In the modern era, advancements in implantable cardiac monitors are revolutionizing the landscape of cardiac healthcare. These sophisticated devices, designed to continuously track heart activity, are ...

IMPLICITY®, a leader in remote patient monitoring and cardiac data management solutions, today unveiled new findings from its EVIDENCE-RM study¹. Leveraging extensive data from the French National ...

PiEEG kit is a Raspberry Pi 5-based bioscience lab in a suitcase suitable for brain-computer interfaces, EMG, EKG, and EOG signal recording ...

This chapter introduces active filters, which use operational amplifiers (op amps) to achieve better performance and flexibility in signal processing.

One of AI’s most immediate impacts is in screening and identifying patients who may have asymptomatic or paroxysmal AF, those ...

In a new Nature Communications study, researchers have developed an in-memory ferroelectric differentiator capable of performing calculations directly in the memory without requiring a separate ...

This study analyzes ECG signal processing for cardiovascular disease diagnosis using AI. LSTM achieved the highest accuracy (95.1%) on a 1,200-record dataset, outperforming CNN (93.5%) and SVM (87.2%) ...

The filter outputs the median value of the window, thereby suppressing outlier values. For applications such as ECG signal processing, where baseline wandering (low-frequency noise) is also a concern, ...

The use of a brief 5-second ECG signal minimizes memory and processing power requirements, enabling rapid data processing and real-time authentication. The data collected specifically for this study ...

This study investigates a fast, DFT-based, one-dimensional Winograd Transform (WT) to extract convolution-based features from 1-D ECG signals ... time feature extraction in medical image and signal ...