A Double-Hurdle Quantification Model for Freezing of Gait of Parkinson’s Patients

Research on Quantitative Model for Freezing of Gait in Parkinson’s Patients Background Introduction Parkinson’s Disease (PD) is a common neurodegenerative disease, accompanied by complex motor disorders. In the later stages of Parkinson’s disease, the phenomenon of “Freezing of Gait” (FOG) becomes particularly prominent. FOG refers to a transient p...

An Intersubject Brain-Computer Interface Based on Domain-Adversarial Training of Convolutional Neural Network for Online Attention Decoding

An Intersubject Brain-Computer Interface Based on Domain-Adversarial Training of Convolutional Neural Network for Online Attention Decoding

Cross-Subject Brain-Computer Interface: Real-time Attention Decoding Based on Domain-Adversarial Training with Convolutional Neural Networks Academic Background Attention decoding plays a crucial role in our daily lives and its implementation based on electroencephalogram (EEG) has garnered extensive attention. However, due to significant inter-ind...

Quantification and Diagnosis of Mobility Deficits

Background and Research Motivation Parkinson’s Disease (PD) is a neurodegenerative disorder primarily affecting patients’ motor abilities, leading to tremors, bradykinesia, limb rigidity, and problems with gait and balance. These motor deficits significantly impact patients’ ability to live independently and their quality of life. Statistics predic...

Hybrid Hydrogel-Magnet Actuated Capsule for Automatic Gut Microbiome Sampling

Hybrid Hydrogel-Magnet Actuated Capsule for Automatic Gut Microbiome Sampling

Hybrid Hydrogel-Magnetic Driven Capsule for Automatic Intestinal Microbiome Sampling Academic Background The gut microbiome is composed of a large and diverse community of microorganisms that significantly impact human health, including conditions such as cancer, diabetes, and inflammatory bowel disease (IBD). Current methods for studying the gut m...

T-Wave Peak-to-End Changes Quantified by Time-Warping Predicts Ventricular Fibrillation in a Porcine Myocardial Infarction Model

Prediction of Ventricular Fibrillation in Myocardial Infarction Model in Pigs Based on T-peak-to-T-end Interval Variation Using Time Warping Technique Background Introduction Source of the Paper Sudden Cardiac Death (SCD) is a leading cause of mortality worldwide, with one of its primary pathogenic mechanisms being Ventricular Fibrillation (VF), es...

A Biomimetic Visual Detection Model: Event-Driven LGMDs Implemented with Fractional Spiking Neuron Circuits

A Biomimetic Visual Detection Model: Event-Driven LGMDs Implemented with Fractional Spiking Neuron Circuits

Academic Report: Research on a Biomimetic Visual Detection Model Based on Fractional Spiking Neuron Circuits In the fields of intelligent autonomous driving and unmanned aerial vehicles, quickly and effectively predicting collisions and triggering avoidance behaviors have significant application value. The Lobula Giant Movement Detectors (LGMDs) in...

A Cervical Elastography System Based on Transvaginal Ultrasound Imaging

A Method for Quantifying Cervical Elasticity During Pregnancy Based on Transvaginal Ultrasound and Pressure Measurement Background and Motivation Preterm birth (delivery before 37 weeks of gestation) is a major cause of neonatal morbidity and mortality. Due to the high risks associated with preterm birth, many pregnant women with preterm symptoms n...

Field-of-View IoU for Object Detection in 360° Images

Object Detection in 360° Images using FOV IoU 360° cameras have gained widespread use in various fields such as virtual reality, autonomous driving, and security monitoring in recent years. With the increase in 360° image data, the demand for 360° image recognition tasks, especially object detection, is continuously growing. Due to the shortcomings...

dvmark: a deep multiscale framework for video watermarking

dvmark: a deep multiscale framework for video watermarking

DVMark: A Multi-Scale Deep Learning Framework for Video Watermarking Video watermarking technology achieves data hiding by embedding information into the cover video. The DVMark model proposed in this paper is a multi-scale video watermarking solution based on deep learning that boasts high robustness and practicality, capable of resisting various ...

Stacked Deconvolutional Network for Semantic Segmentation

Stacked Deconvolutional Network for Semantic Segmentation

Stacked Deconvolutional Network for Semantic Segmentation Introduction Semantic segmentation is a critical task in the field of computer vision, aiming to classify each pixel in an image and predict its category. However, existing Fully Convolutional Networks (FCNs) have limitations in handling spatial resolution, often leading to problems such as ...