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High-resolution manometry (HRM) is the primary procedure used to diagnose esophageal motility disorders. Its interpretation and classification includes an initial evaluation of swallow-level outcomes and then derivation of a study-level…

Diagnosing esophageal motility disorders pose significant challenges due to the complexity of high-resolution impedance manometry (HRIM) data and variability in clinical interpretation. This work explores the feasibility of a multimodal…

Machine Learning · Computer Science 2026-05-14 Alexander Geiger , Lars Wagner , Daniel Rueckert , Alois Knoll , Dirk Wilhelm , Alissa Jell

High-resolution manometry (HRM) is the gold standard in diagnosing esophageal motility disorders. As HRM is typically conducted under short-term laboratory settings, intermittently occurring disorders are likely to be missed. Therefore,…

Computer Vision and Pattern Recognition · Computer Science 2024-05-03 Alexander Geiger , Lars Wagner , Daniel Rueckert , Dirk Wilhelm , Alissa Jell

Endoscopy is a crucial tool for diagnosing the gastrointestinal tract, but its effectiveness is often limited by a narrow field of view and the dynamic nature of the internal environment, especially in the esophagus, where complex and…

Computer Vision and Pattern Recognition · Computer Science 2024-10-03 Muyang Li , Juming Xiong , Ruining Deng , Tianyuan Yao , Regina N Tyree , Girish Hiremath , Yuankai Huo

Hand gesture recognition using multichannel surface electromyography (sEMG) is challenging due to unstable predictions and inefficient time-varying feature enhancement. To overcome the lack of signal based time-varying feature problems, we…

Computer Vision and Pattern Recognition · Computer Science 2025-04-07 Jungpil Shin , Abu Saleh Musa Miah , Sota Konnai , Shu Hoshitaka , Pankoo Kim

The pathogenesis of esophageal disorders is related to the esophageal wall mechanics. Therefore, to understand the underlying fundamental mechanisms behind various esophageal disorders, it is crucial to map the esophageal wall…

Gesture recognition based on surface electromyographic signal (sEMG) is one of the most used methods. The traditional manual feature extraction can only extract some low-level signal features, this causes poor classifier performance and low…

Computer Vision and Pattern Recognition · Computer Science 2024-10-25 Mingjin Zhang , Jiahao Wang , Jianming Wang , Qi Wang

In recent years, many innovative solutions for recording and viewing sounds from a stethoscope have become available. However, to fully utilize such devices, there is a need for an automated approach for detecting abnormal lung sounds,…

The Support Vector Machine (SVM) is one of the most widely used classification methods. In this paper, we consider the soft-margin SVM used on data points with independent features, where the sample size $n$ and the feature dimension $p$…

Machine Learning · Statistics 2019-08-02 Haoyang Liu

The multichannel electrode array used for electromyogram (EMG) pattern recognition provides good performance, but it has a high cost, is computationally expensive, and is inconvenient to wear. Therefore, researchers try to use as few…

Signal Processing · Electrical Eng. & Systems 2022-05-24 Md. Johirul Islam , Shamim Ahmad , Fahmida Haque , Mamun Bin Ibne Reaz , Mohammad A. S. Bhuiyan , Md. Rezaul Islam

Tests for Esophageal cancer can be expensive, uncomfortable and can have side effects. For many patients, we can predict non-existence of disease with 100% certainty, just using demographics, lifestyle, and medical history information. Our…

Machine Learning · Computer Science 2016-10-07 Asis Roy , Sourangshu Bhattacharya , Kalyan Guin

Objective: Bleeding from gastroesophageal varices (GEV) is a medical emergency associated with high mortality. We aim to construct an artificial intelligence-based model of two-dimensional shear wave elastography (2D-SWE) of the liver and…

Surface electromyographic (sEMG) signal serve as a signal source commonly used for lower limb movement recognition, reflecting the intent of human movement. However, it has been a challenge to improve the movements recognition rate while…

Signal Processing · Electrical Eng. & Systems 2024-04-18 Yongkai Ma , Shili Liang , Zekun Chen

Statistical models of Surface electromyography (sEMG) signals have several applications such as better understanding of sEMG signal generation, improved pattern recognition based control of wearable exoskeletons and prostheses, improving…

Signal Processing · Electrical Eng. & Systems 2023-01-16 Durgesh Kusuru , Anish C. Turlapaty , Mainak Thakur

Fluoroscopy is a radiographic procedure for evaluating esophageal disorders such as achalasia, dysphasia and gastroesophageal reflux disease (GERD). It performs dynamic imaging of the swallowing process and provides anatomical detail and a…

Medical image analysis has become a topic under the spotlight in recent years. There is a significant progress in medical image research concerning the usage of machine learning. However, there are still numerous questions and problems…

Image and Video Processing · Electrical Eng. & Systems 2018-05-16 Taha J. Alhindi , Shivam Kalra , Ka Hin Ng , Anika Afrin , Hamid R. Tizhoosh

Seismocardiography (SCG) is a non-invasive method that can be used for cardiac activity monitoring. This paper presents a new electrocardiogram (ECG) independent approach for estimating heart rate (HR) during low and high lung volume (LLV…

Signal Processing · Electrical Eng. & Systems 2019-02-04 Amirtaha Taebi , Andrew J Bomar , Richard H Sandler , Hansen A Mansy

Dynamic magnetic resonance imaging (MRI) is a popular medical imaging technique to generate image sequences of the flow of a contrast material inside tissues and organs. However, its application to imaging bolus movement through the…

Despite progress in the rapidly developing field of geometric deep learning, performing statistical analysis on geometric data--where each observation is a shape such as a curve, graph, or surface--remains challenging due to the…

Computer Vision and Pattern Recognition · Computer Science 2025-08-12 Emmanuel Hartman , Nicolas Charon

In this paper we propose the use of quantum genetic algorithm to optimize the support vector machine (SVM) for human action recognition. The Microsoft Kinect sensor can be used for skeleton tracking, which provides the joints' position…

Machine Learning · Statistics 2017-12-18 Yafeng Liu , Shimin Feng , Zhikai Zhao , Enjie Ding
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