Related papers: An Innovative Wireless Cardiac Rhythm Management (…

Wearable electrocardiograph (ECG) recording and processing systems have been developed to detect cardiac arrhythmia to help prevent heart attacks. Conventional wearable systems, however, suffer from high energy consumption at both circuit…

Integrated sensing and communications (ISAC) as one of the key technologies is capable of supporting high-speed communication and high-precision sensing for the upcoming 6G. This paper studies a waveform strategy by designing the orthogonal…

This study proposes a radar-centric integrated sensing and communication (ISAC) system utilizing a two-layer modulation scheme for vehicular networks. Frequency-modulated continuous wave (FMCW) chirps are jointly modulated via phase…

Since cadiovascular disease (CVD) posts a heavy threat to people's health, long-term electrocardiogram (ECG) monitoring is of great value for the improvement of treatment. To realize remote long-term ECG monitoring, a low-power wireless…

Cost-effective wireless electrocardiograms (ECGs) enable long-term and scalable monitoring of cardiac patients in their home and work environments. Because they offer greater freedom of movement, they are also suitable for investigating the…

The recent developments in wearable devices and the Internet of Medical Things (IoMT) allow real-time monitoring and recording of electrocardiogram (ECG) signals. However, continuous monitoring of ECG signals is challenging in low-power…

Monitoring respiratory health with the use of channel state information (CSI) has shown promising results. Many existing methods focus on monitoring only the respiratory rate, while others focus on monitoring the motion of the chest as a…

Integrating information from multiple data sources can enable more precise, timely, and generalizable decisions. However, it is challenging to make valid causal inferences using observational data from multiple data sources. For example, in…

In this demo paper, we design and prototype RhythmEdge, a low-cost, deep-learning-based contact-less system for regular HR monitoring applications. RhythmEdge benefits over existing approaches by facilitating contact-less nature,…

Cardiovascular diseases remain the leading cause of morbidity and mortality, particularly in aging populations, with rising rates of heart-related incidents in middle-aged and even younger individuals. Currently available electrocardiogram…

Electrocardiogram (ECG), a non-invasive and affordable tool for cardiac monitoring, is highly sensitive in detecting acute heart attacks. However, due to the lengthy nature of ECG recordings, numerous machine learning methods have been…

Electrocardiogram (ECG) is the electrical measurement of cardiac activity, whereas Photoplethysmogram (PPG) is the optical measurement of volumetric changes in blood circulation. While both signals are used for heart rate monitoring, from a…

Electrocardiogram is a useful diagnostic signal that can detect cardiac abnormalities by measuring the electrical activity generated by the heart. Due to its rapid, non-invasive, and richly informative characteristics, ECG has many emerging…

Electrocardiogram (ECG)-based models have achieved strong performance in diagnostic tasks, yet they remain limited in modeling how cardiac dynamics evolve under external interventions. In particular, existing approaches focus primarily on…

Realizing interactive whole-body control for multi-humanoid systems is critical for unlocking complex collaborative capabilities in shared environments. Although recent advancements have significantly enhanced the agility of individual…

This research presents a multi-robot system for inpatient care, designed using swarm intelligence principles and incorporating wearable health sensors, RF-based communication, and AI-driven decision support. Within a simulated hospital…

This paper introduces an integrated sensing, computing, and semantic communication (ISCSC) framework tailored for smart healthcare systems. The framework is evaluated in the context of smart healthcare, optimising the transmit beamforming…

The classification of the electrocardiogram (ECG) signal has a vital impact on identifying heart-related diseases. This can ensure the premature finding of heart disease and the proper selection of the patient's customized treatment.…

In the paper a ballistocardiographic sensor for remote monitoring of activity and vital parameters is presented. The sensor is mainly intended for use in monitoring systems supporting care of older people. It allows to detect occupancy of a…

Cardiopulmonary resuscitation (CPR) is one of the most critical emergency interventions for sudden cardiac arrest. In this paper, a robust sinusoidal model-fitting method based on a Evolution Strategy inspired algorithm for CPR quality…