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Related papers: Detecting Mild Traumatic Brain Injury with MEG Sca…

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Mild Traumatic Brain Injury (mTBI) is a common brain injury and affects a diverse group of people: soldiers, constructors, athletes, drivers, children, elders, and nearly everyone. Thus, having a well-established, fast, cheap, and accurate…

Signal Processing · Electrical Eng. & Systems 2022-08-19 Weiqing Gu , Ryan Chang , Bohan Yang

Mild traumatic brain injury (mTBI) is a growing public health problem with an estimated incidence of one million people annually in US. Neurocognitive tests are used to both assess the patient condition and to monitor the patient progress.…

Computer Vision and Pattern Recognition · Computer Science 2018-02-16 Shervin Minaee , Siyun Wang , Yao Wang , Sohae Chung , Xiuyuan Wang , Els Fieremans , Steven Flanagan , Joseph Rath , Yvonne W. Lui

Traumatic Brain Injury (TBI) is a common cause of death and disability. However, existing tools for TBI diagnosis are either subjective or require extensive clinical setup and expertise. The increasing affordability and reduction in size of…

Signal Processing · Electrical Eng. & Systems 2021-02-01 Navjodh Singh Dhillon , Agustinus Sutandi , Manoj Vishwanath , Miranda M. Lim , Hung Cao , Dong Si

Magnetoencephalography (MEG) is an imaging technique used to measure the magnetic field outside the human head produced by the electrical activity inside the brain. The MEG inverse problem, identifying the location of the electrical sources…

Computation · Statistics 2014-08-01 Zhigang Yao , William F. Eddy

Brain decoding is a data analysis paradigm for neuroimaging experiments that is based on predicting the stimulus presented to the subject from the concurrent brain activity. In order to make inference at the group level, a straightforward…

Machine Learning · Statistics 2014-04-17 Emanuele Olivetti , Seyed Mostafa Kia , Paolo Avesani

Magnetoencephalography (MEG) conventionally operates within high-performance magnetic shields due to the extremely weak magnetic field signals from the measured objects and the narrow dynamic range of the magnetic sensors employed for…

Medical Physics · Physics 2024-03-20 Yosuke Ito , Hiroyuki Ueda , Takenori Oida , Takahiro Moriya , Akinori Saito , Motohiro Suyama

Veterans with mild traumatic brain injury (mTBI) have reported auditory and visual dysfunction that persists beyond the acute incident. The etiology behind these symptoms is difficult to characterize with current clinical imaging. These…

Image and Video Processing · Electrical Eng. & Systems 2020-06-24 Cailey I. Kerley , Kurt G. Schilling , Justin Blaber , Beth Miller , Allen Newton , Adam W. Anderson , Bennett A. Landman , Tonia S. Rex

Magnetoencephalography (MEG) is a noninvasive method for measuring magnetic flux signals caused by brain activity using sensor arrays located on or above the scalp. A common strategy for monitoring brain activity is to place sensors on a…

Medical Physics · Physics 2022-05-24 Wan-Jin Yeo , Samu Taulu , J. Nathan Kutz

The brain-computer interface (BCI) establishes a non-muscle channel that enables direct communication between the human body and an external device. Electroencephalography (EEG) is a popular non-invasive technique for recording brain…

Machine Learning · Computer Science 2026-02-23 Jamal Hwaidi , Mohamed Chahine Ghanem

We study the distribution of brain source from the most advanced brain imaging technique, Magnetoencephalography (MEG), which measures the magnetic fields outside the human head produced by the electrical activity inside the brain. Common…

Applications · Statistics 2019-08-13 Zhigang Yao , Zengyan Fan , Masahito Hayashi , William F. Eddy

Magnetoencephalography and electroencephalography (M/EEG) are non-invasive modalities that measure the weak electromagnetic fields generated by neural activity. Estimating the location and magnitude of the current sources that generated…

Machine Learning · Statistics 2019-10-16 Hicham Janati , Thomas Bazeille , Bertrand Thirion , Marco Cuturi , Alexandre Gramfort

Recent studies have shown promising results in the detection of Mild Cognitive Impairment (MCI) using easily accessible Electroencephalogram (EEG) data which would help administer early and effective treatment for dementia patients.…

Signal Processing · Electrical Eng. & Systems 2025-01-31 Aayush Mishra , David Joffe , Sankara Surendra Telidevara , David S Oakley , Anqi Liu

In this paper, we propose a novel source model for a magnetoencephalography (MEG) inverse problem that combines a conventional extended parametric approach and an imaging approach.Our aim is to separately identify a focal current source and…

Signal Processing · Electrical Eng. & Systems 2023-02-27 Takaaki Nara , Ten-yu Yang , Kenta Kabashima

Magnetoencephalography (MEG) is an advanced imaging technique used to measure the magnetic fields outside the human head produced by the electrical activity inside the brain. Various source localization methods in MEG require the knowledge…

Methodology · Statistics 2017-07-06 Zhigang Yao , Ye Zhang , Zhidong Bai , William F. Eddy

Magnetoencephalography (MEG) recordings of patients with epilepsy exhibit spikes, a typical biomarker of the pathology. Detecting those spikes allows accurate localization of brain regions triggering seizures. Spike detection is often…

Computer Vision and Pattern Recognition · Computer Science 2023-10-16 Pauline Mouches , Thibaut Dejean , Julien Jung , Romain Bouet , Carole Lartizien , Romain Quentin

Prognoses of Traumatic Brain Injury (TBI) outcomes are neither easily nor accurately determined from clinical indicators. This is due in part to the heterogeneity of damage inflicted to the brain, ultimately resulting in diverse and complex…

MEG are non invasive neuroimaging techniques with excellent temporal and spatial resolution, crucial for studying brain function in dementia and Alzheimer Disease. They identify changes in brain activity at various Alzheimer stages,…

Machine Learning · Computer Science 2024-08-12 Alwani Liyana Ahmad , Jose Sanchez-Bornot , Roberto C. Sotero , Damien Coyle , Zamzuri Idris , Ibrahima Faye

Transfer learning makes use of data or knowledge in one problem to help solve a different, yet related, problem. It is particularly useful in brain-computer interfaces (BCIs), for coping with variations among different subjects and/or…

Human-Computer Interaction · Computer Science 2020-05-12 Wen Zhang , Dongrui Wu

Most brain disorders are very heterogeneous in terms of their underlying biology and developing analysis methods to model such heterogeneity is a major challenge. A promising approach is to use probabilistic regression methods to estimate…

Machine Learning · Statistics 2018-12-03 Seyed Mostafa Kia , Christian F. Beckmann , Andre F. Marquand

Magnetoencephalography (MEG) enables the study of brain activity by recording the magnetic fields generated by neural currents and has become an important technique for neuroscientists in research and clinical settings. Unlike the…

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