Recent advances in remote patient monitoring (RPM) systems can recognize various human
activities to measure vital signs, including subtle motions from superficial vessels. There is a …

Cyborg insects are a major part of the vision of future interactions of the living world and
technology, including but not limited to the Internet of Living Things (IoLT). They are crawling …

Computing paradigms have evolved significantly in recent decades, moving from large room-
sized resources (processors and memory) to incredibly small computing nodes. Recently …

The Internet of Things (IoT) will disrupt medicine the most. Healthcare uses edge computing,
deep learning, IoT, and machine learning for real-time analytics, monitoring, and data …

In today's advanced applications, such as memory interfaces, feature-based detection, and
sensory games, human-computer interaction (HCI) plays a pivotal role. A medical decision …

Federated Learning (FL) is currently one of the most popular technologies in the field of
Artificial Intelligence (AI) due to its collaborative learning and ability to preserve client …

As per WHO report, 86.6% of deaths in China is due to chronic disease. Also, on average,
12 million people dies every year due to heart attack. On another side, we have a …

IoT devices are sorely underutilized in the medical field, especially within machine learning
for medicine, yet they offer unrivaled benefits. IoT devices are low cost, energy efficient …

K-means Clustering is the most well-known partitioning algorithm among all clustering, by
which we can partition the data objects very easily in to more than one clusters. However, for …

Machine learning, particularly using neural networks, is now widely adopted in practice even
with the IoT paradigm; however, training neural networks at the edge, on IoT devices …