Article
Clinical Neurology
Chengpeng Hu, Tong Wang, Kenry W. C. Leung, Le Li, Raymond Kai-Yu Tong
Summary: This study demonstrated that FES-assisted cycling training improved lower limb function by developing coordinated muscle activation and facilitating an orderly myofiber arrangement. The results also indicated that EIM and sEMG can be used to evaluate lower extremity function alterations after rehabilitation training.
FRONTIERS IN NEUROLOGY
(2021)
Article
Chemistry, Analytical
Sehyeon Kim, Dae Youp Shin, Taekyung Kim, Sangsook Lee, Jung Keun Hyun, Sung-Min Park
Summary: This study proposes a novel system of two-dimensional input image feature multimodal fusion based on an EEG/EMG-signal transfer learning paradigm for detection of hand movements in transforearm amputees. Compared with conventional single-modal EEG signal trained models, the proposed method significantly improves the classification accuracy of motion classification.
Article
Neurosciences
Valeria de Seta, Jlenia Toppi, Emma Colamarino, Rita Molle, Filippo Castellani, Febo Cincotti, Donatella Mattia, Floriana Pichiorri
Summary: Brain-Computer Interface (BCI) systems have been proven effective in enhancing upper limb motor recovery after stroke by reinforcing motor related brain activity. In this study, a pseudo-online analysis was conducted to optimize the computation of cortico-muscular coupling (CMC) and CMC-based movement detection for a novel non-invasive h-BCI. The results showed that updating the CMC computation every 125 ms and accumulating two predictions before a final classification decision achieved the best trade-off between accuracy and speed in movement classification. The pseudo-online analysis on stroke participants demonstrated high performances in terms of classification speed and accuracy for both attempted and executed hand grasping/extension movements.
FRONTIERS IN HUMAN NEUROSCIENCE
(2022)
Article
Neurosciences
Vadivelan Ramu, Kishor Lakshminarayanan
Summary: The purpose of this study was to evaluate the effect of vibrotactile stimulation prior to repeated complex motor imagery of finger movements using the non-dominant hand on motor imagery performance. The results showed that motor imagery performance was better in terms of event-related desynchronization and digit classification with vibrotactile stimulation compared to without stimulation.
FRONTIERS IN NEUROSCIENCE
(2023)
Article
Neurosciences
Soo-In Choi, Ji-Yoon Lee, Ki Moo Lim, Han-Jeong Hwang
Summary: This study demonstrated the feasibility and reliability of using ear-EEG for the development of real-time endogenous BCIs in online environments. However, further studies are needed to improve its performance for practical applications.
FRONTIERS IN NEUROSCIENCE
(2022)
Article
Engineering, Electrical & Electronic
Mustapha Deji Dere, Ji-Hun Jo, Boreom Lee
Summary: This study presents an event-driven deep neural network capable of classifying gestures from single or hybrid biosignals. The results show that hybrid biosignals outperform single-modal EEG in gesture classification offline and on-device, as well as single-modal EMG in the case of EMG electrode shift. Additionally, the study demonstrates an end-to-end approach that deploys a DNN decoder to an edge device for neuro-inspired control of the dexterous hand without requiring an Internet-of-Things (IoT) connection.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Biomedical
Li-Wei Chou, Shiang-Lin Hou, Hui-Min Lee, Felipe Fregni, Alice Yen, Vincent Chen, Shun-Hwa Wei, Chung-Lan Kao
Summary: This study investigated the immediate effects of noise electrical stimulation on proprioceptive senses and grip force control, as well as the associated neural activities in the central nervous system. The results showed that optimal intensity noise stimulation could improve both force and joint proprioceptive senses, and individuals with higher gamma coherence demonstrated better force proprioceptive sense improvement with 30-min noise electrical stimulation. These findings suggest the potential clinical benefits of noise stimulation for individuals with impaired proprioceptive senses and indicate the characteristics of individuals who might benefit from noise stimulation.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2023)
Article
Engineering, Biomedical
Mahsa Zeynali, Hadi Seyedarabi, Reza Afrouzian
Summary: A Brain-Computer Interface (BCI) is a communication and control system that utilizes the brain's electrical signals for interaction between users and computer devices. This paper introduces a new Transformer-based model that extracts temporal and spectral features from EEG signals for classification purposes.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Engineering, Biomedical
Lei Zhang, Long Chen, Zhongpeng Wang, Xin Zhang, Xiuyun Liu, Dong Ming
Summary: A training strategy based on the combination of MI and sensory threshold somatosensory electrical stimulation (MI+st-SES) is proposed to improve the accuracy of MI-BCI. The results show that subjects in the MI+st-SES group have a significant improvement in alpha rhythm event-related desynchronization (ERD) and classification accuracy of left- and right-hand MI tasks. The functional connectivity based on weighted pairwise phase consistency (wPPC) also increases after MI+st-SES training.
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
(2023)
Article
Automation & Control Systems
Chin-Teng Lin, Tien-Thong Nguyen Do
Summary: BCIs allow users to communicate with external devices via brain signals. Wearable computers combine virtual/augmented/mixed reality experiences for entertainment, health monitoring, and research. Despite the potential of BCIs, adoption is slow due to the unnatural interaction and slower feedback compared to our brains.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Neurosciences
Zhengqing Miao, Meirong Zhaoa, Xin Zhangbc, Dong Ming
Summary: LMDA-Net is a lightweight multi-dimensional attention network that effectively integrates features from EEG signals, resulting in improved classification performance. Experimental results demonstrate its superiority in various BCI tasks and its high interpretability.
Review
Chemistry, Analytical
Kaido Varbu, Naveed Muhammad, Yar Muhammad
Summary: An EEG-based BCI system interprets EEG signals to establish a connection between the brain and external devices. Originally developed for medical purposes, these applications have expanded to improve the lives of healthy individuals as well. This review provides a systematic overview of the literature on EEG-based BCI applications from 2009 to 2019, analyzing the distribution of research in medical and non-medical domains, equipment used, signal processing methods, and current challenges and future possibilities.
Article
Biology
Huiying Li, Dongxue Zhang, Jingmeng Xie
Summary: A novel dual-attention-based adversarial network for motor imagery classification (MI-DABAN) is proposed, which leverages multiple subjects' knowledge to improve a single subject's classification performance. The method employs a clever adversarial learning method and two unshared attention blocks, resulting in effective and superior classification performance.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Engineering, Biomedical
Gabriel Chaves de Melo, Gabriela Castellano, Arturo Forner-Cordero
Summary: A Brain-Computer Interface (BCI) translates brain activities into computer commands through decoding brain signals, with electro-encephalography being the most widely adopted technique for signal recording. However, the high intra-subject variability of EEG signals poses a challenge for BCI development. This study aims to improve a pseudo-online movement detection system by using motor imagery EEG signals, proposing a strategy to minimize the effects of poor spatial resolution and active reference electrode by finding the best combinations of electrode pairs. The average accuracy across 15 subjects was 95%.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Chunfu Lu, Ruite Ge, Zhichuan Tang, Xiaoyun Fu, Lekai Zhang, Keshuai Yang, Xuan Xu
Summary: This study proposes a multi-channel FES gait rehabilitation assistance system based on adaptive myoelectric modulation. The system collects sEMG data and predicts muscle activation values to provide effective walking assistance, offering new ideas and methods for sEMG-controlled FES rehabilitation applications.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2023)
Article
Neurosciences
Stephen T. Foldes, Douglas J. Weber, Jennifer L. Collinger
JOURNAL OF NEUROPHYSIOLOGY
(2017)
Article
Engineering, Biomedical
Alan D. Degenhart, Shivayogi V. Hiremath, Ying Yang, Stephen Foldes, Jennifer L. Collinger, Michael Boninger, Elizabeth C. Tyler-Kabara, Wei Wang
JOURNAL OF NEURAL ENGINEERING
(2018)
Article
Clinical Neurology
Varina L. Boerwinkle, Stephen T. Foldes, Salvatore J. Torrisi, Hamy Temkit, William D. Gaillard, John F. Kerrigan, Virendra R. Desai, Jeffrey S. Raskin, Aditya Vedantam, Randa Jarrar, Korwyn Williams, Sandi Lam, Manish Ranjan, Janna S. Broderson, David Adelson, Angus A. Wilfong, Daniel J. Curry
Article
Clinical Neurology
Virendra R. Desai, Aditya Vedantam, Sandi K. Lam, Lucia Mirea, Stephen T. Foldes, Daniel J. Curry, P. David Adelson, Angus A. Wilfong, Varina L. Boerwinkle
JOURNAL OF NEUROSURGERY-PEDIATRICS
(2019)
Article
Engineering, Biomedical
Safaa Eldeeb, Murat Akcakaya, Matthew Sybeldon, Stephen Foldes, Emiliano Santarnecchi, Alvaro Pascual-Leone, Amit Sethi
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2019)
Review
Clinical Neurology
Brian Appavu, Stephen T. Foldes, P. David Adelson
JOURNAL OF NEUROSURGERY-PEDIATRICS
(2019)
Article
Critical Care Medicine
Brian Appavu, Stephen Foldes, M'hamed Temkit, Austin Jacobson, Brian T. Burrows, Danni Brown, Varina Boerwinkle, Iris Marku, P. David Adelson
PEDIATRIC CRITICAL CARE MEDICINE
(2020)
Review
Clinical Neurology
Brian Appavu, Brian T. Burrows, Stephen Foldes, P. David Adelson
FRONTIERS IN NEUROLOGY
(2019)
Article
Engineering, Biomedical
Stephen T. Foldes, Michael L. Boninger, Douglas J. Weber, Jennifer L. Collinger
JOURNAL OF NEURAL ENGINEERING
(2020)
Article
Clinical Neurology
Varina L. Boerwinkle, Lucia Mirea, William D. Gaillard, Bethany L. Sussman, Diana Larocque, Alexandra Bonnell, Jennifer S. Ronecker, Matthew M. Troester, John F. Kerrigan, Stephen T. Foldes, Brian Appavu, Randa Jarrar, Korwyn Williams, Angus A. Wilfong, P. David Adelson
JOURNAL OF NEUROSURGERY-PEDIATRICS
(2020)
Article
Critical Care Medicine
Brian Appavu, Stephen Foldes, Brian T. Burrows, Austin Jacobson, Todd Abruzzo, Varina Boerwinkle, Anthony Willyerd, Tara Mangum, Vishal Gunnala, Iris Marku, P. D. Adelson
Summary: After pediatric cerebral AVM rupture, poor outcomes are associated with lower AF and higher CA indices, including the development of acquired epilepsy. Increased time spent below lower limits of autoregulation is also linked to unfavorable outcomes.
NEUROCRITICAL CARE
(2021)
Article
Clinical Neurology
Brian Appavu, Stephen Foldes, Jordana Fox, Sheetal Shetty, Ann Oh, Freddy Bassal, Iris Marku, Tara Mangum, Varina Boerwinkle, Derek Neilson, Michael Kruer
Summary: In children with ANE, early immunomodulatory therapy and normal sleep spindles are associated with better functional outcomes, while higher ANE-SS, older age, and brainstem lesions are related to longer hospitalization.
JOURNAL OF CHILD NEUROLOGY
(2021)
Article
Clinical Neurology
Brian L. Appavu, M'hamed H. Temkit, Stephen T. Foldes, Brian T. Burrows, Austin M. Jacobson, Tara K. Mangum, Varina L. Boerwinkle, Iris Marku, Todd A. Abruzzo, Phillip D. Adelson
Summary: This study investigates regional differences in quantitative EEG characteristics and associations of EEG to hemodynamics after pediatric acute stroke. It finds that reduced spectral edge frequency, alpha, and beta power can be observed on injured regions after ischemic stroke, while total power is negatively associated with arterial blood pressure within injured regions after hemorrhagic stroke.
JOURNAL OF CLINICAL NEUROPHYSIOLOGY
(2022)
Article
Clinical Neurology
Stephen T. Foldes, Bryce T. Munter, Brian L. Appavu, John F. Kerrigan, P. David Adelson
Article
Neurosciences
Varina L. Boerwinkle, Deepankar Mohanty, Stephen T. Foldes, Danielle Guffey, Charles G. Minard, Aditya Vedantam, Jeffrey S. Raskin, Sandi Lam, Margaret Bond, Lucia Mirea, P. David Adelson, Angus A. Wilfong, Daniel J. Curry
BRAIN CONNECTIVITY
(2017)