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Xi Long

Associate Professor

Eindhoven University of Technology

Netherlands

Research Interests

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Professors in Netherlands Professors in Medical Imaging Medical Imaging professors in Netherlands

About

Dr. Xi Long is an Associate Professor at Eindhoven University of Technology in the Netherlands. His research primarily focuses on biomedical signal processing, with recent work emphasizing detection methods for conditions such as apnea in preterm infants and sleep disorders. He also explores innovative monitoring techniques utilizing deep learning and sensor technology to enhance health outcomes. His contributions to the field include applications in atrial fibrillation detection and predicting preterm birth through medical record analysis.

Articles (44)

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Collaborators (27)

Hyun Jae Baek

Soonchunhyang University

SOUTH KOREA

Xi Long

Research Interests

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About

Articles (44)

Modeling the post-extrasystolic potentiation to determine heart failure

Multidimensional decomposition framework for electrocardiographic interference, noise and artifacts removal from diaphragmatic electromyography

Comparing diaphragmatic EMG and thoracic respiratory inductance plethysmography to characterize respiratory effort in obstructive sleep apnea

Comparative Analysis of Electrode Configurations for Estimating Respiratory Effort From Diaphragmatic Electromyography

Effect of a grace period on false alarm rates of smartwatch-based out-of-hospital cardiac arrest detection systems: a pilot study

External Validation Complexities: A Comparative Study of Late-Onset Sepsis Prediction Models Across Multiple Clinical Environments

Pulse‐based photoplethysmography quality assessment improves wearable seizure detection performance

Characterizing vascular tone in nocturnal major motor seizures using wearable photoplethysmography

Reduction of motion artifacts from photoplethysmography signals using learned convolutional sparse coding

Improving central apnea detection in preterm infants: Neural network strategies and clinical impact

A Two-Dimensional Position and Motion Monitoring System for Preterm Infants Using a Fiber-Optic Pressure-Sensitive Mattress

Biomedical Signal Processing and Health Monitoring Based on Sensors

Estimation of Respiratory Effort Through Diaphragmatic Electromyography Features

SSC-SleepNet

Longitudinal fecal microbiota and volatile metabolomics preceding necrotizing enterocolitis in preterm infants

Harnessing multiscale time–frequency ballistocardiography feature fusion for bedside atrial fibrillation detection

Detection of Nocturnal Epileptic Seizures Using a Wearable Armband: A Deep Learning Approach Combining Accelerometry and Photoplethysmography Signals

Multi-modal multi-task deep neural networks for sleep disordered breathing assessment using cardiac and audio signals

Normalization of the Photoplethysmographic Signal using the Post-extrasystolic Potentiation

Breathing Rate Detection in Preterm Infants Using a Fiber Optic Pressure-Sensitive Mattress

Improving Machine Learning Models of Late-onset Sepsis Prediction Using Optimized Control Group Selection

Cross-Modal Graph Learning for Perivascular Spaces Segmentation

Movement artifacts reduction from PPG signals using learned convolutional sparse coding

Noncontact respiration monitoring techniques in young children: A scoping review

Continuous prediction and clinical alarm management of late-onset sepsis in preterm infants using vital signs from a patient monitor

BSANet: Boundary-aware and scale-aggregation networks for CMR image segmentation

A pretrain-finetune approach for improving model generalizability in outcome prediction of acute respiratory distress syndrome patients

Characterising the motion and cardiorespiratory interaction of preterm infants can improve the classification of their sleep state

Robust arterial compliance estimation with Katz's fractal dimension of photoplethysmography

A multi-task learning model using RR intervals and respiratory effort to assess sleep disordered breathing

Early prediction of gestational diabetes mellitus using maternal demographic and clinical risk factors

A customised down-sampling machine learning approach for sepsis prediction

Development and Validation of an Interpretable Conformal Predictor to Predict Sepsis Mortality Risk: Retrospective Cohort Study

Predicting preterm birth using electronic medical records from multiple prenatal visits

Ultra-Wideband Radar for Simultaneous and Unobtrusive Monitoring of Respiratory and Heart Rates in Early Childhood: A Deep Transfer Learning Approach

The Use of Respiratory Effort Improves an ECG-Based Deep Learning Algorithm to Assess Sleep-Disordered Breathing

A Continuous Late-Onset Sepsis Prediction Algorithm for Preterm Infants Using Multi-Channel Physiological Signals From a Patient Monitor

DeepLOS: Deep learning for late-onset sepsis prediction in preterm infants using heart rate variability

A behavioral approach to annotating sleep in infants: Building on the classic framework

A Two-Layer Ensemble Method for Detecting Epileptic Seizures Using a Self-Annotation Bracelet With Motor Sensors

Epileptic Seizure Detection by Cascading Isolation Forest-Based Anomaly Screening and EasyEnsemble

Convolutional Neural Networks for Audio-Based Continuous Infant Cry Monitoring at Home

A deep transfer learning approach for wearable sleep stage classification with photoplethysmography

It is All in the Wrist: Wearable Sleep Staging in a Clinical Population versus Reference Polysomnography

Collaborators (27)

Hyun Jae Baek

Marcel Breeuwer

Sebastiaan Overeem

Ronald Aarts

Meicheng Yang

Jean-Paul Linnartz

Henrie van den Boom

Mengzhu XU

R. Vullings

Peter Andriessen

Gerben Hup

Johannes van Dijk

Lukas Dekker

Gabriela Maria Grońska

Zheng Peng

Massimo Mischi

Heenam Yoon

Roel Josef Hendrikus Montree

Rong-Hao Liang

Gabriele Varisco

Jeroen Dudink

Roland D Thijs

Qinhao Wu

Sang Ho Choi

Myrthe A. Plaisier

M. Beatrijs van der Hout-van der Jagt

Haipeng Liu

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