The interconnection between hard electronics and soft textiles remains a noteworthy challenge in regard to the mass production of textile-electronic integrated products such as sensorized garments. The current solutions for this challenge usually have problems with size, flexibility, cost, or complexity of assembly. In this paper, we present a solution with a stretchable and conductive carbon nanotube (CNT)-based paste for screen printing on a textile substrate to produce interconnectors between electronic instrumentation and a sensorized garment. The prototype connectors were evaluated via electrocardiogram (ECG) recordings using a sensorized textile with integrated textile electrodes. The ECG recordings obtained using the connectors were evaluated for signal quality and heart rate detection performance in comparison to ECG recordings obtained with standard pre-gelled Ag/AgCl electrodes and direct cable connection to the ECG amplifier. The results suggest that the ECG recordings obtained with the CNT paste connector are of equivalent quality to those recorded using a silver paste connector or a direct cable and are suitable for the purpose of heart rate detection.
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http://dx.doi.org/10.3390/s19204426 | DOI Listing |
J Cardiovasc Med (Hagerstown)
February 2025
Division of Cardiology, Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, Rende (CS).
Brugada syndrome (BrS) is a genetic condition that increases the risk of life-threatening arrhythmias, which can result in sudden cardiac death (SCD). Implantable loop recorders (ILRs) have become a key tool in managing patients with unexplained syncope, and guidelines advise their use in individuals with recurrent, unexplained syncope or palpitations. However, the role of ILRs in inherited arrhythmic conditions like BrS remains a topic of debate.
View Article and Find Full Text PDFResuscitation
September 2024
Department of Anesthesiology & Critical Care, Perelman School of Medicine at the University of Pennsylvania, Children's Hospital of Philadelphia 3401 Civic Center Blvd., Philadelphia, PA 19104, USA.
Aim: Adherence to post-cardiac arrest care (PCAC) recommendations is associated with improved outcomes for adults. We aimed to describe the survival impact of meeting American Heart Association (AHA) PCAC guidelines in children after cardiac arrest.
Methods: We conducted a retrospective study using Get With The Guidelines® Resuscitation's (GWTG®-R) registry to describe the PCAC of patients ≤ 18 years old who suffered an in-hospital or out-of-hospital cardiac arrest (IHCA or OHCA).
J Vis Exp
January 2025
School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine;
Electroacupuncture (EA) is one of the most commonly used methods in acupuncture and has a good effect on pain, depression, sensory movement disorders, and other diseases. The effectiveness of EA is influenced by many factors, such as the accuracy of acupoint selection, the duration and course of EA treatment, and EA parameters. However, it has rarely been discussed whether the positive and negative electrodes of the EA instrument with acupoints at different locations and distances have an effect on the curative effect.
View Article and Find Full Text PDFJ Vet Emerg Crit Care (San Antonio)
January 2025
Center for Interdisciplinary Statistical Education and Research, Washington State University, Pullman, Washington, USA.
Objective: To evaluate the effect of rescuer team size on objective skill measures of basic life support (BLS) and advanced life support (ALS) using high-fidelity canine CPR simulation.
Design: Prospective, experimental study.
Setting: Veterinary clinical simulation center.
J Electrocardiol
January 2025
Dipartimento di Informatica, Università degli Studi di Milano, Milan, Italy. Electronic address:
Background: Detecting subtle patterns of atrial fibrillation (AF) and irregularities in Holter recordings is intricate and unscalable if done manually. Artificial intelligence-based techniques can be beneficial. In fact, with the rapid advancement of AI, deep learning (DL) demonstrated the capability to identify AF from ECGs with significant performance.
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