Wearable devices monitoring food intake through passive sensing is slowly emerging to
complement self-reporting of users' caloric intake and eating behaviors. Though the ultimate …

The threat of obesity, diabetes, anorexia, and bulimia in our society today has motivated
extensive research on dietary monitoring. Standard self-report methods such as 24-h recall …

Document-level event extraction aims to extract event-related information from an
unstructured document composed of multiple sentences. Existing approaches are not …

Self-reported methods of recall and real-time recording are the most commonly used
approaches to assess dietary intake, both in research as well as the health-care setting. The …

Automated detection of intake gestures with wearable sensors has been a critical area of
research for advancing our understanding and ability to intervene in people's eating …

The paper reports some of the essential works done on the utilization of sensors for the
detection of food intake. Due to the health problems currently faced by the modern world, the …

The development of big data, machine learning, and the Internet of Things has led to rapid
advances in the research field of Active and Assisted Living (AAL). A human is placed in the …

This paper proposes a method to classify food types and to estimate meal intake amounts in
pre-and post-meal images through a deep learning object detection network. The food types …

In this paper, we propose an amount estimation method for food intake based on both color
and depth images. Two pairs of color and depth images are captured pre-and post-meals …

Now a days, E-health or electronic health monitoring system is one of the major applications
of wireless body area network (WBAN). Body area network or body sensor network (BSN) is …