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Development of an Adaptive Artifact Subspace Reconstruction Based on Hebbian/Anti-Hebbian Learning Networks for Enhancing BCI Performance

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IEEE Transactions on Neural Networks and Learning Systems 2024年第1期35卷 348-361页

作者： Tsai, Bo-Yu Diddi, Sandeep Vara Sankar Ko, Li-Wei Wang, Shuu-Jiun Chang, Chi-Yuan Jung, Tzyy-Ping Institute of Biomedical Engineering and the Brain Research Center National Yang Ming Chiao Tung University Hsinchu300 Taiwan Hsinchu300 Taiwan College of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu300 Taiwan Institute of Electrical and Control Engineering Institute of Biomedical Engineering Brain Research Center College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Department of Electronics and Electrical Engineering Hsinchu300 Taiwan Kaohsiung Medical University Department of Biomedical Science and Environment Biology Drug Development and Value Creation Research Center Kaohsiung807 Taiwan Taipei Veterans General Hospital Taipei11217 Taiwan National Yang Ming Chiao Tung University Brain Research Center School of Medicine Taipei112 Taiwan University of California San Diego Swartz Center for Computational Neuroscience San DiegoCA92093 United States

Brain-computer interface (BCI) actively translates the brain signals into executable actions by establishing direct communication between the human brain and external devices. Recording brain activity through electroencephalography (EEG) is generally contaminated with both physiological and nonphysiological artifacts, which significantly hinders the BCI performance. Artifact subspace reconstruction (ASR) is a well-known statistical technique that automatically removes artifact components by determining the rejection threshold based on the initial reference EEG segment in multichannel EEG recordings. In real-world applications, the fixed threshold may limit the efficacy of the artifact correction, especially when the quality of the reference data is poor. This study proposes an adaptive online ASR technique by integrating the Hebbian/anti-Hebbian neural networks into the ASR algorithm, namely, principle subspace projection ASR (PSP-ASR) and principal subspace whitening ASR (PSW-ASR) that segmentwise self-organize the artifact subspace by updating the synaptic weights according to the Hebbian and anti-Hebbian learning rules. The effectiveness of the proposed algorithm is compared to the conventional ASR approaches on benchmark EEG dataset and three BCI frameworks, including steady-state visual evoked potential (SSVEP), rapid serial visual presentation (RSVP), and motor imagery (MI) by evaluating the root-mean-square error (RMSE), the signal-to-noise ratio (SNR), the Pearson correlation, and classification accuracy. The results demonstrated that the PSW-ASR algorithm effectively removed the EEG artifacts and retained the activity-specific brain signals compared to the PSP-ASR, standard ASR (Init-ASR), and moving-window ASR (MW-ASR) methods, thereby enhancing the SSVEP, RSVP, and MI BCI performances. Finally, our empirical results from the PSW-ASR algorithm suggested the choice of an aggressive cutoff range of c =1-10 for activity-specific BCI applications and a moderat

关键词： Electroencephalography

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An injectable curcumin-releasing organohydrogel with non-drying property and high mechanical stability at low-temperature for expe dite d skin wound care

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Journal of Materials Science & technology 2023年第2期133卷 123-134页

作者： Kang Wu Qiang Yang Lin Zhang Pengcheng Xu Xiexing Wu Huilin Yang Huan Zhou Xiao Lin Lei Yang College of Chemistry Chemical Engineering and Materials ScienceOrthopaedic InstituteDepartment of Orthopaedic SurgeryThe First Affiliated HospitalSoochow UniversitySuzhou 215031China Center for Health Sciences and Engineering(CHSE) School of Health Sciences and Biomedical EngineeringHebei University of TechnologyTianjin 300130China Department of Minimally Invasive Spine Surgery Tianjin HospitalTianjin 300211China

Although hydrogels have demonstrated great potential as new wound dressing materials,their instability in shape and/or mechanical characteristics due to water loss or freezing remains a shortcoming for wound care ***,a novel injectable organohydrogel(IOH)of physically crosslinked polyvinyl alco-hol/glycerol that possesses non-drying capability and high stability at low temperature was developed for wound *** has a skin-like stiffness(G’,∼280 Pa),high injectability,self-healing capability,high water-vapor transmission rate,and bacterial inhibitory *** exhibits high shape and mechanical stabilities after curing at 37°C and 50%relative humidity for 7 days or after curing at-20°C for 1 *** addition,glycerol in IOH enabled an efficient loading and release of water-insoluble curcumin,a well-known anti-bacterial and anti-inflammation *** curcumin-releasing IOH(Cur-IOH)demonstrated significantly enhanced anti-bacterial performance compared to IOH or curcumin-loading polyvinyl alco-hol *** importantly,Cur-IOH could accelerate wound healing in a murine full-thickness skin defect wound model,revealing improved wound contraction,collagen deposition,angiogenesis,and epi-dermis *** study demonstrates the great potential of organohydrogel for the reparation of severe wounds and Cur-IOH as a new type of injectable wound healing material.

关键词： Wound dressing Organohydrogel Non-drying Stability Curcumin

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Chondrogenic commitment of human umbilical cord blood and umbilical cord-derived mesenchymal stem cells induced by the supernatant of chondrocytes:A comparison study

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Animal Models and Experimental Medicine 2024年第6期7卷 793-801页

作者： Xingfu Li Zhenhan Deng Wei Lu Department of Orthopedics Shenzhen Second People's Hospital(The First Affiliated Hospital of Shenzhen UniversityHealth Science Center)ShenzhenChina Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging National-Regional Key Technology Engineering Laboratory for Medical UltrasoundSchool of Biomedical EngineeringShenzhen University Medical SchoolShenzhenChina Department of Orthopedics The First Affiliated Hospital of Wenzhou Medical UniversityWenzhouChina

Background:Native cartilage has low capacity for regeneration because it has very few progenitor *** umbilical cord blood-derived mesenchymal stem cells(hUCB-MSCs)and human umbilical cord-derived MSCs(hUC-MSCs)have been employed as promising sources of stem cells for cartilage injury *** of hyaline cartilage from MSCs remains a challenging *** paracrine factors secreted by chondrocytes possess the capability to induce chondrogenesis from ***:The conditioned medium derived from chondrocytes was utilized to induce chondrogenic differentiation of hUCB-MSCs and *** expression levels of collagen type I alpha 1 chain(Col1a1),collagen type II alpha 1 chain(Col2a1),and SRY-box transcription factor 9(SOX9)were assessed through quantitative real-time polymerase chain reaction(qRT-PCR),Western blot(WB),and immunofluorescence(IF)*** elucidate the mechanism of differentiation,the concentration of transforming growth factor-β1(TGF-β1)in the conditioned medium of chondrocytes was quantified using enzyme-l inked immunosorbent assay(ELISA).Meanwhile,the viability of cells was assessed using Cell Counting Kit-8(CCK-8)***:The expression levels of Col2a1 and SOX9 were found to be higher in induced hUC-MSCs compared to those in induced *** conditioned medium of chondrocytes contained TGF-β*** CCK-8 assays revealed that the proliferation rate of hUC-MSCs was significantly higher compared to that of ***:The chondrogenic potential and proliferation capacity of hUC-MSCs surpass those of hUCB-MSCs,thereby establishing hUC-MSCs as a superior source of seed cells for cartilage tissue engineering.

关键词： cartilage diseases chondrogenic differentiation mesenchymal stem cells

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Hybrid Microfabrication, and Electrochemical Analysis of Nonagonal 2d/3d Microelectrode Arrays, with Multi-Metallic Interfaces 22

Hybrid Microfabrication, and Electrochemical Analysis of Non...

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22nd International Conference on Solid-State Sensors, Actuators and Microsystems, Transducers 2023

作者： Didier, Charles M. Corina Garcia-Chalbaud, Maria Orrico, Julia F. Manrique Castro, Jorge Rajaraman, Swaminathan University Of Central Florida NanoScience Technology Center United States Polytechnic University Of Puerto Rico Department Of Biomedical Engineering Puerto Rico

ISBN: (纸本)9784886864352

Microelectrode Arrays (MEAs) are an innovative class of sensors which are essential interfaces to in vitro biological models of human disease conditions on-a-chip. This research study contributes to advances in the "Organ-on-Chip"field, providing electrical, geometric, material, and other design options, for the next generation of 2D/3D MEAs. Herein, four combinatorial, microfabricated nonagonal microelectrode arrays (MEAs) with varied multi-metallic materials and geometric considerations are presented. Investigations on how multi-material 2D/3D microfabrication and multi-metallic interfaces impact MEA performance, particularly impedance were studied, and functional quantitative differences were elucidated utilizing equivalent circuit modelling and Nyquist Plot analysis. © 2023 IEEJ.

关键词： Electrochemical Impedance Spectroscopy (EIS) Hybrid Microfabrication Microdrilling (μD) Microelectrode Arrays (MEAs) Micromilling (μM) Multi-Metallic Interfaces

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One-step preparation of modified photothermal-driven melamine foam with gradient wettability for oil-waterseparation

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Frontiers of Materials Science 2024年第3期18卷 71-82页

作者： Mengdan Jia Mei-Chen Lin Hai-Tao Ren Bing-Chiuan Shiu Ching-Wen Lou Zhi-Ke Wang Li-Yan Liu Ting-Ting Li Innovation Platform of Intelligent and Energy-Saving Textiles School of Textile Science and EngineeringTiangongUniversityTianjin 300387China Tianjin and Ministry of Education Key Laboratory for Advanced Textile Composite Materials Tiangong UniversityTianjin 300387China Department of Biomedical Engineering College of Biomedical EngineeringChina Medical UniversityTaichung 404333China College of Material and Chemical Engineering Minjiang UniversityFuzhou 350108China Department of Bioinformatics and Medical Engineering AsiaUniversityTaichung 413305China Department of Medical Research China Medical University HospitalChina Medical UniversityTaichung 404333China Advanced Medical Care and Protection Technology Research Center College of Textile and ClothingQingdaoUniversityQingdao 266071China Department of Textile and Clothing Shandong Vocational College of Science and TechnologyWeifang 261053China

The absorption of high-viscosity oil by traditional oil absorbing materials has always been a *** there is an urgent need to solve the problem of slow absorption of high-viscosity *** this work,an emulsion composed of polydimethylsiloxane(PDMS),carbon black(CB)and waterborne polyurethane(solid content 40%)was sprayed on the melamine foam(MF).After volatilization of organic solvents,the photothermal material CB was fixed on the MF framework,making it *** raising the temperature of the modified foam to accelerate the internal thermal movement of high-viscosity oil molecules around the foam,intermolecular forces are reduced,thereby accelerating the separation *** absorption capacity of this modified MF towards organic solvents and oil is up to 79 times its own *** addition,the mechanical properties of the modified foam are improved to a certain extent,more conducive to the continuous oil-water *** photothermal absorption material provides ideas for the rapid removal of high-viscosity oil,heavy oil,etc.

关键词： photothermal high-viscosity oil oil-water separation

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KDTL: knowledge-distilled transfer learning framework for diagnosing mental disorders using EEG spectrograms

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Neural Computing and Applications 2024年第30期36卷 18919-18934页

作者： Singh, Shreyash Jadli, Harshit Padma Priya, R. Surya Prasath, V.B. Department of Software Systems School of Computer Science and Engineering Vellore Institute of Technology Vellore India Division of Biomedical Informatics Cincinnati Children’s Hospital Medical Center CincinnatiOH45229 United States Department of Pediatrics University of Cincinnati College of Medicine CincinnatiOH45257 United States Department of Biomedical Informatics College of Medicine University of Cincinnati CincinnatiOH45267 United States Department of Computer Science University of Cincinnati CincinnatiOH45221 United States

Electroencephalography (EEG) is a well-known modality in neuroscience and is widely used in identifying and classifying neurological disorders. This paper investigates how EEG data can be used along with knowledge distillation-based deep learning models to detect mental disorders like epilepsy and sleep disorders. The EEG signals are converted into time–frequency plots using short-time Fourier transforms. Further, we propose a novel methodology for using knowledge distillation-based transfer learning (KDTL). Knowledge distillation is becoming quite prevalent in the machine learning field and is associated with various applications in our work;we propose its use in the detection of mental disorders from EEG spectrograms. We convert the EEGs using short-term Fourier transform to obtain time–frequency representation and apply teacher-student by first training a large teacher model and use knowledge distillation to train a student model. In our experiments, we found that ConvNext teacher and MobileNet student combination obtained better results. Our proposed KDTL approach is tested on two datasets with multiple cases, namely the Bonn and ISRUC datasets and obtain 98% and 95% accuracies, respectively. Further experimental results show that the overall KDTL methodology can obtain high classification accuracy across both datasets in binary and multiclass classifications and proves to be better than multiple prior works. Further, our KDTL approach provides a way to train lightweight models which have a smaller number of trainable parameters and thereby constitute lower training time overall. Our proposed KDTL-based approach obtained accurate results in diagnosing mental disorders from EEG spectrograms. Compared to other related methods, KDTL outperformed across tasks with obtained good results in both binary and multiclass classifications. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Electroencephalography

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Design principles in mechanically adaptable biomaterials for repairing annulus fibrosus rupture:A review

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Bioactive Materials 2024年第1期31卷 422-439页

作者： Dan Zhou Hongmei Liu Zhaomin Zheng Decheng Wu Guangdong Provincial Key Laboratory of Advanced Biomaterials Department of Biomedical EngineeringSouthern University of Science and TechnologyShenzhen518055China Department of Spine Surgery The First Affiliated HospitalSun Yat-Sen UniversityGuangzhou510080China Pain Research Center Sun Yat-Sen UniversityGuangzhou 510080China

Annulus fibrosus(AF)plays a crucial role in the biomechanical loading of intervertebral disc(IVD).AF is difficult to self-heal when the annulus tears develop,because AF has a unique intricate structure and biologic milieu in *** engineering is promising for repairing AF rupture,but construction of suitable mechanical matching devices or scaffolds is still a grand *** deeply know the varied forces involved in the movement of the native annulus is highly beneficial for designing biomimetic scaffolds to recreate the AF *** this review,we overview six freedom degrees of forces and adhesion strength on AF ***,we summarize the mechanical modalities to simulate related forces on AF and to assess the characteristics of *** finally outline some current advanced techniques to develop mechanically adaptable biomaterials for AF rupture repair.

关键词： Annulus fibrosus Forces Mechanical matching High tough High adhesion

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NIR-Responsive Methotrexate-Modified Iron Selenide Nanorods for Synergistic Magnetic Hyperthermic, Photothermal, and Chemodynamic Therapy

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ACS Applied Materials and Interfaces 2024年第20期16卷 25622-25636页

作者： Thirumurugan, Senthilkumar Muthiah, Kayalvizhi Samuvel Lin, Yu-Chien Dhawan, Udesh Liu, Wai-Ching Wang, An-Ni Liu, Xinke Hsiao, Michael Tseng, Ching-Li Chung, Ren-Jei No. 1 Section 3 Zhongxiao East Road Taipei10608 Taiwan Centre for the Cellular Microenvironment Division of Biomedical Engineering James Watt School of Engineering Mazumdar-Shaw Advanced Research Centre University of Glasgow GlasgowG116EW United Kingdom Faculty of Science and Technology Technological and Higher Education Institute of Hong Kong Hong Kong New Territories999077 Hong Kong Scrona AG Grubenstrasse 9 Zürich8045 Switzerland College of Materials Science and Engineering Chinese Engineering and Research Institute of Microelectronics Shenzhen University Shenzhen518060 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Genomics Research Center Academia Sinica Taipei115 Taiwan Department and Graduate Institute of Veterinary Medicine School of Veterinary Medicine National Taiwan University Taipei10617 Taiwan Graduate Institute of Biomedical Materials and Tissue Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan International Ph.D. Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Research Center of Biomedical Device College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan International Ph.D. Program in Cell Therapy and Regenerative Medicine College of Medicine Taipei Medical University Taipei11031 Taiwan Taipei10608 Taiwan

Breast cancer is a malignant tumor with a high mortality rate among women. Therefore, it is necessary to develop novel therapies to effectively treat this disease. In this study, iron selenide nanorods (FeSe2 NRs) were designed for use in magnetic hyperthermic, photothermal, and chemodynamic therapy (MHT/PTT/CDT) for breast cancer. To illustrate their efficacy, FeSe2 NRs were modified with the chemotherapeutic agent methotrexate (MTX). MTX-modified FeSe2 (FeSe2-MTX) exhibited excellent controlled drug release properties. Fe2+ released from FeSe2 NRs induced the release of •OH from H2O2 via a Fenton/Fenton-like reaction, enhancing the efficacy of CDT. Under alternating magnetic field (AMF) stimulation and 808 nm laser irradiation, FeSe2-MTX exerted potent hyperthermic and photothermal effects by suppressing tumor growth in a breast cancer nude mouse model. In addition, FeSe2 NRs can be used for magnetic resonance imaging in vivo by incorporating their superparamagnetic characteristics into a single nanomaterial. Overall, we presented a novel technique for the precise delivery of functional nanosystems to tumors that can enhance the efficacy of breast cancer treatment. © 2024 The Authors. Published by American Chemical Society

关键词： Magnetic resonance imaging

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Inhibiting scar formation via wearable multilayer stacked electret patch:Self-creation of persistent and customizable DC electric field for fibrogenic activity restriction

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InfoMat 2024年第3期6卷 66-80页

作者： Sung-Won Kim Sumin Cho Donghan Lee Jiyu Hyun Sunmin Jang Inwoo Seo Hyun Su Park Hee Jae Hwang Hyung-Seop Han Dae Hyeok Yang Heung Jae Chun Suk Ho Bhang Dongwhi Choi School of Chemical Engineering Sungkyunkwan UniversitySuwonRepublic of Korea Department of Mechanical Engineering(Integrated Engineering Program) Kyung Hee UniversityYonginGyeonggiRepublic of Korea Biomaterials Research Center Biomedical Research DivisionKorea Institute of Science and Technology(KIST)SeoulRepublic of Korea Department of Medical Life Sciences College of MedicineInstitute of Cell and Tissue EngineeringThe Catholic University of KoreaSeoulRepublic of Korea

Electrical stimulation has recently received attention as noninvasive treatment in skin wound healing with its outstanding biological property for clinical ***,the complexity of equipment for applying appropriate electrical stimulation remains an ongoing ***,we proposed a strategy for skin scar inhibition by providing electrical stimulation via a multilayer stacked electret(MS-electret),which can generate direct current(DC)electric field(EF)without any power supply *** addition,the MS-electret can easily control the intensity of EFs by simply stacking electret layers and maintain stable EF with the surface potential of 3400 V over 5 days owing to the injected charges on the electret *** confirmed inhibition of type 1 collagen andα-SMA expression of human dermal fibroblasts(hDFs)by 90%and 44%in vitro,indicating that the transition of hDFs to myofibroblasts was restricted by applying stable electrical *** further revealed a 20%significant decrease in the ratio of myofibroblasts caused by the MS-electret in *** findings present that the MS-electret is an outstanding candidate for effective skin scar inhibition with a battery-free,physiological electrical microenvironment,and noninvasive treatment that allows it to prevent external infection.

关键词： DC electric field dermal fibroblasts electret scar formation restriction self-creation of electrical stimulation

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Cervical Cancer Classification Using Combined Machine Learning and Deep Learning Approach

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Computers, Materials & Continua 2022年第9期72卷 5117-5134页

作者： Hiam Alquran Wan Azani Mustafa Isam Abu Qasmieh Yasmeen Mohd Yacob Mohammed Alsalatie Yazan Al-Issa Ali Mohammad Alqudah Department of Biomedical Engineering Jordan University of Science and TechnologyIrbid22110Jordan Department of Biomedical Systems and Informatics Engineering Yarmouk University 556Irbid21163Jordan Faculty of Electrical Engineering Technology Campus Pauh PutraUniversiti Malaysia Perlis02000ArauPerlisMalaysia Advanced Computing Centre of Excellence(CoE)Universiti Malaysia Perlis(UniMAP)02000ArauPerlisMalaysia The Institute of Biomedical Technology King Hussein Medical CenterRoyal Jordanian Medical ServiceAmman11855Jordan Department of Computer Engineering Yarmouk UniversityIrbid21163Jordan

Cervical cancer is screened by pap smear methodology for detection and classification *** smear images of the cervical region are employed to detect and classify the abnormality of cervical *** this paper,we proposed the first system that it ables to classify the pap smear images into a seven classes *** smear images are exploited to design a computer-aided diagnoses system to classify the abnormality in cervical images *** features that have been extracted using ResNet101 are employed to discriminate seven classes of images in Support Vector Machine(SVM)*** success of this proposed system in distinguishing between the levels of normal cases with 100%accuracy and 100%*** top of that,it can distinguish between normal and abnormal cases with an accuracy of 100%.The high level of abnormality is then studied and classified with a high *** the other hand,the low level of abnormality is studied separately and classified into two classes,mild and moderate dysplasia,with∼92%*** proposed system is a built-in cascading manner with five models of polynomial(SVM)*** overall accuracy in training for all cases is 100%,while the overall test for all seven classes is around 92%in the test phase and overall accuracy reaches 97.3%.The proposed system facilitates the process of detection and classification of cervical cells in pap smear images and leads to early diagnosis of cervical cancer,which may lead to an increase in the survival rate in women.

关键词： Classification deep learning machine learning pap smear images resnet101 support vector machines

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