tools... ...to Theory AISC Approach Brain Science on the World Stage • EU Human Brain Project • US BRAIN initiative • China Brain Project • Japan Brain Project • Global NeuroS/T Economic Predictions 2025 – Asia – US/Western Europe – South America Neuroscience and Technologies (NeuroS/T) • Assessment – Biomarkers – Genetics/genomics – Imaging – Brain modeling/mapping • Interventional – Technopharmaceutics – P-Stim – Neurofeedback – Transcranial Modulation – Deep Brain Stimulation – BCI – Neuroprosthetics • Derivative – -Artificial neural networks – -AI technologies A-3: Actual Ability to Assess...Access...Affect To What Effect(s) and Ends? Neuroimaging – PET – CT – MR – fMR – DTI – MEG/qEEG Can we Scan the Brain to Depict Consciousness and/or “Read” Minds? text copyright, J. Giordano, 2014 Neurogenetics – Genotyping – Phenotyping – Proteomics – Genetic Intervention(s) Can we “Predict” or “Create” Present and Future “Selves”? text copyright, J. -
Noninvasive Electroencephalography Equipment for Assistive, Adaptive, and Rehabilitative Brain–Computer Interfaces: a Systematic Literature Review
sensors Systematic Review Noninvasive Electroencephalography Equipment for Assistive, Adaptive, and Rehabilitative Brain–Computer Interfaces: A Systematic Literature Review Nuraini Jamil 1 , Abdelkader Nasreddine Belkacem 2,* , Sofia Ouhbi 1 and Abderrahmane Lakas 2 1 Department of Computer Science and Software Engineering, College of Information Technology, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates; [email protected] (N.J.); sofi[email protected] (S.O.) 2 Department of Computer and Network Engineering, College of Information Technology, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates; [email protected] * Correspondence: [email protected] Abstract: Humans interact with computers through various devices. Such interactions may not require any physical movement, thus aiding people with severe motor disabilities in communicating with external devices. The brain–computer interface (BCI) has turned into a field involving new elements for assistive and rehabilitative technologies. This systematic literature review (SLR) aims to help BCI investigator and investors to decide which devices to select or which studies to support based on the current market examination. This examination of noninvasive EEG devices is based on published BCI studies in different research areas. In this SLR, the research area of noninvasive Citation: Jamil, N.; Belkacem, A.N.; BCIs using electroencephalography (EEG) was analyzed by examining the types of equipment used Ouhbi, S.; Lakas, A. Noninvasive for assistive, adaptive, and rehabilitative BCIs. For this SLR, candidate studies were selected from Electroencephalography Equipment the IEEE digital library, PubMed, Scopus, and ScienceDirect. The inclusion criteria (IC) were limited for Assistive, Adaptive, and to studies focusing on applications and devices of the BCI technology. -
Subproject 10: Neurorobotics
Co-funded by the European Union Subproject 10: Neurorobotics Deliverable D10.7.2 Revised Report, 6 Oct 2017 D10.7.2 (D60.2 D25, SGA1 M12) ACCEPTED 20171108.docx PU = Public 08-Nov-2017 Page 1 of 124 Co-funded by the European Union Project Number: 720270 Project Title: Human Brain Project SGA1 Document Title: D10.7.2 SP10 Neurorobotics Platform - Results for SGA1 Period 1 Document Filename: D10.7.2 (D60.2 D25, SGA1 M12) ACCEPTED 20171108.docx Deliverable Number: SGA1 D10.7.2 Deliverable Type: Report Work Package(s): All WPs in SP10 Dissemination Level: PU = Public Planned Delivery SGA1 M12 / 31 Mar 2017 Date: Submitted: 31 May 2017 (M14), Resubmitted 6 Oct 2017 (M19), Accepted 08 Nov Actual Delivery Date: 2017 Authors: Alois KNOLL, TUM (P56), Marc-Oliver Gewaltig, EPFL (P1) Compiling Editors: Florian RÖHRBEIN, TUM (P56) Contributors: All Task leaders and their representatives SciTechCoord Re- EPFL (P1): Jeff MULLER, Martin TELEFONT, Marie-Elisabeth COLIN view: UHEI (P47): Martina SCHMALHOLZ, Sabine SCHNEIDER Editorial Review: EPFL (P1): Guy WILLIS, Colin McKINNON Abstract: This document describes the progress made in the first half of the first SGA. Keywords: Neurorobotics, virtual robotics, in silico experiments D10.7.2 (D60.2 D25, SGA1 M12) ACCEPTED 20171108.docx PU = Public 08-Nov-2017 Page 2 of 124 Co-funded by the European Union Table of Contents 1. Preamble ........................................................................................................ 8 2. SP Leader’s Overview........................................................................................ -
Editorial Brain Computer Interface Systems for Neurorobotics: Methods and Applications
Hindawi BioMed Research International Volume 2017, Article ID 2505493, 2 pages https://doi.org/10.1155/2017/2505493 Editorial Brain Computer Interface Systems for Neurorobotics: Methods and Applications Victor Hugo C. de Albuquerque,1 Robertas DamaševiIius,2 Nuno M. Garcia,3 Plácido Rogério Pinheiro,1 and Pedro P. Rebouças Filho4 1 Programa de Pos´ Graduac¸ao˜ em Informatica´ Aplicada, Laboratorio´ de Bioinformatica,´ Universidade de Fortaleza, Fortaleza, CE, Brazil 2Department of Software Engineering, Kaunas University of Technology, Kaunas, Lithuania 3Department of Informatics, Instituto de Telecomunicac¸oes˜ and ALLab Assisted Living Computing and Telecommunications Laboratory,UniversidadedaBeiraInterior,Covilha,˜ Portugal 4Laboratorio´ de Processamento de Imagens e Simulac¸ao˜ Computacional, Instituto Federal de Educac¸ao,˜ Cienciaˆ e Tecnologia do Ceara,´ Maracanau,´ CE, Brazil Correspondence should be addressed to Victor Hugo C. de Albuquerque; [email protected] Received 7 August 2017; Accepted 7 August 2017; Published 30 October 2017 Copyright © 2017 Victor Hugo C. de Albuquerque et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Brain computer interface (BCI) systems establish a direct data mining. However, to overcome numerous challenges the communication between the brain and an external device. BCI technology still requires research in high-performance These systems can be used for entertainment, to improve the and robust signal processing and machine learning algo- quality of life of patients and to control virtual and augmented rithmstoproduceareliableandstablecontrolsignalfrom reality applications, industrial machines, and robots. In the nonstationary brain signals to allow development of real- neuroscience field such as in neurorehabilitation, BCIs are life BCI systems usable across many individuals.