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Continuous monitoring of heart activity, particularly electrocardiogram (ECG) waveforms and heart rate variability (HRV), is essential for the early detection of cardiac diseases. However, conventional wearable ECG systems typically require direct skin contact and external software for signal acquisition and analysis, limiting user comfort and long-term usability. This study presents an unobtrusive contactless bed-embedded system that enables wearable-free, comfortable, and precise monitoring of ECG and HRV without the need for the subject to undress. Flexible active electrodes achieve high signal acquisition performance and strong noise immunity by employing double active shielding for noise reduction of 64 dB. The analog front-end has an input-referred noise of 0.49 μV within the QRS bandwidth. Further noise reduction of 27.5 dB is obtained by a non-contact driven-right-leg. Real-time signal denoising, R-peak detection, and HRV calculation are performed on the field-programmable gate array for on-hardware processing, running a stationary wavelet transform and adaptive thresholding. The system demonstrates over 70% R-peak detection precision for users wearing even thick clothing during a 5-minute measurement. This system enables R-peak detection when the subject makes slight movements.
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http://dx.doi.org/10.1016/j.bios.2025.117838 | DOI Listing |
Sensors (Basel)
August 2025
Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio 22, 80125 Naples, Italy.
Background: Respiratory rate (RR) is a key vital sign and one of the most sensitive indicators of physiological conditions, playing a crucial role in the early identification of clinical deterioration. The monitoring of RR using electrocardiography (ECG) and photoplethysmography (PPG) aims to overcome limitations of traditional methods in clinical settings.
Methods: The proposed approach extracts RR from ECG and PPG signals using different morphological and temporal features from publicly available datasets (iAMwell and Capnobase).
IEEE J Biomed Health Inform
August 2025
Direct fetal electrocardiogram (FECG) plays a crucial role in assessing fetal health and monitoring pregnancy conditions. Extracting high-quality FECG signals from maternal abdominal electrocardiogram (AECG) recordings remains a significant challenge due to the low amplitude of the FECG, its overlap with the maternal electrocardiogram (MECG), and the potential exposure to impulsive noise in the real world. Adaptive filtering (AF) is an essential method for FECG extraction, however, its performance tends to degrade in the presence of impulsive noise, such as instrument interference.
View Article and Find Full Text PDFSensors (Basel)
July 2025
Department of Cardiovascular Medicine, Institute of Science Tokyo, Tokyo 113-8519, Japan.
Magnetocardiography (MCG) provides a non-invasive, contactless technique for evaluating the magnetic fields generated by cardiac electrical activity, offering unique spatial insights into cardiac electrophysiology. However, conventional MCG systems depend on superconducting quantum interference devices that require cryogenic cooling and magnetic shielded environments, posing considerable impediments to widespread clinical adoption. In this study, we present a novel MCG system utilizing a high-sensitivity, wide-dynamic-range magnetoresistive sensor array operating at room temperature.
View Article and Find Full Text PDFBiosens Bioelectron
December 2025
Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea; Program of Brain and Cognitive Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea. Electronic address: kimch
Continuous monitoring of heart activity, particularly electrocardiogram (ECG) waveforms and heart rate variability (HRV), is essential for the early detection of cardiac diseases. However, conventional wearable ECG systems typically require direct skin contact and external software for signal acquisition and analysis, limiting user comfort and long-term usability. This study presents an unobtrusive contactless bed-embedded system that enables wearable-free, comfortable, and precise monitoring of ECG and HRV without the need for the subject to undress.
View Article and Find Full Text PDFComput Biol Med
September 2025
Department of Computer Science and Engineering, University of West Bohemia in Pilsen, Pilsen, 30100, Czech Republic. Electronic address:
Background: Sleep apnea (SA), a prevalent sleep-related breathing disorder, disrupts normal respiratory patterns during sleep. This disruption can have a cascading effect on the body, potentially leading to complications in various organs, including the heart, brain, and lungs. Due to the potential for these complications, early and accurate detection of SA is critical.
View Article and Find Full Text PDF