Accurate cardiac signal monitoring feasible for long-term monitoring is important for a practical, cost-effective health monitoring system. In this study, we propose a wearable healthcare system based on conductive fabric-based electrodes allowing monitoring of electrocardiogram (ECG) waveforms and demonstrated the potential for arrhythmia detection using the system. The measurement system uses conductive fabric-based electrodes arranged in a modified bipolar electrode configuration on the chest area of the patient. An adaptive impulse correlation filter (AICF) algorithm and a band pass filter to enable accurate R-peak detection in noisy environments.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1109/EMBC.2013.6611293 | DOI Listing |
Comput Biol Med
January 2025
Department of Computer Science, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran. Electronic address:
Tiny machine learning (TinyML) and edge intelligence have emerged as pivotal paradigms for enabling machine learning on resource-constrained devices situated at the extreme edge of networks. In this paper, we explore the transformative potential of TinyML in facilitating pervasive, low-power cardiovascular monitoring and real-time analytics for patients with cardiac anomalies, leveraging wearable devices as the primary interface. To begin with, we provide an overview of TinyML software and hardware enablers, accompanied by an examination of networking solutions such as Low-power Wide area network (LPWAN) that facilitate the seamless deployment of TinyML frameworks.
View Article and Find Full Text PDFExpert Rev Med Devices
January 2025
Division of Gastroenterology, P.D Hinduja Hospital, Mumbai, India.
Introduction: Wearables are electronic devices worn on the body to collect health data. These devices, like smartwatches and patches, use sensors to gather information on various health parameters. This review highlights current use and the potential benefit of wearable technology in patients with inflammatory bowel disease (IBD).
View Article and Find Full Text PDFACS Appl Mater Interfaces
January 2025
Textile and Clothing College, Qingdao University, Qingdao 266071, China.
Fiber-based strain sensors, as wearable integrated devices, have shown substantial promise in health monitoring. However, current sensors suffer from limited tunability in sensing performance, constraining their adaptability to diverse human motions. Drawing inspiration from the structure of the spiranthes sinensis, this study introduces a unique textile wrapping technique to coil flexible silver (Ag) yarn around the surface of multifilament elastic polyurethane (PU), thereby constructing a helical structure fiber-based strain sensor.
View Article and Find Full Text PDFJ Clin Med
December 2024
Department of Adult Critical Care, Guy's and St Thomas' NHS Foundation Trust, King's Health Partners, London SE1 9RT, UK.
Extracorporeal carbon dioxide removal (ECCOR) is an emerging technique designed to reduce carbon dioxide (CO) levels in venous blood while enabling lung-protective ventilation or alleviating the work of breathing. Unlike high-flow extracorporeal membrane oxygenation (ECMO), ECCOR operates at lower blood flows (0.4-1.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Instruction and Leadership, Duquesne University, Pittsburgh, PA 15282, USA.
This article examines how sensor technologies (such as environmental sensors, biometric sensors, and IoT devices) intersect with conversational AI models like ChatGPT 4.0. In particular, this article explores how data from different sensors in real time can improve AI models' comprehension of surroundings, user contexts, and physical conditions.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!