Adaptive Stepwise Feature Selection Approach for EEG-Based Epileptic Seizure Classification.

Recent advancements in feature selection (FS) optimization algorithms have influenced the field of epileptic seizure classification. However, integrating these optimization algorithms into machine learning (ML) models often creates time complexity, limiting their clinical deployment. To address this issue, we propose an innovative adaptive stepwise FS method tailored for epileptic seizure detection (ESD).

An Attention-Based Hybrid Deep Learning Approach for Patient-Specific, Cross-Patient, and Patient-Independent Seizure Detection.

Automatic detection of epilepsy plays a crucial role in diagnosing and treatment of patients, while most current methods rely on patient-specific models and have shown promising results, which is not suitable for clinical application, especially when new patient data are used for diagnosis in EEG epileptic seizure detection (ESD). Therefore, the proposed study introduces a novel hybrid deep learning approach consisting of a one-dimensional convolutional neural network (1D CNN), a Multi-Long Short-Term Memory Network (MLSTM) with a multi-attention layer (MAT) for patient-specific, cross-patient, and patient-independent seizure detection. The 1D CNN model extracts spatial features, while the MLSTM extracts temporal features from segmented EEG data.

Revivable self-assembled supramolecular biomass fibrous framework for efficient microplastic removal.

Microplastic remediation in aquatic bodies is essential for the entire ecosystem, but is challenging to achieve with a universal and efficient strategy. Here, we developed a sustainable and environmentally adaptable adsorbent through supramolecular self-assembly of chitin and cellulose. This biomass fibrous framework (Ct-Cel) showcases an excellent adsorption performance for polystyrene, polymethyl methacrylate, polypropylene, and polyethylene terephthalate.

Personalization of clopidogrel therapy based on genetic polymorphism analysis: clinical implications.

Objective: This study aimed to evaluate the impact of gene polymorphisms on clopidogrel metabolism and to use this analysis to inform treatment strategy for a population in southern Anhui of China.

Methods: The research was conducted from 2019 to 2022, aincluding 430 patients from the Wuhu Hospital, affiliated with East China Normal University who were candidates for clopidogrel therapy. Genes influencing clopidogrel's absorption and metabolism were analyzed to guide treatment.

[Advances in nanostructured surfaces for enhanced mechano-bactericidal applications].

The issue of bacterial drug resistance has remained unresolved, and in recent years, biomimetic nanostructured surfaces inspired by nature have garnered significant attention due to their bactericidal properties demonstrated through mechanical mechanisms. This article reviewed the main research progress in the field of nanostructured mechanical bactericidal surfaces, including various preparation methods for nanostructured surfaces with mechanical bactericidal properties, as well as the basic mechanisms and related physical models of the interaction between bacteria and nanostructured surfaces. In addition, the application of nanostructured surfaces in biomedicine was introduced.

Activating Adsorption Sites of Waste Crayfish Shells via Chemical Decalcification for Efficient Capturing of Nanoplastics.

The property of being stubborn and degradation resistant makes nanoplastic (NP) pollution a long-standing remaining challenge. Here, we apply a designed top-down strategy to leverage the natural hierarchical structure of waste crayfish shells with exposed functional groups for efficient NP capture. The crayfish shell-based organic skeleton with improved flexibility, strength (14.

Adhesive Carbon Paste Electrode for Convenient and Long-term Electrocardiogram Monitoring: A Pilot Study.

Long-term electrocardiogram (ECG) monitoring is an important and widely-used technique in the clinic that helps with the diagnosis of possible diseases that cannot be detected in a short time monitoring. However, the clinically used electrode needs conductive gel to reduce the impedance between the skin and the electrodes, which easily causes the possibility of allergy. Moreover, as the conductive gel becomes dry, the signal's quality will decrease accordingly.

Highly Anthropomorphic Finger Design With a Novel Friction Clutch for Achieving Human-Like Reach-and-Grasp Movements.

In the design of prosthetic hand fingers, achieving human-like movement while meeting anthropomorphic demands such as appearance, size, and lightweight is quite challenging. Human finger movement involves two distinct motion characters during natural reach-and-grasp tasks: consistency in the reaching stage and adaptability in the grasping stage. The former one enhances grasp stability and reduces control complexity; the latter one promotes the adaptability of finger to various objects.

A Scalable Video Multicast Scheme Based on User Demand Perception and D2D Communication.

With the widespread application of 5G technology, there has been a significant surge in wireless video service demand and video traffic due to the proliferation of smart terminal devices and multimedia applications. However, the complexity of terminal devices, heterogeneous transmission channels, and the rapid growth of video traffic present new challenges for wireless network-based video applications. Although scalable video coding technology effectively improves video transmission efficiency in complex networks, traditional cellular base stations may struggle to handle video transmissions for all users simultaneously, particularly in large-scale networks.

Classification of attention deficit/hyperactivity disorder based on EEG signals using a EEG-Transformer model.

. Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder in adolescents that can seriously impair a person's attention function, cognitive processes, and learning ability. Currently, clinicians primarily diagnose patients based on the subjective assessments of the Diagnostic and Statistical Manual of Mental Disorders-5, which can lead to delayed diagnosis of ADHD and even misdiagnosis due to low diagnostic efficiency and lack of well-trained diagnostic experts.

A Microservice and Serverless Architecture for Secure IoT System.

In cross-border transactions, the transmission and processing of logistics information directly affect the trading experience and efficiency. The use of Internet of Things (IoT) technology can make this process more intelligent, efficient, and secure. However, most traditional IoT logistics systems are provided by a single logistics company.

High-Precision and Rapid Direct Laser Writing Using a Liquid Two-Photon Polymerization Initiator.

Two-photon polymerization based direct laser writing (DLW) is an emerging micronano 3D fabrication technology wherein two-photon initiators (TPIs) are a key component in photoresists. Upon exposure to a femtosecond laser, TPIs can trigger the polymerization reaction, leading to the solidification of photoresists. In other words, TPIs directly determine the rate of polymerization, physicochemical properties of polymers, and even the photolithography feature size.

Using Flexible and Stretchable Surface Electromyography Electrode Array to Evaluate Congenital Muscular Torticollis in Children.

Congenital Muscular Torticollis (CMT) is a neuromuscular disease in children, which leads to exacerbation of postural deformity and neck muscle dysfunction with age. Towards facilitating functional assessment of neuromuscular disease in children, topographic electromyography (EMG) maps enabled by flexible and stretchable surface EMG (sEMG) electrode arrays are used to evaluate the neck myoelectric activities in this study. Customed flexible and stretchable sEMG electrode arrays with 84 electrodes were utilized to record sEMG in all subjects during neck motion tasks.

Hairy-Skin-Adaptive Viscoelastic Dry Electrodes for Long-Term Electrophysiological Monitoring.

Long-term epidermal electrophysiological (EP) monitoring is crucial for disease diagnosis and human-machine synergy. The human skin is covered with hair that grows at an average rate of 0.3 mm per day.

A Hybrid Deep Learning Approach for Epileptic Seizure Detection in EEG signals.

Early detection and proper treatment of epilepsy is essential and meaningful to those who suffer from this disease. The adoption of deep learning (DL) techniques for automated epileptic seizure detection using electroencephalography (EEG) signals has shown great potential in making the most appropriate and fast medical decisions. However, DL algorithms have high computational complexity and suffer low accuracy with imbalanced medical data in multi seizure-classification task.

Ascertaining the optimal myoelectric signal recording duration for pattern recognition based prostheses control.

Introduction: Electromyogram-based pattern recognition (EMG-PR) has been widely considered an essentially intuitive control method for multifunctional upper limb prostheses. A crucial aspect of the scheme is the EMG signal recording duration (SRD) from which requisite motor tasks are characterized per time, impacting the system's overall performance. For instance, lengthy SRD inevitably introduces fatigue (that alters the muscle contraction patterns of specific limb motions) and may incur high computational costs in building the motion intent decoder, resulting in inadequate prosthetic control and controller delay in practical usage.

[A neonatal intelligent regulation system based on the combination of mild hypothermia mattress and hyperbaric oxygen chamber: introduction to a patent].

Neonatal hypoxic-ischemic encephalopathy (HIE) is a common disease that affects brain function in neonates. At present, mild hypothermia and hyperbaric oxygen therapy are the main methods for the treatment of neonatal HIE; however, they are independent of each other and cannot be combined for synchronous treatment, without monitoring of brain function-related physiological information. In addition, parameter setting of hyperbaric oxygen chamber and mild hypothermia mattress relies on the experience of the medical practitioner, and the parameters remain unchanged throughout the medical process.