Cardiovascular diseases currently pose the highest threat to human health around the
world. Proper investigation of the abnormalities in heart sounds is known to provide vital …

Technological advances in sensors and communications have enabled discrete integration
into everyday objects, both in the home and about the person. Information gathered by …

Activity recognition plays an essential role in bridging the gap between the low-level sensor
data and the high-level applications in ambient-assisted living systems. With the aim to …

This study provides a comparative assessment on the different techniques of classifying
human activities performed while wearing inertial and magnetic sensor units on the chest …

In this paper we present a methodology for recognizing three fundamental movements of the
human forearm (extension, flexion and rotation) using pattern recognition applied to the data …

Abstract Human Activity Recognition (HAR) makes it possible to drive applications directly
from embedded and wearable sensors. Machine learning, and especially deep learning …

This paper proposes the use of posterior-adapted class-based weighted decision fusion to
effectively combine multiple accelerometer data for improving physical activity recognition …

Rapid advancement in computing technology brings computers and humans to be
seamlessly integrated in future. The emergence of smartphone has driven computing era …

Context-awareness is an interesting topic in mobile navigation scenarios where the context
of the application is highly dynamic. Using context-aware computing, navigation services …

Activity recognition in smart homes plays an important role in healthcare by maintaining the
well being of elderly and patients through remote monitoring and assisted technologies. In …