Abstract Body Sensor Networks (BSNs) have emerged as a revolutionary technology in
many application domains in health-care, fitness, smart cities, and many other compelling …

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 …

The widespread presence of motion sensors on users' personal mobile devices has
spawned a growing research interest in human activity recognition (HAR). However, when …

The last 20 years have seen ever-increasing research activity in the field of human activity
recognition. With activity recognition having considerably matured, so has the number of …

Indoor pedestrian tracking extends location-based services to indoor environments where
GPS signal is rarely detected. Typical indoor localization method is Wi-Fi-based positioning …

Although indoor localization is a key topic for mobile computing, it is still very difficult for the
mobile sensing community to compare state-of-art localization algorithms due to the scarcity …

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 …

This paper describes how to recognize certain types of human physical activities using
acceleration data generated by a user's cell phone. We propose a recognition system in …

Monitoring the activities of daily living (ADLs) and detection of deviations from previous
patterns is crucial to assessing the ability of an elderly person to live independently in their …

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 …