Download or read book A Wireless Multichannel Neural Recording Platform for Real time Brain Machine Interfaces written by Iyad Obeid and published by . This book was released on 2004 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book An Ultra Low Power Implantable Neural Recording System for Brain machine Interfaces written by Woradorn Wattanapanitch and published by . This book was released on 2011 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past few decades, direct recordings from different areas of the brain have enabled scientists to gradually understand and unlock the secrets of neural coding. This scientific advancement has shown great promise for successful development of practical brain-machine interfaces (BMIs) to restore lost body functions to patients with disorders in the central nervous system. Practical BMIs require the uses of implantable wireless neural recording systems to record and process neural signals, before transmitting neural information wirelessly to an external device, while avoiding the risk of infection due to through-skin connections. The implantability requirement poses major constraints on the size and total power consumption of the neural recording system. This thesis presents the design of an ultra-low-power implantable wireless neural recording system for use in brain-machine interfaces. The system is capable of amplifying and digitizing neural signals from 32 recording electrodes, and processing the digitized neural data before transmitting the neural information wirelessly to a receiver at a data rate of 2.5 Mbps. By combining state-of-the-art custom ASICs, a commercially-available FPGA, and discrete components, the system achieves excellent energy efficiency, while still offering design flexibility during the system development phase. The system's power consumption of 6.4 mW from a 3.6-V supply at a wireless output data rate of 2.5 Mbps makes it the most energy-efficient implantable wireless neural recording system reported to date. The system is integrated on a flexible PCB platform with dimensions of 1.8 cm x 5.6 cm and is designed to be powered by an implantable Li-ion battery. As part of this thesis, I describe the design of low-power integrated circuits (ICs) for amplification and digitization of the neural signals, including a neural amplifier and a 32-channel neural recording IC. Low-power low-noise design techniques are utilized in the design of the neural amplifier such that it achieves a noise efficiency factor (NEF) of 2.67, which is close to the theoretical limit determined by physics. The neural recording IC consists of neural amplifiers, analog multiplexers, ADCs, serial programming interfaces, and a digital processing unit. It can amplify and digitize neural signals from 32 recording electrodes, with a sampling rate of 31.25 kS/s per channel, and send the digitized data off-chip for further processing. The IC was successfully tested in an in-vivo wireless recording experiment from a behaving primate with an average power dissipation per channel of 10.1 [mu]W. Such a system is also widely useful in implantable brain-machine interfaces for the blind and paralyzed, and in cochlea implants for the deaf.

Download or read book Event Based Neuromorphic Systems written by Shih-Chii Liu and published by John Wiley & Sons. This book was released on 2015-02-16 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neuromorphic electronic engineering takes its inspiration from the functioning of nervous systems to build more power efficient electronic sensors and processors. Event-based neuromorphic systems are inspired by the brain's efficient data-driven communication design, which is key to its quick responses and remarkable capabilities. This cross-disciplinary text establishes how circuit building blocks are combined in architectures to construct complete systems. These include vision and auditory sensors as well as neuronal processing and learning circuits that implement models of nervous systems. Techniques for building multi-chip scalable systems are considered throughout the book, including methods for dealing with transistor mismatch, extensive discussions of communication and interfacing, and making systems that operate in the real world. The book also provides historical context that helps relate the architectures and circuits to each other and that guides readers to the extensive literature. Chapters are written by founding experts and have been extensively edited for overall coherence. This pioneering text is an indispensable resource for practicing neuromorphic electronic engineers, advanced electrical engineering and computer science students and researchers interested in neuromorphic systems. Key features: Summarises the latest design approaches, applications, and future challenges in the field of neuromorphic engineering. Presents examples of practical applications of neuromorphic design principles. Covers address-event communication, retinas, cochleas, locomotion, learning theory, neurons, synapses, floating gate circuits, hardware and software infrastructure, algorithms, and future challenges.

Download or read book Recent Advances and the Future Generation of Neuroinformatics Infrastructure written by Xi Cheng and published by Frontiers Media SA. This book was released on 2015-12-11 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: The huge volume of multi-modal neuroimaging data across different neuroscience communities has posed a daunting challenge to traditional methods of data sharing, data archiving, data processing and data analysis. Neuroinformatics plays a crucial role in creating advanced methodologies and tools for the handling of varied and heterogeneous datasets in order to better understand the structure and function of the brain. These tools and methodologies not only enhance data collection, analysis, integration, interpretation, modeling, and dissemination of data, but also promote data sharing and collaboration. This Neuroinformatics Research Topic aims to summarize the state-of-art of the current achievements and explores the directions for the future generation of neuroinformatics infrastructure. The publications present solutions for data archiving, data processing and workflow, data mining, and system integration methodologies. Some of the systems presented are large in scale, geographically distributed, and already have a well-established user community. Some discuss opportunities and methodologies that facilitate large-scale parallel data processing tasks under a heterogeneous computational environment. We wish to stimulate on-going discussions at the level of the neuroinformatics infrastructure including the common challenges, new technologies of maximum benefit, key features of next generation infrastructure, etc. We have asked leading research groups from different research areas of neuroscience/neuroimaging to provide their thoughts on the development of a state of the art and highly-efficient neuroinformatics infrastructure. Such discussions will inspire and help guide the development of a state of the art, highly-efficient neuroinformatics infrastructure.

Download or read book ARCHITECTURE DESIGN FOR A NEURAL SPIKE BASED DATA REDUCTION PLATFORM PROCESSING THOUSANDS OF RECORDING CHANNELS written by Nashwa Elaraby and published by . This book was released on 2014 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simultaneous recordings of single and multi-unit neural signals from multiple cortical areas in the brain are a vital tool for gaining more understanding of the operating mechanism of the brain as well as for developing Brain Machine Interfaces. Monitoring the activity levels of hundreds or even thousands of neurons can lead to reliable decoding of brain signals for controlling prosthesis of multiple degrees of freedom and different functionalities. With the advancement of high density microelectrode arrays, the craving of neuroscience research to record the activity of thousands of neurons is achievable. Recently CMOS-based Micro-electrode Arrays MEAs featuring high spatial and temporal resolution have been reported. The augmentation in the number of recording sites carries different challenges to the neural signal processing system. The primary challenge is the massive increase in the incoming data that needs to be transmitted and processed in real time. Data reduction based on the sparse nature of the neural signals with respect to time becomes essential. The dissertation presents the design of a neural spike-based data reduction platform that can handle a few thousands of channels on Field Programmable Gate Arrays (FPGAs), making use of their massive parallel processing capabilities and reconfigurability. For Standalone implementation the spike detector core uses Finite State Machines (FSMs) to control the interface with the data acquisition as well as sending the spike waveforms to a common output FIFO. The designed neural signal processing platform integrates the application of high-speed serial Multi-Gigabit transceivers on FPGAs to allow massive data transmission in real time. It also provides a design for autonomous threshold setting for each channel.

Download or read book Brain Machine Interface written by Xilin Liu and published by Springer. This book was released on 2017-10-17 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to the emerging area of “Brain-Machine Interfaces,” with emphasis on the operation and practical design aspects. The book will help both electrical & bioengineers as well as neuroscience investigators to learn about the next generation brain-machine interfaces. The comprehensive review and design analysis will be very helpful for researchers who are new to this area or interested in the study of the brain. The in-depth discussion of practical design issues especially in animal experiments will also be valuable for experienced researchers.

Download or read book Low Power Scalable Platforms for Implantable Neural Interfaces written by Rikky Muller and published by . This book was released on 2013 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clinically viable and minimally invasive neural interfaces stand to revolutionize disease care for patients with neurological conditions. For example, recent research in Brain-Machine Interfaces has shown success in using electronic signals from the motor cortex of the brain to control artificial limbs, providing hope for patients with spinal cord injuries. Currently, neural interfaces are large, wired and require open-skull operation. Future, less invasive interfaces with increased numbers of electrodes, signal processing and wireless capability will enable prosthetics, disease control and completely new user-computer interfaces. The first part of this thesis presents a signal-acquisition front end for neural recording that uses a digitally intensive architecture to reduce system area and enable operation from a 0.5V supply. The entire front-end occupies only 0.013mm2 while including "per-pixel" digitization, and enables simultaneous recording of LFP and action potentials for the first time. The second part presents the development of a minimally invasive yet scalable wireless platform for electrocorticography (ECoG), an electrophysiological technique where electrical potentials are recorded from the surface of the cerebral cortex, greatly reducing cortical scarring and improving implant longevity. A high-density flexible MEMS electrode array is tightly integrated with active circuits and a power-receiving antenna to realize a fully implantable system in a very small footprint. Building on the previously developed digitally intensive architecture, an order of magnitude in circuit area reduction is realized with 3x improvement in power efficiency over state-of-the-art enabling a scalable platform for 64-channel recording and beyond.

Download or read book Closing the Loop Around Neural Systems written by Steve M Potter and published by Frontiers Media SA. This book was released on 2014-12-03 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Closed-loop neurophysiology has been accelerated by recent software and hardware developments and by the emergence of novel tools to control neuronal activity with spatial and temporal precision, in which stimuli are delivered in real time based on recordings or behavior. Real-time stimulation feedback enables a wide range of innovative studies of information processing and plasticity in neuronal networks. This Research Topic e-Book comprises 16 Original Research Articles, seven Methods Articles, and seven Reviews, Mini- Reviews, and Perspectives, all peer-reviewed and published in Frontiers in Neural Circuits. The contributions deal with closed loop neurophysiology experiments at a variety of levels of neural circuit complexity. Some include modeling and theoretical analyses. New enabling technologies and techniques are described. Novel work is presented from experiments in vitro, in vivo, and in humans, along with their clinical and technological implications for improving the human condition.

Download or read book A Low Cost End to End Multi Channel Wireless Neural Recording System written by Benjamin Donald Wood and published by . This book was released on 2018 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past few years neural recording and stimulation technology has advanced rapidly. As new implants and electrode devices are implemented and tested, a full system capable of effectively utilizing them within a medical application has remained unrealized. A mechanism that is able to wirelessly communicate with and control such instruments would drastically increase the ease with which they can be used in scenarios such as free-moving animal experiments, medical studies, and field trials. Certain constraints come with constructing such an end-to-end device, such as limits on power, cost, and size, along with stringent performance requirements on data rates and range. This thesis introduces a fully developed wireless neural recording system. Consisting of a multi-channel neural implant, a small microcontroller relay device, and a tablet running a control application, it is capable of recording and displaying neural data at high speed and long range. Communication between the three components is accomplished purely through wireless transmissions, utilizing inductive coils to transfer data through the patient's tissue along with an 802.11 WiFi to establish a link and facilitate transmission between the microcontroller and control software. The control software gives the researcher freedom to specify recording parameters such as the amount of data desired, sampling speed, recording channels, and format of the data to be sent from the implant. Upon data reception, the software processes the received data, creating a time series of neural points per channel that can be graphed, displayed, and downloaded. This modular and simple approach to an end-to-end wireless recording system will allow cutting edge neural implants to be quickly integrated into full solutions that can be used in neurological and biomedical research.

Download or read book Microelectronic Implants for Central and Peripheral Nervous System Overview of Circuit and System Technology written by Morris (Ming-Dou) Ker and published by Frontiers Media SA. This book was released on 2022-01-11 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Professor Ker is on the Board of Amazingneuron. The Other Topic Editors Declare no Competing Interests With Regards to the Research Topic Theme.

Download or read book A Wearable Platform for Decoding Single Neuron and Local Field Potential Activity in Freely Moving Humans written by Uros Topalovic and published by . This book was released on 2022 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in technologies that can record and stimulate deep-brain activity in humans have led to impactful discoveries within the field of neuroscience and contributed to the develop- ment of novel closed-loop stimulation therapies for neurological and psychiatric disorders. Human neuroscience research based on intracranial electroencephalography (iEEG) is con- ducted on voluntary basis during various stages of participant's disease treatment using both external (in-clinic) and implantable systems. In clinical practice, external systems serve as monitoring and testing ground for biomarker extraction and closed-loop neuromodulation, which are, once approved, translated into a compact and low compute resource implantable version for disorder treatment. External systems allow recordings with fine spatiotemporal resolution at the expense of participant's mobility due to their large size, while implantable devices have reduced record- ing capabilities and they are not restricted to clinical environment. Due to high transmission and processing latencies across multiple devices, external systems have limited support for testing computationally expensive online biomarker detection and machine-learning based closed-loop electrical stimulation paradigms including online stimulation programmability. The motivation for this work comes from the need to extend capabilities of externalized systems, allowing more naturalistic (freely-moving) human neuroscience experiments with fine spatiotemporal resolution. Additionally, externalized systems should provide flexible and local hardware resources that can support real-time and moderately complex embedded neural decoders (biomarker extraction), which in turn could be used to trigger adaptive closed-loop stimulation with low latency. In order to demonstrate initial proof-of-concept technology, this work incorporates: 1. A small versatile neuromodulation platform that can be wearable and lightweight, supporting up to 16 depth electrode arrays; 2. A high-rate (" MB/s on all channels) interfacing of the analog sensing and stimulation front-ends with wearable hardware suitable for embedded machine learning algorithms including artificial neural networks (usually100M multi-accumulate operations or MACs); 3. A state of the art, performance-driven, neural decoder, small enough to run on an embedded hardware and large enough to generalize across participants; 4. Real-time training and inference with millisecond latency; 5. Closing the loop from the decoder output to the stimulation engines. Therefore, we developed a wearable, miniaturized, embedded, and external neuromodula- tion platform built from previously reported integrated circuits for sensing and stimulation, and interfaced with Edge Tensor Processing Unit (TPU) for real-time neural analysis. The Neuro-stack can record and decode single-neuron (32 channels), local field potential (LFP; 256 channels) activity, and deliver highly programmable current-controlled stimulation (256 channels) during stationary and ambulatory behaviors in humans. The TPU Dev Board was chosen because of the ability to perform 2 trillion MACs per second (64 64 MAC matrix at 480 MHz) using 2 W of power, with data bandwidth of 40 MB/s. Additionally, the system contains a field-programmable gate array (FPGA) for data pre-processing (filtering, down-sampling) and ARM-based microprocessor (TPU Dev Board) for data management, device control, and secure wireless access point. The Neuro-stack interfaces with the brain through commonly used macro- and micro-electrodes. The Neuro-stack validation includes in-vitro testing of recorded signal quality and measurement of system induced delays (e.g., closed-loop delay from sensing to stimulation site - 1.57 0.19 ms). We provide in-vivo single-unit, LFP, iEEG, and stimulation delivery recorded (2 - 40 channels) from twelve hu- man participants who had depth electrodes implanted for epilepsy evaluation. Among this data are also the first recordings of single-neuron activity during human walking. To utilize hardware capabilities of the Neuro-stack, we developed a software decoder based on prerecorded human LFP data, which uses TensorFlow artificial neural network (sequential convolutional 1D and recurrent layers) to predict the outcome of a memory task from raw data with higher performance (F1-score 88.6 5.5%) than current state of the art that use shallow machine learning methods (

Download or read book A High Data Rate Wireless Brain Computer Interface written by and published by . This book was released on 2016 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brain computer interface (BCI) taps into brain state and provides an associated quantitative assessment. It has potential for the real-time assessment of a person's cognitive state. BCI is a study to analyze characteristics of brain (Electrophysiology). Electrophysiology can be categorized into Invasive and Non-invasive methods. Electroencephalography (EEG) produced spontaneously during the process of thinking with frequency bands alpha waves, beta waves, theta waves and delta waves is one of the Non- Invasive methods. Electrocorticography (ECoG) is one of the invasive methods which records mu, beta and gamma frequency bands. In single unit recording, single or multi-neuron spiking and local field potential (LFP’s) are recorded. Invasive methods require surgery to implant electrodes inside the skull. A wireless interface is required to transfer brain data from BCI circuitry to host interface. Wireless transmission module eliminates the inconvenience of wiring and reduce risk of contamination. The wireless link implemented in this study has ability to switch among classic Bluetooth protocol, Bluetooth smart protocol and proprietary protocol depends on desired throughput, Power consumption and transmission distance (RSSI). Invasive methods like single unit recording requires processing high frequency band spectrum and optimum data throughput to transmit spike data. This study proposes a high speed sampling algorithm to increase sampling rate and a proprietary wireless protocol to transmit high sample data and reduce packet error rate for physiological sensing. A low-power bio potential amplifier in BCI circuitry converts analog brain data to digital format. High sampling rate can be achieved by multi-threading software call to receive data from sense electronics. The proposed sampling algorithm proposed increases sampling frequency from 800 Samples/sec to 10k for samples 8 channels. Wireless interface which allows throughput and power optimization can be achieved by implementing transmit mode with dynamic connection interval. Packet error rate is vital parameter for data integrity and can be optimized by implementing dynamic channel shifting mechanism in the presence of noisy channel. Dynamic transmit buffer length allocation algorithm should be implemented for better utilization of channel.

Download or read book Wearable Electronics and Embedded Computing Systems for Biomedical Applications written by Enzo Pasquale Scilingo and published by MDPI. This book was released on 2018-04-03 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Wearable Electronics and Embedded Computing Systems for Biomedical Applications" that was published in Electronics

Download or read book Low powder and High rate Wireless Transmission Systems for Neural Implants written by Henrique Do Carmo Miranda and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural recording systems are fundamental to the advancement of brain-machine interfaces that can significantly improve the quality of lives of patients with neurological diseases, such as spinal cord injuries or quadriplegia. This thesis presents two newly developed wireless neural recording systems that are able to provide a high degree of usability and neural decoding accuracy. They are capable of simultaneously transmitting 32 to 96 channels of neural signals detected by an implanted neural sensor array. This work was carried out within the framework of the Hermes project and its technical design challenges will be addressed. The Hermes project is aimed at primarily developing hardware and software tools that extract neural information from the motor cortex. Those tools can enable practical prosthetic devices used to significantly ameliorate the life of patients with neurological impairments that directly affect motor functions. The first developed system, HermesD, is a 32-channel broadband transmission system using an FSK modulated carrier at 24 Mbit/s in the 3.7-4.1 GHz band. The link range extends beyond 20 m and the total power consumption is 142 mW. The HermesD system uses only COTS components and can be easily replicated. HermesD is fully operational and is currently used to transmit broadband neural data for neuroscience research in the Neural Prosthetic Systems Laboratory (NPSL) at Stanford University. HermesD is also planned as the base platform for future human trials to take place in the same laboratory. The second system that represents the next Hermes generation, HermesE, uses a novel UWB transmitter architecture implemented in a custom IC in the 65-nm CMOS technology. The transmitted signal bandwidth covers the 3.6 to 7.5 GHz frequency range. The time domain waveform is digitally programmable, allowing a very flexible control of the output spectrum to avoid interference and to allow multi-band operation. The UWB transmitter chip is part of a 96-channel broadband recording system delivering 40 Mbit/s. Its power consumption is 230 uW for a communication range of about 5 m. The antenna subsystems for these wireless recording devices presented a design challenge given the requirements for small size, large bandwidth and high efficiency. While HermesD has an operating FBW of 10%, HermesE is much more demanding in this respect, with 70% FBW, requiring unconventional antenna structures. The design techniques and performance of the antennas required to meet the specifications of both systems are also addressed in this work.

Download or read book Brain Computer Interfaces for Perception Learning and Motor Control written by Saugat Bhattacharyya and published by Frontiers Media SA. This book was released on 2021-12-21 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Reconfigurable System on Chip Architecture for Neural Signal Processing written by Karthikeyan Balasubramanian and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Electrical Engineering

Download or read book Artificial Intelligence and Computational Intelligence written by Fu Lee Wang and published by Springer Science & Business Media. This book was released on 2010-10-08 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume proceedings contains revised selected papers from the International Conference on Artificial Intelligence and Computational Intelligence, AICI 2010, held in Sanya, China, in October 2010. The total of 105 high-quality papers presented were carefully reviewed and selected from 1216 submissions. The topics covered are: applications of artificial intelligence; automated problem solving; automatic programming; data mining and knowledge discovering; distributed AI and agents; expert and decision support systems; fuzzy logic and soft computing; intelligent information fusion; intelligent scheduling; intelligent signal processing; machine learning; machine vision; multi-agent systems; natural language processing; neural networks; pattern recognition; robotics; applications of computational intelligence; biomedical informatics and computation; fuzzy computation; genetic algorithms; immune computation; information security; intelligent agents and systems; nature computation; particle swarm optimization; and probabilistic reasoning.