A5100326592- EEG and Brain-Computer Interfaces
- Non-Invasive Vital Sign Monitoring
- ECG Monitoring and Analysis
- Obstructive Sleep Apnea Research
- Functional Brain Connectivity Studies
- Network Security and Intrusion Detection
- Advanced Image and Video Retrieval Techniques
- Video Surveillance and Tracking Methods
- Advanced X-ray and CT Imaging
- Belt Conveyor Systems Engineering
- Bioinformatics and Genomic Networks
- Gaze Tracking and Assistive Technology
- Blind Source Separation Techniques
- Privacy-Preserving Technologies in Data
- Indoor and Outdoor Localization Technologies
- Recommender Systems and Techniques
- Robotics and Sensor-Based Localization
- Radiomics and Machine Learning in Medical Imaging
- Neuroscience and Neural Engineering
- Advanced Sensor and Control Systems
- Neural dynamics and brain function
- Sleep and Wakefulness Research
- Energy Efficient Wireless Sensor Networks
- Topic Modeling
- Power Line Inspection Robots
Heilongjiang University of Chinese Medicine
2025
Wuhan Institute of Virology
2023-2025
Chinese Academy of Sciences
2023-2025
Xiangtan University
2020-2025
Shandong University of Science and Technology
2011-2025
University of Chinese Academy of Sciences
2023-2025
Guangxi University
2008-2025
Chongqing Medical University
2025
Nanjing Drum Tower Hospital
2025
Southwest University
2011-2024
Wireless sensor networks (WSNs) have witnessed rapid advancement in medical applications from real-time telemonitoring and computer-assisted rehabilitation to emergency response systems. In this paper, we present the state-of-the-art research ubiquity perspective, discuss insights as well vision of future directions WSN-based healthcare First, propose a novel tiered architecture that can be generally applied Then, analyze IEEE 802 series standards access layer on their capabilities setting...
Epilepsy seizure prediction paves the way of timely warning for patients to take more active and effective intervention measures. Compared detection that only identifies inter-ictal state ictal state, far fewer researches have been conducted on because high similarity makes it challenging distinguish between pre-ictal state. In this paper, a novel solution is proposed using common spatial pattern (CSP) convolutional neural network (CNN). Firstly, artificial preictal EEG signals based...
Iontronic pressure sensors are promising in robot haptics because they can achieve high sensing performance using nanoscale electric double layers (EDLs) for capacitive signal output. However, it is challenging to both sensitivity and mechanical stability these devices. need microstructures that offer subtly changeable EDL interfaces boost sensitivity, while the microstructured mechanically weak. Here, we embed isolated ionic gel (IMIG) a hole array (28 × 28) of elastomeric matrix cross-link...
Abstract Humans can gently slide a finger on the surface of an object and identify it by capturing both static pressure high-frequency vibrations. Although modern robots integrated with flexible sensors precisely detect pressure, shear force, strain, they still perform insufficiently or require multi-sensors to respond physical stimuli during interaction. Here, we report real-time artificial sensory system for high-accuracy texture recognition based single iontronic slip-sensor, propose...
The utility of endophytic bacteria in Cadmium (Cd) remediation has gained significant attention due to their ability alleviate metal-induced stress and enhance plant growth. Here, we investigate C. metallidurans CML2, an bacterial strain prevalent rice, showing resilience against 2400 mg/L Cd(II). We conducted in-depth integrated morphological transcriptomic analysis illustrating the multifarious mechanisms CML2 employs combat Cd, including formation biofilm CdO nanoparticles, upregulation...
Abstract Objectives This study aimed to reveal the anti-fibrotic effects of Botrychium ternatum (Thunb.) Sw. (BT) against idiopathic pulmonary fibrosis (IPF) and preliminarily analyze its potential mechanism on bleomycin-induced IPF rats. Methods The inhibition progression in vivo was assessed by histopathology combined with biochemical indicators. In addition, metabolic regulatory investigated using 1H-nuclear magnetic resonance-based metabolomics multivariate statistical analysis. Key...
Blood glucose level needs to be monitored regularly manage the health condition of hyperglycemic patients. The current measurement approaches still rely on invasive techniques which are uncomfortable and raise risk infection. To facilitate daily care at home, in this article, we propose an intelligent, noninvasive blood monitoring system can differentiate a user's into normal, borderline, warning based smartphone photoplethysmography (PPG) signals. main implementation processes proposed...
Session-based recommendation aims to predict a user's next action based on previous actions in the current session. The major challenge is capture authentic and complete user preferences entire Recent work utilizes graph structure represent session adopts Graph Neural Network (GNN) encode information. This modeling choice has been proved be effective achieved remarkable results. However, most of existing studies only consider each item within independently do not semantics from high-level...
The electroencephalogram (EEG), for measuring the electrophysiological activity of brain, has been widely applied in automatic detection epilepsy seizures. Various EEG-based seizure algorithms have already yielded high sensitivity, but training those requires a large amount labelled data. Data labelling is often done with lot human efforts, which very time-consuming. In this study, we propose hybrid system integrating an unsupervised learning (UL) module and supervised (SL) module, where UL...
Abstract Facial palsy (FP) profoundly influences interpersonal communication and emotional expression, necessitating precise diagnostic monitoring tools for optimal care. However, current electromyography (EMG) systems are limited by their bulky nature, complex setups, dependence on skilled technicians. Here we report an innovative biosensing approach that utilizes a PEDOT:PSS-modified flexible microneedle electrode array (P-FMNEA) to overcome the limitations of existing EMG devices. Supple...
The development of smart cities and the emergence three-dimensional (3-D) urban terrain data have introduced new requirements issues to research on 3-D deployment wireless sensor networks. We study issue heterogeneous directional networks in cities. Traditionally, studies problem WSNs focus omnidirectional sensors a 2-D plane or full space. Based data, we transform into multiobjective optimization problem, which objectives Coverage, Connectivity Quality, Lifetime, as well Reliability...
Autism spectrum disorder (ASD) is an intricate neuropsychiatric brain characterized by social deficits and repetitive behaviors. Deep learning approaches have been applied in clinical or behavioral identification of ASD; most erstwhile models are inadequate their capacity to exploit the data richness. On other hand, classification techniques often solely rely on region-based summary and/or functional connectivity analysis magnetic resonance imaging (fMRI). Besides, biomedical modeling...
Noninvasive blood glucose (BG) measurement could significantly improve the prevention and management of diabetes. In this paper, we present a robust novel paradigm based on analyzing photoplethysmogram (PPG) signals. The method includes signal pre-processing optimization multi-view cross-fusion transformer (MvCFT) network for non-invasive BG assessment. Specifically, multi-size weighted fitting (MSWF) time-domain filtering algorithm is proposed to optimally preserve most authentic...
With the ultimate intent of improving quality life, identification human's affective states on collected electroencephalogram (EEG) has attracted lots attention recently. In this domain, existing methods usually use only a few labeled samples to classify consisting over thousands features. Therefore, important information may not be well utilized and performance is lowered due randomness caused by small sample problem. However, issue rarely been discussed in previous studies. Besides, many...