Corey Nicholas Bufi

Gait characterization via pulse-Doppler radar

Falls are a major cause of injury in the elderly with almost 1/3rd of people aged 65 and more falling each year [1]. This work aims to use gait measurements from everyday living environments to estimate risk of falling and enable improved interventions. For this purpose, we consider the use of low-cost pulse-Doppler range control radar. These radars can continuously acquire data during normal activity of a person in night and day conditions and even in the presence of obstructing furniture. A short-time Fourier transform of the radar data reveals unique Doppler signatures from the torso motion and the leg swings. Two algorithms that can extract these features from the radar spectrogram are proposed in this study for estimating gait velocity and stride durations. The performance of the proposed radar system is evaluated with experimental data, which consists of 9 different walk types and a total of 27 separate tests. A high accuracy motion-capture camera system has also been used to acquire data simultaneously with the radar and provides the ground truth reference. Results indicate that the proposed radar system is a viable candidate for gait characterization and can be used to accurately track mean gait velocity, mean stride duration and stride duration variability. The gait velocity variability can also be estimated but with relatively larger error levels.

Ranked Relations: Query Languages and Query Processing Methods for Multimedia

In this paper, we describe the notion of a ranked relation that incorporates to the relational data model the notion of rank, i.e. ordering among tuples or objects. The ordering of tuples may be based on a single rank information, or multiple ranks combined together. We show that such relations arise naturally in many applications, especially in applications that query outside sources and return ranked relations as answers to content based queries. We introduce an algebra for querying ranked relations and give examples of its use for various applications. We then prove various properties of the algebra with special emphasis on the preservation of the coherence property, which shows when different rank columns are guaranteed to induce the same ordering among tuples. We show how these properties can be used to produce approximate early returns. Finally, we give experimental results based on Internet search engines for our early returns method and show that our method provides meaningful and fast answers to the user.