Rui Luo,Hongzhang Huang,Qinfang Miao et al.
Rui Luo et al.
Objective: To develop a real-time method for designing gradient waveforms for arbitrary k-space trajectories that are time-optimal and hardware-compliant. ...
MSHANet: A Multiscale Hybrid Attention Network for Motor Imagery EEG Decoding [0.03%]
用于运动想象EEG解码的多尺度混合注意网络蒋孟翰
Yanlong Zhao,Dianguo Cao,Haoyang Yu et al.
Yanlong Zhao et al.
Brain-computer interface (BCI) technology has significant applications in neuro rehabilitation and motor function restoration, especially for patients with stroke or spinal cord injury. Motor imagery electroencephalog-raphy (MI-EEG) is wide...
ECG-Adapt: A Novel Framework for Robust Electrocardiogram Classification Across Diverse Populations and Recording Conditions [0.03%]
ECG-Adapt：一种鲁棒的心电图分类框架，在不同人群和记录条件下均适用
Ahmadreza Argha,Hamid Alinejad-Rokny,Farshid Hajati et al.
Ahmadreza Argha et al.
The electrocardiogram (ECG) is a vital diagnostic tool used to monitor and diagnose a wide range of cardiac conditions. However, ECG signals can exhibit significant variability across different patient populations, recording devices, and en...
Multimodal Spiking Neural Network With Generalized Distributive Law for Biosignal and Sensory Fusion [0.03%]
基于广义分配律的用于生物信号和感官融合的多模态脉冲神经网络
Zenan Huang,Bingrui Guo,Hailing Xu et al.
Zenan Huang et al.
Multimodal signal fusion is a cornerstone of biomedical engineering and intelligent sensing, enabling holistic analysis of heterogeneous sources such as electroencephalography (EEG), peripheral signals, speech, and imaging data. However, in...
Muscle Synergy-Guided Reinforcement Learning for Embodied Musculoskeletal Motion Skill Learning [0.03%]
基于肌协同的强化学习在具身骨骼肌肉运动技能学习中的应用
Lijun Han,Long Cheng,Muyuan Ma et al.
Lijun Han et al.
Background: Acquiring human- like motor skills in embodied musculoskeletal models is challenging due to the high dimensionality and redundancy of muscle actuators. ...
Fusing Tabular Features and Deep Learning for Fetal Heart Rate Analysis: A Clinically Interpretable Model for Fetal Compromise Detection [0.03%]
融合表格特征和深度学习的胎儿心率分析模型：一种临床可解释的胎儿窘迫检测模型
Lochana Mendis,Debjyoti Karmakar,Marimuthu Palaniswami et al.
Lochana Mendis et al.
Objective: Cardiotocography (CTG) is commonly used to monitor fetal heart rate (FHR) and assess fetal well-being during labor. However, its effectiveness in reducing adverse outcomes remains limited due to low sensitivity...
SW-VEI-Net: A Physics-Informed Deep Neural Network for Shear Wave Viscoelasticity Imaging [0.03%]
基于物理的深度神经网络在剪切波粘弹性成像中的应用
Haoming Lin,Zhongjun Ma,Yunxiang Wang et al.
Haoming Lin et al.
Quantitative viscoelasticity imaging via shear wave elastography (SWE) remains challenging due to complex wave physics and limitations of conventional reconstruction methods. To address this, we present SW-VEI-Net, a physics-informed neural...
Dynamic Cardiac Event Detection from Single-Arm Wearable ECG via a Contrastive Multitask Framework [0.03%]
基于对比多任务框架的单导联可穿戴心电监护设备心脏事件检测方法
Xianbin Zhang,Haoke Zhang,Gui-Bin Bian et al.
Xianbin Zhang et al.
Objective: Upper-limb electrocardiogram (ECG) acquired from a single-arm wearable device offers a practical approach for dynamic cardiac monitoring. This study addresses whether single-channel Arm-ECG, characterized by hi...
A Dual-Energy CBCT With Reduced Scatter and Cone Beam Artifacts Using an X-Ray Source Array and Interlaced Spectral Filters [0.03%]
一种利用X射线源阵列和交错光谱滤波器降低散射及锥形束伪影的双能量CBCT
Yuanming Hu,Boyuan Li,Shuang Xu et al.
Yuanming Hu et al.
Objective: To design a dual-energy cone beam computed tomography (DE-CBCT) scanner with reduced scatter and cone beam artifacts. Methods: ...
Haoyu Dong,Hanxue Gu,Yaqian Chen et al.
Haoyu Dong et al.
Segment Anything Model (SAM) has gained significant attention because of its ability to segment a variety of objects in images upon providing a prompt. Recently developed SAM 2 has extended this ability to video segmentation, and by substit...