Increased life expectancy coupled with declining birth rates is leading to an aging
population structure. Aging-caused changes, such as physical or cognitive decline, could …

This paper surveys the current research directions of activity recognition using inertial
sensors, with potential application in healthcare, wellbeing and sports. The analysis of …

The proliferation of smartphones has significantly facilitated people's daily life, and diverse
and powerful embedded sensors make smartphone a ubiquitous platform to acquire and …

The ubiquity of smartphones together with their ever-growing computing, networking, and
sensing powers have been changing the landscape of people's daily life. Among others …

This paper presents a systematic design approach for constructing neural classifiers that are
capable of classifying human activities using a triaxial accelerometer. The philosophy of our …

This paper developed a high-accuracy human activity recognition system based on single tri-
axis accelerometer for use in a naturalistic environment. This system exploits the discrete …

Body sensor networks (BSN) have emerged as an active field of research to connect and
operate sensors within, on or at close proximity to the human body. BSN have unique roles …

Although human activity recognition (HAR) has been studied extensively in the past decade,
HAR on smartphones is a relatively new area. Smartphones are equipped with a variety of …

The fixed-size non-overlap** sliding window (FNSW) and fixed-size overlap** sliding
window (FOSW) approaches are the most commonly used data-segmentation techniques in …

In this paper, the autoregressive (AR) model of time-series is presented to recognize human
activity from a tri-axial accelerometer data. Four orders of autoregressive model for …