Smart wearables collect and analyze data, and in some scenarios make a smart decision
and provide a response to the user and are finding more and more applications in our daily …

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 …

With the development of artificial intelligence and the broad application of sensors, human
activity recognition (HAR) technologies based on noninvasive environmental sensors have …

As a new revolution of the Internet, Internet of Things (IoT) is rapidly gaining ground as a
new research topic in many academic and industrial disciplines, especially in healthcare …

This paper presents a review of different classification techniques used to recognize human
activities from wearable inertial sensor data. Three inertial sensor units were used in this …

A variety of real-life mobile sensing applications are becoming available, especially in the
life-logging, fitness tracking and health monitoring domains. These applications use mobile …

Activity detection and classification are very important for autonomous monitoring of humans
for applications, including assistive living, rehabilitation, and surveillance. Wearable sensors …

Human activity recognition (HAR) is a very active yet challenging and demanding area of
computer science. Due to the articulated nature of human motion, it is not trivial to detect …

Providing accurate and opportune information on people's activities and behaviors is one of
the most important tasks in pervasive computing. Innumerable applications can be …

Signal segmentation is a crucial stage in the activity recognition process; however, this has
been rarely and vaguely characterized so far. Windowing approaches are normally used for …