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Author: Briana Landavazo Publisher: ISBN: Category : Languages : en Pages : 132
Book Description
Due to the hands-free, non-invasive nature of electroencephalography (EEG) based control, research into brain-computer interface (BCI) systems has been a topic of interest in robotics applications. BCI systems have been studied in several applications including designing simple prosthesis, wheelchairs and virtual navigation, but its scope has often been constrained by several limiting factors. These factors include the need for lengthy training per each specific action desired, poor accuracy when dealing with multiple potential outputs and differences in brain signal behavior for each participant that make finding patterns that work for all individual test subjects a challenge. This research will focus on a method of controlling a robotic arm and dexterous hand system using a combination of BCI and machine learning to quickly train a model to recognize patterns from raw EEG data from a specific individual. This model will be tailored to that individual, allowing the subject to send a high-level input to initiate an adaptive command. The high-level adaptive command considers not only a broad intention of a desired action through EEG signals, but also sensor inputs and other user inputs to perform a desired action effectively. Research will be presented on a system wide implementation of a prototype of this design. The proposed brain-controlled robot is comprised of several major subsystems including the high level BCI input, a 4-degree of freedom (DOF) robot arm system with microcontroller, a 3-wheel omnidirectional mobile platform, a 9-DOF Brunel robot hand, and a MATLAB interface with an interactive GUI. The system receives inputs from an Xbox Kinect color and depth camera and respective microcontrollers that communicate with each other through serial ports, Bluetooth, and wired connections and with the environment through a force sensor, a Kinect depth sensor, and inputs from a MATLAB GUI and Xbox controller. This thesis research demonstrates the development of this multi degree of freedom integrated mobile robotic arm and gripper system that uses EEG data, Kinect image and depth inputs, and a force sensor to successfully control its operation after being trained using one machine learning session. A case study was performed where a subject was asked to record at least 25 sessions of each BCI command. 25% of the data from each test set was set aside for testing purposes. For a total of four different cases, an accuracy of 80% was reached whereas for five different cases, an accuracy of 76% was obtained. Motion of the robotic arm was simulated in MATLAB and successfully replicated in the robot prototype for grabbing different sized objects.
Author: Briana Landavazo Publisher: ISBN: Category : Languages : en Pages : 132
Book Description
Due to the hands-free, non-invasive nature of electroencephalography (EEG) based control, research into brain-computer interface (BCI) systems has been a topic of interest in robotics applications. BCI systems have been studied in several applications including designing simple prosthesis, wheelchairs and virtual navigation, but its scope has often been constrained by several limiting factors. These factors include the need for lengthy training per each specific action desired, poor accuracy when dealing with multiple potential outputs and differences in brain signal behavior for each participant that make finding patterns that work for all individual test subjects a challenge. This research will focus on a method of controlling a robotic arm and dexterous hand system using a combination of BCI and machine learning to quickly train a model to recognize patterns from raw EEG data from a specific individual. This model will be tailored to that individual, allowing the subject to send a high-level input to initiate an adaptive command. The high-level adaptive command considers not only a broad intention of a desired action through EEG signals, but also sensor inputs and other user inputs to perform a desired action effectively. Research will be presented on a system wide implementation of a prototype of this design. The proposed brain-controlled robot is comprised of several major subsystems including the high level BCI input, a 4-degree of freedom (DOF) robot arm system with microcontroller, a 3-wheel omnidirectional mobile platform, a 9-DOF Brunel robot hand, and a MATLAB interface with an interactive GUI. The system receives inputs from an Xbox Kinect color and depth camera and respective microcontrollers that communicate with each other through serial ports, Bluetooth, and wired connections and with the environment through a force sensor, a Kinect depth sensor, and inputs from a MATLAB GUI and Xbox controller. This thesis research demonstrates the development of this multi degree of freedom integrated mobile robotic arm and gripper system that uses EEG data, Kinect image and depth inputs, and a force sensor to successfully control its operation after being trained using one machine learning session. A case study was performed where a subject was asked to record at least 25 sessions of each BCI command. 25% of the data from each test set was set aside for testing purposes. For a total of four different cases, an accuracy of 80% was reached whereas for five different cases, an accuracy of 76% was obtained. Motion of the robotic arm was simulated in MATLAB and successfully replicated in the robot prototype for grabbing different sized objects.
Author: Alyssa Marie Batula Publisher: ISBN: Category : Brain-computer interfaces Languages : en Pages : 300
Book Description
The ability to direct a robot using only human thoughts could provide a powerful mechanism for human-robot interaction with a wide range of potential applications including medical robotics, search-and-rescue operations, and industrial manufacturing. Brain-computer interfaces (BCIs) are systems that allow the user to control a computer with only their thoughts, providing a promising research area for new methods of robotic control. They could be used to control the navigation of a robotic wheelchair, an assistive or telepresence robot that performs errands, or even the movement of a prosthetic limb. In this work I present the design and evaluation of the first BCI to use four imagined movements recorded via functional near-infrared spectroscopy (fNIRS) to control both a virtual and a physical robot. The BCI is used to navigate the robot to a goal location in a room, a prototype and initial step towards remote control of a telepresence or assistive robot. Four imagined movement tasks (tapping of the left hand, right hand, left foot, and right foot) are mapped to high-level commands (turn left, turn right, walk forwards, walk backwards) to direct the robot. The ability to reliably distinguish multiple mental tasks is essential for use in a practical BCI. In an offline analysis I compare the activation patterns generated during both motor imagery and motor execution (actual movement). This is the first analysis of the activation patterns recorded via fNIRS separately for left and right foot motor imagery tasks. Signal processing, feature extraction, and machine learning methods are integral parts of BCI design. In an additional offline analysis I compare classification results using eight methods of signal preprocessing that have been suggested for use in fNIRS BCIs. I also provide comparisons of two commonly-used classifiers in BCIs as well as feed-forward and convolutional neural networks. Additionally I present the results of a five-class classification task, adding a resting state to the four motor imagery tasks, which could potentially increase the number of inputs available to the BCI.
Author: Swagata Das Publisher: ISBN: 9789811330995 Category : Arduino (Programmable controller) Languages : en Pages :
Book Description
This book discusses the basic requirements and constraints in building a brain-computer interaction system. These include the technical requirements for building the signal processing module and the acquisition module. The major aspects to be considered when designing a signal acquisition module for a brain-computer interaction system are the human brain, types and applications of brain-computer systems, and the basics of EEG (electroencephalogram) recording. The book also compares the algorithms that have been and that can be used to design the signal processing module of brain-computer interfaces, and describes the various EEG-acquisition devices available and compares their features and inadequacies. Further, it examines in detail the use of Emotiv EPOC (an EEG acquisition module developed by Emotiv) to build a complete brain-computer interaction system for driving robots using a neural network classification module.
Author: Bernhard Graimann Publisher: Springer Science & Business Media ISBN: 3642020917 Category : Medical Languages : en Pages : 397
Book Description
A brain-computer interface (BCI) establishes a direct output channel between the human brain and external devices. BCIs infer user intent via direct measures of brain activity and thus enable communication and control without movement. This book, authored by experts in the field, provides an accessible introduction to the neurophysiological and signal-processing background required for BCI, presents state-of-the-art non-invasive and invasive approaches, gives an overview of current hardware and software solutions, and reviews the most interesting as well as new, emerging BCI applications. The book is intended not only for students and young researchers, but also for newcomers and other readers from diverse backgrounds keen to learn about this vital scientific endeavour.
Author: Rajesh P. N. Rao Publisher: Cambridge University Press ISBN: 0521769418 Category : Computers Languages : en Pages : 337
Book Description
The idea of interfacing minds with machines has long captured the human imagination. Recent advances in neuroscience and engineering are making this a reality, opening the door to restoration and augmentation of human physical and mental capabilities. Medical applications such as cochlear implants for the deaf and neurally controlled prosthetic limbs for the paralyzed are becoming almost commonplace. Brain-computer interfaces (BCIs) are also increasingly being used in security, lie detection, alertness monitoring, telepresence, gaming, education, art, and human augmentation. This introduction to the field is designed as a textbook for upper-level undergraduate and first-year graduate courses in neural engineering or brain-computer interfacing for students from a wide range of disciplines. It can also be used for self-study and as a reference by neuroscientists, computer scientists, engineers, and medical practitioners. Key features include questions and exercises in each chapter and a supporting website.
Author: Fouad Sabry Publisher: One Billion Knowledgeable ISBN: 1005580081 Category : Computers Languages : en Pages : 97
Book Description
The idea of interfacing minds with computers has captured human imagination for a long time. Recent developments in neuroscience and engineering have made this concept a possibility, opening the door to restoring and potentially growing human physical and mental capabilities. Medical applications such as cochlear implants for deaf patients and deep brain stimulation for Parkinson's disease are becoming increasingly common. Brain-computer interfaces (BCIs) (also known as brain-machine interfaces or BMIs) are currently being explored in applications as diverse as defense, lie detection, alertness monitoring, telepresence, gaming, education, art, and human enhancement. By the end of reading this book, you will master the discussion about the following topics of Brain Computer Interface: Definitions UCLA and DARPA Neuro-Prosthetics Applications Neuromodulation History Electroencephalography (EEG) Brain Computer Interface challenge Brain/Neural Computer Interaction (BNCI) project Contingent Negative Variation (CNV) The Brain Computer Interface Society BCI Versus Neuro Prosthetics Animal Brain Computer Interface Research Phillip Kennedy's Research Yang Dan's Research Miguel Nicolelis' Research Donoghue, Schwartz, Andersen Research Carmena and colleagues Research Lebedev and colleagues Research General-Purpose Brain Computer Interface Research Framework Brain Machine Interface (BMI) Passive Brain Computer Interface Invasive Brain Computer Interfaces Treat Non-Congenital Blindness Restore Mobility in Disabled Individuals Partially invasive Brain Computer Interfaces Electrocorticography (ECoG) Light Reactive Imaging Brain Computer Interface Non-invasive Brain Computer Interface Non-Electroencephalography (EEG)-based brain–computer interface Pupil-Size Oscillation Functional Near Infrared Spectroscopy Electroencephalography (EEG)-based brain-computer interface Advanced Functional Neuroimaging Dry Active Electrode Array SSVEP Mobile Electroencephalography (EEG) Brain Computer Interface Cellular-based Brain Computer Interface Mobile Brain Computer Interface Devices Limitations Prosthesis and Regulation of the World Brain Computer Interface in Military Do It Yourself and Open-Source Brain Machine Interface Open Brain Programming Interface Reconstruction of Human Vision Brain Computer Interface Control Strategies in Neurogaming Motor Imagery Bio/Neurofeedback for Passive Brain Computer Interface Visual Evoked Potential (VEP) Synthetic telepathy/silent communication DARPA Silent Talk Objective Brain-Based Communication Using Imagined Speech First Direct Electronic Contact Experiment Conducted Between Two Humans' Nervous Systems Produce Morse Code Using Electroencephalography (EEG) Transmission of Electroencephalography (EEG) Signals Over the Internet Cell-Culture Brain Computer InterfaceS Caltech First Neurochip Artificial or Prosthetic Hippocampus Neurochip Rat Brain Neurons Fly an F-22 Fighter Jet Aircraft Simulator Ethical Considerations Current Brain Machine Interfacess Are Away from The Ethical Problems Brain Computer Interface In Medical and Pharmaceutical Research Low-cost Brain Computer Interface Sony 2006 NeuroSky 2007 OCZ 2008 Final Fantasy 2008 Uncle Milton Industries 2009 Emotiv 2009 Neurowear's "Necomimi" 2012 They Shall Walk 2014 Open-Source Brain Computer Interface 2016 Neuralink 2020 Future directions Disorders of consciousness (DOC) Motor Recovery Functional Brain Mapping Flexible Devices Neural Dust
Author: Georgios Konstantinos Karavas Publisher: ISBN: Category : Brain-computer interfaces Languages : en Pages : 93
Book Description
A robotic swarm can be defined as a large group of inexpensive, interchangeable robots with limited sensing and/or actuating capabilities that cooperate (explicitly or implicitly) based on local communications and sensing in order to complete a mission. Its inherent redundancy provides flexibility and robustness to failures and environmental disturbances which guarantee the proper completion of the required task. At the same time, human intuition and cognition can prove very useful in extreme situations where a fast and reliable solution is needed. This idea led to the creation of the field of Human-Swarm Interfaces (HSI) which attempts to incorporate the human element into the control of robotic swarms for increased robustness and reliability. The aim of the present work is to extend the current state-of-the-art in HSI by applying ideas and principles from the field of Brain-Computer Interfaces (BCI), which has proven to be very useful for people with motor disabilities. At first, a preliminary investigation about the connection of brain activity and the observation of swarm collective behaviors is conducted. After showing that such a connection may exist, a hybrid BCI system is presented for the control of a swarm of quadrotors. The system is based on the combination of motor imagery and the input from a game controller, while its feasibility is proven through an extensive experimental process. Finally, speech imagery is proposed as an alternative mental task for BCI applications. This is done through a series of rigorous experiments and appropriate data analysis. This work suggests that the integration of BCI principles in HSI applications can be successful and it can potentially lead to systems that are more intuitive for the users than the current state-of-the-art. At the same time, it motivates further research in the area and sets the stepping stones for the potential development of the field of Brain-Swarm Interfaces (BSI).
Author: Szczepan Paszkiel Publisher: Springer Nature ISBN: 3030722546 Category : Technology & Engineering Languages : en Pages : 348
Book Description
This book presents the proceedings of the 4th International Scientific Conference IC BCI 2021 Opole, Poland. The event was held at Opole University of Technology in Poland on 21 September 2021. Since 2014, the conference has taken place every two years at the University’s Faculty of Electrical Engineering, Automatic Control and Informatics. The conference focused on the issues relating to new trends in modern brain–computer interfaces (BCI) and control engineering, including neurobiology–neurosurgery, cognitive science–bioethics, biophysics–biochemistry, modeling–neuroinformatics, BCI technology, biomedical engineering, control and robotics, computer engineering and neurorehabilitation–biofeedback.
Author: Briana Landavazo
Author: Briana Landavazo
Author: Luca Tonin
Author: Alyssa Marie Batula
Author: Swagata Das
Author: Bernhard Graimann
Author: Rajesh P. N. Rao
Author: Fouad Sabry
Author: Ian Daly
Author: Georgios Konstantinos Karavas
Author: Szczepan Paszkiel