This paper presents a neuromorphic processing system with a spike-driven spiking neural
network (SNN) processor design for always-on wearable electrocardiogram (ECG) …

The paper presents a novel method for the compressed acquisition of electrocardiographic
(ECG) signals. The proposed method is intended to be applied to Internet-of-Medical-Things …

In this paper, a new methodology for choosing design parameters of level-crossing analog-
to-digital converters (LC-ADCs) is presented that improves sampling accuracy and reduces …

This paper presents a compression study of electrocardiogram (ECG) signals for e-Health
cardiac online diagnostic systems. The study uses 75 real electrocardiogram records …

A novel low-power sensor wireless system for continuous and simultaneous measurement
of the electrocardiogram (ECG) and the impedance plethysmogram (IPG) from a single limb …

A fixed-window level-crossing analog-to-digital converter (LC-ADC) with only one
continuous-time comparator is proposed for the biomedical electronics. Compared with the …

Electrocardiogram (ECG) data's high dimensionality challenges real-time arrhythmia
classification. Our approach employs functional approximation to condense ECG recordings …

The long-term monitoring of cardiovascular signs requires a wearable and connected
electrocardiogram (ECG) healthcare device. It increases user's comfort and diagnosis …

This paper presents an energy‐efficient single‐transistor leaky integrate‐and‐fire neuron,
based on Suspended Gate‐FET (SG‐FET), for signal classification and neuromorphic …

This paper presents a new self-clocked time-to-digital conversion method based on a binary
successive approximation (SA) algorithm. Its novelty consists in combining fully clockless …