193 resources related to Clinical Neuroscience
- Topics related to Clinical Neuroscience
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- Conferences related to Clinical Neuroscience
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- Most published Xplore authors for Clinical Neuroscience
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.
The International Conference on Robotics and Automation (ICRA) is the IEEE Robotics and Automation Society’s biggest conference and one of the leading international forums for robotics researchers to present their work.
All areas of ionizing radiation detection - detectors, signal processing, analysis of results, PET development, PET results, medical imaging using ionizing radiation
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI 2020)
The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2020 will be the 17th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2020 meeting will continue this tradition of fostering cross-fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.
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.
Serves as a compendium for papers on the technological advances in control engineering and as an archival publication which will bridge the gap between theory and practice. Papers will highlight the latest knowledge, exploratory developments, and practical applications in all aspects of the technology needed to implement control systems from analysis and design through simulation and hardware.
2018 International Workshop on Pattern Recognition in Neuroimaging (PRNI), 2018
Since machine learning models have been applied to neuroimaging data, researchers have drawn conclusions from the derived weight maps. In particular, weight maps of classifiers between two conditions are often described as a proxy for the underlying signal differences between the conditions. Recent studies have however suggested that such weight maps could not reliably recover the source of the neural ...
2016 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), 2016
Understanding the amount of forces exerted to the brain tissue during the performance of surgical tasks in neurosurgery is critical for educating trainees. Quantifying such forces can help trainees gain important information about the appropriate amount of force required to safely, yet effectively, complete microsurgical tasks. This paper reports the amount of forces exerted during the performance of neurosurgical tasks ...
IEEE/ASME Transactions on Mechatronics, 2016
The ability to exert an appropriate amount of force on brain tissue during surgery is an important component of instrument handling. It allows surgeons to achieve the surgical objective effectively while maintaining a safe level of force in tool-tissue interaction. At the present time, this knowledge, and hence skill, is acquired through experience and is qualitatively conveyed from an expert ...
2013 6th International IEEE/EMBS Conference on Neural Engineering (NER), 2013
In this study, kinematic characteristics of writing are compared in 5 patients with writer's cramp who performed a set of standardized writing tasks. The kinematic characteristics include upper limb joint angles, vertical hand pressure, and finger grip force. The effect of writing on different inclined supporting surfaces is also investigated. Our results indicate that altering upper limb posture using inclined ...
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2011
Intuitive somatosensory feedback is required for fine motor control. Here we explored whether thalamic electrical stimulation could provide the necessary durations and consistency of percepts for a human somatosensory neural prosthetic. Continuous and cycling high-frequency (185 Hz, 0.21 ms pulse duration charge balanced square wave) electrical pulses with the cycling patterns varying between 7% and 67% of duty cycle were ...
IEEE Brain: Abbott Neuromodulation - The Importance and Practice of Late-stage Innovation
Neuropriming: What Are The Ethical Implications? - IEEE TechEthics Virtual Panel
ICASSP 2012 Plenary-Dr. Mitsuo Kawato
Laura Specker Sullivan: Neuroscience & Brain Panel - Forecasting the Future by Looking at the Past - TTM 2018
Sharing New Breakthroughs in Neuroscience
Robotics History: Narratives and Networks Oral Histories:Michael Arbib
Creating a Culture of Welcoming Transformative Technologies in the Clinical Setting: The USC Neurorestoration Center Experience - IEEE Brain Workshop
Eliot Siegel - COVID-19, Deep Learning and Biomedical Imaging Panel
Q&A: Neuroscience and Brain Panel - TTM 2018
COVID-19 & the Rise of Telehealth: Examining the Social Impacts | IEEE TechEhics Virtual Panel
Clinical, Research, and Government Careers in Neurotechnology - IEEE Brain Workshop
Panel: Healthcare AI for the Clinical Environment - IEEE EMBS at NIH, 2019
Implementation of POC Testing in Healthcare - Nicole Tolan - IEEE EMBS at NIH, 2019
Q&A with Jack Gallant: IEEE Brain Podcast, Episode 11
Q&A with Emery Brown: IEEE Brain Podcast, Episode 3
IEEE Brain: Platypus Neuro : Applied Neuroscience and Optimized Human Performance at Scale
Mind/Brain Research and AI Development: How Do They Inform Each Other? - IEEE TechEthics Panel
Engineering Our Future - Maja Mataric, Ph.D
Q&A with Dr. Al Emondi: IEEE Brain Podcast, Episode 13
Since machine learning models have been applied to neuroimaging data, researchers have drawn conclusions from the derived weight maps. In particular, weight maps of classifiers between two conditions are often described as a proxy for the underlying signal differences between the conditions. Recent studies have however suggested that such weight maps could not reliably recover the source of the neural signals and even led to false positives (FP). In this work, we used semi-simulated data from ElectroCorticoGraphy (ECoG) to investigate how the signal-to-noise ratio and sparsity of the neural signal affect the similarity between signal and weights. We show that not all cases produce FP and that it is unlikely for FP features to have a high weight in most cases.
Understanding the amount of forces exerted to the brain tissue during the performance of surgical tasks in neurosurgery is critical for educating trainees. Quantifying such forces can help trainees gain important information about the appropriate amount of force required to safely, yet effectively, complete microsurgical tasks. This paper reports the amount of forces exerted during the performance of neurosurgical tasks by means of a force-sensing bipolar forceps, retrofitted by a set of force sensing components. An experienced surgeon and a surgical team conducted a variety of microsurgical tasks on a cadaver brain using the developed instrumented bipolar forceps, while the forces of dissections were measured real-time. Results showed that depending on the surgical task, the peak (effective) value of dissection forces varied between 0.50 N and 1.84 N. Correlation between calculated force signals, during performance of different trials for the same task was investigated using cross correlation test. Results indicated a strong link between the forces measured in different trials.
The ability to exert an appropriate amount of force on brain tissue during surgery is an important component of instrument handling. It allows surgeons to achieve the surgical objective effectively while maintaining a safe level of force in tool-tissue interaction. At the present time, this knowledge, and hence skill, is acquired through experience and is qualitatively conveyed from an expert surgeon to trainees. These forces can be assessed quantitatively by retrofitting surgical tools with sensors, thus providing a mechanism for improved performance and safety of surgery, and enhanced surgical training. This paper presents the development of a force-sensing bipolar forceps, with installation of a sensory system, that is able to measure and record interaction forces between the forceps tips and brain tissue in real time. This research is an extension of a previous research where a bipolar forceps was instrumented to measure dissection and coagulation forces applied in a single direction. Here, a planar forceps with two sets of strain gauges in two orthogonal directions was developed to enable measuring the forces with a higher accuracy. Implementation of two strain gauges allowed compensation of strain values due to deformations of the forceps in other directions (axial stiffening) and provided more accurate forces during microsurgery. An experienced neurosurgeon performed five neurosurgical tasks using the axial setup and repeated the same tasks using the planar device. The experiments were performed on cadaveric brains. Both setups were shown to be capable of measuring real-time interaction forces. Comparing the two setups, under the same experimental condition, indicated that the peak and mean forces quantified by planar forceps were at least 7% and 10% less than those of axial tool, respectively; therefore, utilizing readings of all strain gauges in planar forceps provides more accurate values of both peak and mean forces than axial forceps. Cross-correlation analysis between the two force signals obtained, one from each cadaveric practice, showed a high similarity between the two force signals.
In this study, kinematic characteristics of writing are compared in 5 patients with writer's cramp who performed a set of standardized writing tasks. The kinematic characteristics include upper limb joint angles, vertical hand pressure, and finger grip force. The effect of writing on different inclined supporting surfaces is also investigated. Our results indicate that altering upper limb posture using inclined surfaces improves aspects of writing discomfort in writer's cramp subjects. Although the change in arm joint angles and fingers/hand pressure is not generalizable between patients, such kinematic evaluations seem to be a key factor in the outcome of any personalized treatment or rehabilitation strategy.
Intuitive somatosensory feedback is required for fine motor control. Here we explored whether thalamic electrical stimulation could provide the necessary durations and consistency of percepts for a human somatosensory neural prosthetic. Continuous and cycling high-frequency (185 Hz, 0.21 ms pulse duration charge balanced square wave) electrical pulses with the cycling patterns varying between 7% and 67% of duty cycle were applied in five patients with chronically implanted deep brain stimulators. Stimulation produced similar percepts to those elicited immediately after surgery. While consecutive continuous stimuli produced decreasing durations of sensation, the amplitude and type of percept did not change. Cycling stimulation with shorter duty cycles produced more persisting percepts. These features suggest that the thalamus could provide a site for stable and enduring sensations necessary for a long term somatosensory neural prosthesis.
Neural oscillations in various distinct frequency bands and their interrelations yield high temporal resolution signatures of the human brain activity. This study demonstrates solutions to some of the common challenges in the analysis of neurophysiological data by means of subthalamic local field potentials (LFP) acquired form patients with Parkinson's Disease (PD) undergoing deep brain stimulation therapy. Multivariate empirical mode decomposition (MEMD), being a data-driven method suitable for multichannel data, is employed. This method allows identification of oscillatory bands without the requirement of fixed a priori basis functions. Our study focuses on two issues: (i) Determination of data specific frequency bands and revealing the weak inconspicuous high frequency components in the data and (ii) validation of the biological meaningfulness of the MEMD oscillatory components via phase-amplitude coupling as previously shown to be inherent in subcortical PD LFP data.
Although smartphone technology provides new opportunities for the recording of speech samples in everyday life, its ability to capture prodromal speech impairment in persons with a high risk of developing Parkinson's disease (PD) has never been investigated. Speech data were acquired through a smartphone as well as a professional microphone with a linear frequency response from 50 participants with a rapid eye movement sleep behavior disorder that are at a high risk of developing PD and related neurodegenerative disorders. Additionally, recordings of 30 newly diagnosed, untreated PD patients and 30 healthy participants were evaluated. Acoustic assessment of 11 speech dimensions representing the key aspects of hypokinetic dysarthria in the early stages of PD was performed. Smartphone allowed the detection of speech abnormalities in participants with a high risk of developing PD. Acoustic measurements related to fundamental frequency variability, duration of pause intervals, and rate of speech timing extracted from spontaneous speech were sufficiently sensitive to significantly separate groups (area under curve of 0.85 between PD and controls) and showed very strong correlation and reliability between the professional microphone and the smartphone. Speech- based biomarkers collected through smartphones may have the potential to revolutionize the diagnostic process in neurodegenerative diseases and improve stratification for future neuroprotective therapy in PD.
Brain aneurysm or intracranial aneurysm is an abnormal dilatation of the cerebral arteries. Detecting unruptured aneurysm remains a challenging task. Indeed, it is complicated and time-consuming for neuroradiologists to detect intracranial aneurysm due to complexity of cerebral vascular anatomy. To solve this problem, computer-aided diagnosis (CAD) approach has become a main tool to assist neuroradiologistsW to interpret unclear findings of aspects mimicking aneurysms. In this paper, we review the state of the art on CAD systems for detecting intracranial aneurysm with an emphasis on highlighting advantages. Hence, various approaches were used in this field. A discussion and conclusion on future possibilities of CAD methodologies for detecting intracranial aneurysm will be produced.
Due to technological developments in PET detectors and PET-MR integration, the simultaneous measurement of PET-MR-EEG has become feasible, offering the possibility of exploring the complementary information provided by each modality. Studies have already shown the benefits of simultaneous measurement using PET-MR, however, such achievements come with different technical and practical challenges. In this context, we aim to give an overview of the technical challenges involved in integrating EEG with hybrid PET-MR scanners and demonstrate possible solutions. When acquiring simultaneous data from multiple modalities, the data acquisition protocol should be optimised in order to utilise time and complementary information most effectively. Thus, practical considerations with regard to protocol optimisation are also discussed, alongside relevant examples. In addition to simultaneous data acquisition, another major challenge is the integration of the multimodal data, which is also addressed. Finally, a clinical application with a strong focus on neuro-psychiatry is shown. This clinical application is discussed with relevant examples from an ongoing clinical study. Finally, the possibility of utilising the PET-MR-EEG data in search for new biomarkers for individualised medicine in clinical neuroscience is briefly explored.
We investigated changes of time-frequency (TF) complexity, in terms of Rényi entropy and a measure of concentration, of middle cerebral blood flow velocity (CBFV) and arterial blood pressure in relation to the development of cerebral vasospasm in 15 patients after aneurysmal subarachnoid hemorrhage. Interhemispheric differences in the period of no vasospasm and vasospasm were also compared. Results show reduced complexity of TF representations of CBFV on the side of aneurysm before vasospasm was identified. This potentially can serve as an early-warning indicator of future derangement of cerebral circulation.
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