443 resources related to Neurotechnology
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The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and postersessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE
The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.
2020 IEEE International Symposium on Circuits and Systems (ISCAS)
The International Symposium on Circuits and Systems (ISCAS) is the flagship conference of the IEEE Circuits and Systems (CAS) Society and the world’s premier networking and exchange forum for researchers in the highly active fields of theory, design and implementation of circuits and systems. ISCAS2020 focuses on the deployment of CASS knowledge towards Society Grand Challenges and highlights the strong foundation in methodology and the integration of multidisciplinary approaches which are the distinctive features of CAS contributions. The worldwide CAS community is exploiting such CASS knowledge to change the way in which devices and circuits are understood, optimized, and leveraged in a variety of systems and applications.
The program of the conference will be tailored to reflect the wide spectrum of topics and research interest shared among the organizing entities. This collaboration will be oriented towards advanced research in adaptive systems which constitutes the highlights of the NEWCAS conference, but also areas related to analog and digital signal processing, low power consumption, and circuits and systems designs. The topics include, but are not limited to: Computer architecture and memories, Analog circuit design, Digital and mixed-signal circuit design, RF circuit design, mm-Wave circuits, Microsystems, sensors and actuators, Test and verification, Communication, microwaves and RF, Technology Trends, Data and signal processing, Neural networks and artificial vision, CAD and design tools, Low-Power circ. & syst. techniques, Imaging & image sensors, Embedded hand-held devices, Biomed. circuits & systems, Energy Harvesting / Scavenging
Brain-Computer Interface, etc.
The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...
The IEEE Reviews in Biomedical Engineering will review the state-of-the-art and trends in the emerging field of biomedical engineering. This includes scholarly works, ranging from historic and modern development in biomedical engineering to the life sciences and medicine enabled by technologies covered by the various IEEE societies.
Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.
Computer, the flagship publication of the IEEE Computer Society, publishes peer-reviewed technical content that covers all aspects of computer science, computer engineering, technology, and applications. Computer is a resource that practitioners, researchers, and managers can rely on to provide timely information about current research developments, trends, best practices, and changes in the profession.
IEEE Transactions on Industrial Informatics focuses on knowledge-based factory automation as a means to enhance industrial fabrication and manufacturing processes. This embraces a collection of techniques that use information analysis, manipulation, and distribution to achieve higher efficiency, effectiveness, reliability, and/or security within the industrial environment. The scope of the Transaction includes reporting, defining, providing a forum for discourse, and informing ...
2017 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2017
This paper presents an implantable, wireless, 2-channel electromyography (EMG) recording system that was successfully tested in a chronic experiment in a rodent for up to three months. The system comprises of an implanted device and an external reader module. The implanted device is a multi-channel neural amplifier chip coupled with inductive power and data transfer electronics. The external reader module ...
2018 IEEE CPMT Symposium Japan (ICSJ), 2018
Active Implantable Medical Devices used in Neurotechnology as Brain-Computer Interfaces enable paralyzed patients to recover some degree of movement and speech. Impressive results have been achieved already by high-resolution cortical BCIs. Wyss Center is working presently to create wireless implantable BCIs for clinical treatment of neurological disorders. However, translation of existing animal use prototypes to human use BCIs has encountered ...
2017 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2017
We have developed a fully implantable 4-channel wireless muscle stimulator system with the ability to elicit precise and graded muscle movements for a hand grasping motion. The stimulator system consists of a WiFi enabled inductive powering and data transfer circuitry connected to a laptop, and a wireless implantable stimulator unit with biocompatible stainless steel electrodes. We shall demonstrate this stimulator ...
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2018
Despite the apparent importance of mental fatigue detection, a reliable application is hindered due to the incomprehensive understanding of the neural mechanisms of mental fatigue. In this paper, we investigated the topological alterations of functional brain networks in the theta band (4 - 7 Hz) of electroencephalography (EEG) data from 40 male subjects undergoing two distinct fatigue-inducing tasks: a low-intensity ...
IEEE Pulse, 2012
This article explores the psychophysiological metrics during expert and novice performances in marksmanship, combat deadly force judgment and decision making (DFJDM), and interactions of teams. Electroencephalography (EEG) and electrocardiography (ECG) are used to characterize the psychophysiological profiles within all categories. Closed-loop biofeedback was administered to accelerate learning during marksmanship training in which the results show a difference in groups that ...
How will Neurotechnology Impact your Future? - IEEE Brain Workshop
Q&A with Kip Ludwig: IEEE Brain Podcast, Episode 7
Q&A with Dr. Jennifer Gelinas: IEEE Brain Podcast, Episode 8
Neuropreneurs and the Waves they Ride: A HPC-driven Future - IEEE Brain Workshop
Translational Neural Engineering: Bringing Neurotechnology into the Clinics - IEEE Brain Workshop
Q&A with Dr. Al Emondi: IEEE Brain Podcast, Episode 13
Q&A with Chris Berka: IEEE Brain Podcast, Episode 9
Q&A with Dr. Maryam Shanechi: IEEE Brain Podcast, Episode 6 Part 2
Q&A with Laura Specker Sullivan: IEEE Brain Podcast, Episode 15
IEEE Brain: Nia Therapeutics: Building an Early-stage Medical Device Business
Q&A with Dr. Jacob Robinson: IEEE Brain Podcast, Episode 5
IEEE Brain: Regulatory Considerations
IEEE Brain: Platypus Neuro : Applied Neuroscience and Optimized Human Performance at Scale
Dr. Scott Fish
Neuropriming: What Are The Ethical Implications? - IEEE TechEthics Virtual Panel
This paper presents an implantable, wireless, 2-channel electromyography (EMG) recording system that was successfully tested in a chronic experiment in a rodent for up to three months. The system comprises of an implanted device and an external reader module. The implanted device is a multi-channel neural amplifier chip coupled with inductive power and data transfer electronics. The external reader module consists of a transcutaneous power supply, EMG data recovery circuitry, and a USB to computer interface for display and storage purposes. Stainless steel EMG electrodes were connected to the implanted device, and the device was then encapsulated using biocompatible FDA compliant silicone. Chronic recordings in a rodent across a three-month period validated this system's ability to acquire EMG signals (at sample rates of 20 kSPS/channel) in in-vivo conditions. This wireless device can be incorporated into a wireless proximal muscle/neural recording and distal muscle stimulation neuroprosthesis to address peripheral nerve injuries.
Active Implantable Medical Devices used in Neurotechnology as Brain-Computer Interfaces enable paralyzed patients to recover some degree of movement and speech. Impressive results have been achieved already by high-resolution cortical BCIs. Wyss Center is working presently to create wireless implantable BCIs for clinical treatment of neurological disorders. However, translation of existing animal use prototypes to human use BCIs has encountered many technical challenges that are worth mentioning. This article summarizes the technical challenges found in implantable BCIs and some of the solutions available or needed to mitigate them.
We have developed a fully implantable 4-channel wireless muscle stimulator system with the ability to elicit precise and graded muscle movements for a hand grasping motion. The stimulator system consists of a WiFi enabled inductive powering and data transfer circuitry connected to a laptop, and a wireless implantable stimulator unit with biocompatible stainless steel electrodes. We shall demonstrate this stimulator package and its features through a dummy robotic rat limb. We will also show videos of the stimulator being used to activate the rodent hind limb muscles to kick a ball, and activate the forearm muscles of a non-human primate to elicit individual finger movement to play a virtual piano.
Despite the apparent importance of mental fatigue detection, a reliable application is hindered due to the incomprehensive understanding of the neural mechanisms of mental fatigue. In this paper, we investigated the topological alterations of functional brain networks in the theta band (4 - 7 Hz) of electroencephalography (EEG) data from 40 male subjects undergoing two distinct fatigue-inducing tasks: a low-intensity one-hour simulated driving and a high-demanding half-hour sustained attention task [psychomotor vigilance task (PVT)]. Behaviorally, subjects demonstrated a robust mental fatigue effect, as reflected by significantly declined performances in cognitive tasks prior and post these two tasks. Furthermore, characteristic path length presented a positive correlation with task duration, which led to a significant increase between the first and the last five minutes of both tasks, indicating a fatigue-related disruption in information processing efficiency. However, significantly increased clustering coefficient was revealed only in the driving task, suggesting distinct network reorganizations between the two fatigue-inducing tasks. Moreover, high accuracy (92% for driving; 97% for PVT) was achieved for fatigue classification with apparently different discriminative functional connectivity features. These findings augment our understanding of the complex nature of fatigue-related neural mechanisms and demonstrate the feasibility of using functional connectivity as neural biomarkers for applicable fatigue monitoring.
This article explores the psychophysiological metrics during expert and novice performances in marksmanship, combat deadly force judgment and decision making (DFJDM), and interactions of teams. Electroencephalography (EEG) and electrocardiography (ECG) are used to characterize the psychophysiological profiles within all categories. Closed-loop biofeedback was administered to accelerate learning during marksmanship training in which the results show a difference in groups that received feedback compared with the control. During known distance marksmanship and DFJDM scenarios, experts show superior ability to control physiology to meet the demands of the task. Expertise in teaming scenarios is characterized by higher levels of cohesiveness than those seen in novices.
The ultimate goal is to understand how the information in the distributed neural circuits of the brain reorganizes and plastically adapts to laboratory disruptions designed to reversibly mimic brain injury. Our approach involves a new generation of data- driven mathematical models of brain circuits and their connection with complex behavioral tasks in primates that are enabled with a suite of novel experimental tools .In the following article, we illustrate a few of these methods, which include projecting input directly onto specifically targeted brain microcircuits and thus writing in neuromodulatory signals. These methods also enable the simultaneous read out and write in of real-time neural responses across multiple spatial and temporal scales of network activity.
Bipedal robotics is a field referred to chiefly developing humanoids and other biologically inspire two legged robots, due to the complex mechanisms and decision making processes involved in physical activities of human beings we require highly reliable sensor modules and high precision high frequency processor platforms for near to real time response of the bipedal robots (bipeds). Since in human beings the entire decision making process and control signal triggering actions are taken care chiefly by Brain neurons, their unmatched parallelism is far from reality to be realized by conventional processors. The novel approach to such a problem would be using brain neurons itself for processing of data and making decisions. The recent lab results published by Johanna Varner of MIT have shown that occipital and cortical neurons can be cultured efficiently in the lab on a silicon substrate. This paper discusses the technique of using lab cultured (in vivo) occipital and cortical neurons for image processing and motor control.
Restoring normal walking abilities following the loss of them is a challenge. Importantly, there is a growing need for a better understanding of brain plasticity and the neural involvements for the initiation and control of these abilities so as to develop better rehabilitation programmes and external support devices. In this paper, we attempt to identify gait-related neural activities by decoding neural signals obtained from electroencephalography (EEG) measurements while subjects performed three types of walking: without exoskeleton (free walking), and with exoskeleton support (zero force and assisting force). An average classification accuracy of 92.0% for training and 73.8% for testing sets was achieved using features extracted from mu and beta frequency bands. Furthermore, we found that mu band features contributed significantly to the classification accuracy and were localized mainly in sensorimotor regions that are associated with the control of the exoskeleton. These findings contribute meaningful insight on the neural dynamics associated with lower limb movements and provide useful information for future developments of orthotic devices and rehabilitation programs.
We have developed an implantable four-channel high-current biphasic stimulator device for controlling the muscles of the hand, and successfully tested it in a non-human primate (NHP). The charge-balanced stimulator features an external unit which connects to a personal computer via WiFi, and provides wireless power and data control commands to the implant across biological tissue. The stimulator obtained realtime grip force from the hand using a force sensor to perform automated closed-loop control of the stimulation amplitude to ensure that we were able to produce sustained gripping force in the hand of the animal in the event of muscle fatigue. The device was encapsulated using a FDA-compliant biocompatible polymer for reliable long-term study. In-vivo experiments performed after the stimulator (with electrodes embedded in different muscles) had been implanted for one month demonstrated that the system was able to evoke, and automatically maintain, a targeted range of gripping force in the animal's hand. Our results demonstrate the utility of our closed-loop muscle stimulator as a neuroprosthesis for restoring functional hand movements in patients with upper-limb peripheral nerve injuries.
Neuroprosthetic devices that interface with the nervous system to restore functional motor activity offer a viable alternative to nerve regeneration, especially in proximal nerve injuries like brachial plexus injuries where muscle atrophy may set in before nerve re-innervation occurs. Prior studies have used control signals from muscle or cortical activity. However, nerve signals are preferred in many cases since they permit more natural and precise control when compared to muscle activity, and can be accessed with much lower risk than cortical activity. Identification of nerve signals that control the appropriate muscles is essential for the development of such a `bionic link'. Here we examine the correlation between muscle and nerve signals responsible for hand grasping in the M. fascicularis. Simultaneous recordings were performed using a 4-channel thin-film longitudinal intra-fascicular electrode (tf-LIFE) and 9 bipolar endomysial muscle electrodes while the animal performed grasping movements. We were able to identify a high degree of correlation (r > 0.6) between nerve signals from the median nerve and movement-dependent muscle activity from the flexor muscles of the forearm, with a delay that corresponded to 25 m/s nerve conduction velocity. The phase of the flexion could be identified using a wavelet approximation of the ENG. This result confirms this approach for a future neu-roprosthetic device for the treatment of peripheral nerve injuries.
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Postdoctoral Researcher - Micro and Nano Technology
Lawrence Livermore National Laboratory