Over the past few years, the emergence of electrochemical wearable sensors has attracted
considerable attention because of their promising application in point‐of‐care testing due to …

In this paper, we propose a lightweight neural network for real-time electrocardiogram (ECG)
anomaly detection and system level power reduction of wearable Internet of Things (IoT) …

Electrocardiogram (ECG) analysis is widely used in the diagnosis of cardiovascular
diseases. This article proposes an explainable rule-mining strategy for prioritizing abnormal …

The accurate detection of heartbeats is of paramount importance in the current healthcare
scenario as they act as an indicator for various underlying cardiac conditions and provides …

Wearable and Internet of Things devices (IoT) are becoming ubiquitous in health
applications, such as movement disorders, rehabilitation, and activity monitoring. Wearable …

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 …

The advent of low-cost wearable Internet of Things (IoT) sensors has made it possible to
continuously acquire physiological signals such as electrocardiogram (ECG) for long …

Wearable Artificial Intelligence-of-Things (AIoT) devices exhibit the need to be resource and
energy-efficient. In this paper, we introduced a quantized multilayer perceptron (qMLP) for …

A wearable electrocardiogram (ECG) device is an effective tool for managing cardiovascular
diseases. This paper presents a low power clinician-like cardiac arrhythmia watchdog …

This paper presents a very large–scale integration chip for a novel discrete wavelet
transform (DWT) based QRS complex detection algorithm. In many aspects of …