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Wu Z, Tang X, Wu J, Huang J, Shen J, Hong H. Portable deep-learning decoder for motor imaginary EEG signals based on a novel compact convolutional neural network incorporating spatial-attention mechanism. Med Biol Eng Comput 2023; 61:2391-2404. [PMID: 37095297 DOI: 10.1007/s11517-023-02840-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 04/13/2023] [Indexed: 04/26/2023]
Abstract
Due to high computational requirements, deep-learning decoders for motor imaginary (MI) electroencephalography (EEG) signals are usually implemented on bulky and heavy computing devices that are inconvenient for physical actions. To date, the application of deep-learning techniques in independent portable brain-computer-interface (BCI) devices has not been extensively explored. In this study, we proposed a high-accuracy MI EEG decoder by incorporating spatial-attention mechanism into convolution neural network (CNN), and deployed it on fully integrated single-chip microcontroller unit (MCU). After the CNN model was trained on workstation computer using GigaDB MI datasets (52 subjects), its parameters were then extracted and converted to build deep-learning architecture interpreter on MCU. For comparison, EEG-Inception model was also trained using the same dataset, and was deployed on MCU. The results indicate that our deep-learning model can independently decode imaginary left-/right-hand motions. The mean accuracy of the proposed compact CNN reaches 96.75 ± 2.41% (8 channels: Frontocentral3 (FC3), FC4, Central1 (C1), C2, Central-Parietal1 (CP1), CP2, C3, and C4), versus 76.96 ± 19.08% of EEG-Inception (6 channels: FC3, FC4, C1, C2, CP1, and CP2). To the best of our knowledge, this is the first portable deep-learning decoder for MI EEG signals. The findings demonstrate high-accuracy deep-learning decoding of MI EEG in a portable mode, which has great implications for hand-disabled patients. Our portable system can be used for developing artificial-intelligent wearable BCI devices, as it is less computationally expensive and convenient for real-life application.
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Affiliation(s)
- Zhanxiong Wu
- School of Electronic Information, Hangzhou Dianzi University, Hangzhou, 310018, Zhejiang, China.
| | - Xudong Tang
- School of Electronic Information, Hangzhou Dianzi University, Hangzhou, 310018, Zhejiang, China
| | - Jinhui Wu
- School of Electronic Information, Hangzhou Dianzi University, Hangzhou, 310018, Zhejiang, China
| | - Jiye Huang
- School of Electronic Information, Hangzhou Dianzi University, Hangzhou, 310018, Zhejiang, China
| | - Jian Shen
- Neurosurgery Department, The First Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang University, Hangzhou, 310003, Zhejiang, China
| | - Hui Hong
- School of Electronic Information, Hangzhou Dianzi University, Hangzhou, 310018, Zhejiang, China
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Zhang H, Rong G, Bian S, Sawan M. Lab-on-Chip Microsystems for Ex Vivo Network of Neurons Studies: A Review. Front Bioeng Biotechnol 2022; 10:841389. [PMID: 35252149 PMCID: PMC8888888 DOI: 10.3389/fbioe.2022.841389] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 01/17/2022] [Indexed: 11/13/2022] Open
Abstract
Increasing population is suffering from neurological disorders nowadays, with no effective therapy available to treat them. Explicit knowledge of network of neurons (NoN) in the human brain is key to understanding the pathology of neurological diseases. Research in NoN developed slower than expected due to the complexity of the human brain and the ethical considerations for in vivo studies. However, advances in nanomaterials and micro-/nano-microfabrication have opened up the chances for a deeper understanding of NoN ex vivo, one step closer to in vivo studies. This review therefore summarizes the latest advances in lab-on-chip microsystems for ex vivo NoN studies by focusing on the advanced materials, techniques, and models for ex vivo NoN studies. The essential methods for constructing lab-on-chip models are microfluidics and microelectrode arrays. Through combination with functional biomaterials and biocompatible materials, the microfluidics and microelectrode arrays enable the development of various models for ex vivo NoN studies. This review also includes the state-of-the-art brain slide and organoid-on-chip models. The end of this review discusses the previous issues and future perspectives for NoN studies.
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Affiliation(s)
| | | | - Sumin Bian
- CenBRAIN Lab, School of Engineering, Westlake University, Hangzhou, China
| | - Mohamad Sawan
- CenBRAIN Lab, School of Engineering, Westlake University, Hangzhou, China
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Tost A, Migliorelli C, Bachiller A, Medina-Rivera I, Romero S, García-Cazorla Á, Mañanas MA. Choosing Strategies to Deal with Artifactual EEG Data in Children with Cognitive Impairment. ENTROPY (BASEL, SWITZERLAND) 2021; 23:1030. [PMID: 34441170 PMCID: PMC8392530 DOI: 10.3390/e23081030] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/15/2021] [Revised: 07/23/2021] [Accepted: 08/05/2021] [Indexed: 12/21/2022]
Abstract
Rett syndrome is a disease that involves acute cognitive impairment and, consequently, a complex and varied symptomatology. This study evaluates the EEG signals of twenty-nine patients and classify them according to the level of movement artifact. The main goal is to achieve an artifact rejection strategy that performs well in all signals, regardless of the artifact level. Two different methods have been studied: one based on the data distribution and the other based on the energy function, with entropy as its main component. The method based on the data distribution shows poor performance with signals containing high amplitude outliers. On the contrary, the method based on the energy function is more robust to outliers. As it does not depend on the data distribution, it is not affected by artifactual events. A double rejection strategy has been chosen, first on a motion signal (accelerometer or EEG low-pass filtered between 1 and 10 Hz) and then on the EEG signal. The results showed a higher performance when working combining both artifact rejection methods. The energy-based method, to isolate motion artifacts, and the data-distribution-based method, to eliminate the remaining lower amplitude artifacts were used. In conclusion, a new method that proves to be robust for all types of signals is designed.
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Affiliation(s)
- Ana Tost
- Biomedical Engineering Research Centre (CREB), Department of Automatic Control (ESAII), Universitat Politècnica de Catalunya (UPC), 08028 Barcelona, Spain; (C.M.); (A.B.); (S.R.); (M.A.M.)
| | - Carolina Migliorelli
- Biomedical Engineering Research Centre (CREB), Department of Automatic Control (ESAII), Universitat Politècnica de Catalunya (UPC), 08028 Barcelona, Spain; (C.M.); (A.B.); (S.R.); (M.A.M.)
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), 28029 Madrid, Spain
- Institut de Recerca Sant Joan de Déu, 08950 Barcelona, Spain; (I.M.-R.); (Á.G.-C.)
| | - Alejandro Bachiller
- Biomedical Engineering Research Centre (CREB), Department of Automatic Control (ESAII), Universitat Politècnica de Catalunya (UPC), 08028 Barcelona, Spain; (C.M.); (A.B.); (S.R.); (M.A.M.)
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), 28029 Madrid, Spain
- Institut de Recerca Sant Joan de Déu, 08950 Barcelona, Spain; (I.M.-R.); (Á.G.-C.)
| | - Inés Medina-Rivera
- Institut de Recerca Sant Joan de Déu, 08950 Barcelona, Spain; (I.M.-R.); (Á.G.-C.)
| | - Sergio Romero
- Biomedical Engineering Research Centre (CREB), Department of Automatic Control (ESAII), Universitat Politècnica de Catalunya (UPC), 08028 Barcelona, Spain; (C.M.); (A.B.); (S.R.); (M.A.M.)
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), 28029 Madrid, Spain
- Institut de Recerca Sant Joan de Déu, 08950 Barcelona, Spain; (I.M.-R.); (Á.G.-C.)
| | - Ángeles García-Cazorla
- Institut de Recerca Sant Joan de Déu, 08950 Barcelona, Spain; (I.M.-R.); (Á.G.-C.)
- Neurometabolic Unit and Synaptic Metabolism Lab, Neurology Department, Institut Pediàtric de Recerca, Hospital Sant Joan de Déu, metabERN and CIBERER-ISCIII, 08950 Barcelona, Spain
| | - Miguel A. Mañanas
- Biomedical Engineering Research Centre (CREB), Department of Automatic Control (ESAII), Universitat Politècnica de Catalunya (UPC), 08028 Barcelona, Spain; (C.M.); (A.B.); (S.R.); (M.A.M.)
- CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), 28029 Madrid, Spain
- Institut de Recerca Sant Joan de Déu, 08950 Barcelona, Spain; (I.M.-R.); (Á.G.-C.)
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Dominguez-Rodriguez A, Chavez-Valdez S, Avitia G, Valencia-Espinoza L. Unified protocol for anxiety disorders in two cities of Mexico measuring gamma activity: Study protocol for a randomized controlled trial. Contemp Clin Trials Commun 2020; 18:100556. [PMID: 32274440 PMCID: PMC7136174 DOI: 10.1016/j.conctc.2020.100556] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2019] [Revised: 03/02/2020] [Accepted: 03/14/2020] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND The Unified Protocol for Emotional Disorders (UP) for emotional regulation manifests effective results in a broad range of mental disorders. The UP efficacy was tested in several countries, but it has not been tested within Mexican population. It is crucial to do more research and implement effective protocols to intervene Mexican population with Anxiety Disorders (AD). OBJECTIVE This study aims to examine and describe the research procedures and treatment interventions of the UP in a Randomized Controlled Trial (RCT), to approach and treat AD in patients in 2 Mexican borderland cities, by applying the UP and an Electroencephalogram (EGG) neuro screening. METHODS The enrolled patients will be randomized in a two-arm control trial with repeated measures, comprising between 18 and 60 years, that were diagnosed with an AD, and low scored in depression symptoms and suicidal ideation. The study will comprise of two conditions: an intervention group clinical trial with the UP or a waiting list control. The primary outcome measures will be applied on AD quantitative self-reports and a gamma activity by EGG before and after the intervention and in follow-ups of 3 and 6 months. The participants in the waiting list group, will receive the treatment after the trial first group completes the treatment. CONCLUSIONS Processes and outcomes of this project, will provide evidence in order to apply the UP in a broader population with AD and other mental disorders also covered by this protocol, such as depression and borderline personality disorder in a broader Mexican population, a country that suffers with a major health issue with an increasing rate of mental disorders and scarce psychological and health coverage.
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Affiliation(s)
- A. Dominguez-Rodriguez
- Faculty of Medicine and Psychology, Autonomous University of Baja California, Calzada Universidad 14418, Parque Industrial Internacional Tijuana, Tijuana, B.C, 22427, Mexico
| | - S.M. Chavez-Valdez
- Faculty of Psychology, Escuela Libre de Psicología, A.C. ELPAC-Universidad de Ciencias del Comportamiento, ELPAC University of Behavioral Sciences, Calle Pedro Zuloaga #8805, Colonia Labor de Terrazas, Chihuahua, Chih, 31207, Mexico
| | - G.C. Avitia
- Institute of Social Sciences and Administration, Autonomous University of Ciudad Juárez, Av. Universidad y Av. Heroico Colegio Militar Zona Chamizal, 32300, Juarez, Chihuahua, Mexico
| | - L.C. Valencia-Espinoza
- Faculty of Medicine and Psychology, Autonomous University of Baja California, Calzada Universidad 14418, Parque Industrial Internacional Tijuana, Tijuana, B.C, 22427, Mexico
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