We have developed a system that could potentially be used to identify the site of origin of ventricular tachycardia (VT) and to guide a catheter to that site to deliver radio-frequency ablation therapy. This system employs the Inverse Solution Guidance Algorithm based upon Single Equivalent Moving Dipole (SEMD) localization method. The system was evaluated in in vivo swine experiments. Arrays consisting of 9 or 16 bipolar epicardial electrodes and an additional mid-myocardial pacing lead were sutured to each ventricle. Focal tachycardia was simulated by applying pacing pulses to each epicardial electrode at multiple pacing rates during breath hold at the end-expiration phase. Surface potentials were recorded from 64 surface electrodes and then analyzed using the SEMD method to localize the position of the pacing electrodes. We found a close correlation between the locations of the pacing electrodes as measured in computational and real spaces. The reproducibility error of the SEMD estimation of electrode location was 0.21 ± 0.07 cm. The vectors between every pair of bipolar electrodes were computed in computational and real spaces. At 120 bpm, the lengths of the vectors in the computational and real space had a 95% correlation. Computational space vectors were used in catheter guidance simulations which showed that this method could reduce the distance between the real space locations of the emulated catheter tip and the emulated arrhythmia origin site by approximately 72% with each movement. We have demonstrated the feasibility of using our system to guide a catheter to the site of the emulated VT origin.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s10840-019-00605-z | DOI Listing |
Nutrients
January 2025
Department of Computer Engineering, Inje University, Gimhae 50834, Republic of Korea.
Background: Food image recognition, a crucial step in computational gastronomy, has diverse applications across nutritional platforms. Convolutional neural networks (CNNs) are widely used for this task due to their ability to capture hierarchical features. However, they struggle with long-range dependencies and global feature extraction, which are vital in distinguishing visually similar foods or images where the context of the whole dish is crucial, thus necessitating transformer architecture.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Biomedical and Robotics Engineering, Incheon National University, Incheon 22012, Republic of Korea.
With the rise of modern healthcare monitoring, heart rate (HR) estimation using remote photoplethysmography (rPPG) has gained attention for its non-contact, continuous tracking capabilities. However, most HR estimation methods rely on stable, fixed sampling intervals, while practical image capture often involves irregular frame rates and missing data, leading to inaccuracies in HR measurements. This study addresses these issues by introducing low-complexity timing correction methods, including linear, cubic, and filter interpolation, to improve HR estimation from rPPG signals under conditions of irregular sampling and data loss.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Airworthiness Division, Air Force Institute of Technology, 01-494 Warsaw, Poland.
The range of sensor technologies for structural health monitoring (SHM) systems is expanding as the need for ongoing structural monitoring increases. In such a case, damage to the monitored structure elements is detected using an integrated network of sensors operating in real-time or periodically in frequent time stamps. This paper briefly introduces a new type of sensor, called a Customized Crack Propagation Sensor (CCPS), which is an alternative for crack gauges, but with enhanced functional features and customizability.
View Article and Find Full Text PDFSensors (Basel)
January 2025
College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, China.
According to the physical characteristics of cotton and the work characteristics of cotton pickers in the field, during the picking process, there is a risk of cotton combustion. The cotton picker working environment is complex, cotton ignition can be hidden, and fire is difficult to detect. Therefore, in this study, we designed an improved algorithm for multi-sensor data fusion; built a cotton picker fire detection system by using infrared temperature sensors, CO sensors, and the upper computer; and proposed a BP neural network model based on improved mutation operator hybrid gray wolf optimizer and particle swarm optimization (MGWO-PSO) algorithm based on the BP neural network model.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Information Science and Technology, Southwest Jiaotong University, Chengdu 611756, China.
Real-time and accurate traffic forecasting aids in traffic planning and design and helps to alleviate congestion. Addressing the negative impacts of partial data loss in traffic forecasting, and the challenge of simultaneously capturing short-term fluctuations and long-term trends, this paper presents a traffic forecasting model, D-MGDCN-CLSTM, based on Multi-Graph Gated Dilated Convolution and Conv-LSTM. The model uses the DTWN algorithm to fill in missing data.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!