Bayesian Contrast Measures and Clutter Distribution Determinants of Human Target Detection.

Human target detection is known to be dependent on a number of components: one, basic electro-optics including image contrast, the target size, pixel resolution, and contrast sensitivity; two, target shape, image type and features, types of clutter; and three, context and task requirements. Here, we consider a Bayesian approach to investigating how these components contribute to target detection. To this end, we develop and compare three different formulations for contrast: mean contrast, perceptual contrast, and a Bayesian-based histogram contrast statistic.

Functional range of movement of the hand: declination angles to reachable space.

The measurement of the range of hand joint movement is an essential part of clinical practice and rehabilitation. Current methods use three finger joint declination angles of the metacarpophalangeal, proximal interphalangeal and distal interphalangeal joints. In this paper we propose an alternate form of measurement for the finger movement.

Multi-kinect skeleton fusion for physical rehabilitation monitoring.

Kinect has been increasingly applied in rehabilitation as a motion capture device. However, the inherent limitations significantly hinder its further development in this important area. Although a number of Kinect fusion approaches have been proposed, only a few of them was actually considered for rehabilitation.

Non-contact measurement of respiratory function and deduction of tidal volume.

This paper further the investigation of Doppler radar feasibility in measuring the flow in and out due to inhalation and exhalation under different conditions of breathing activities. Three different experiment conditions were designed to investigate the feasibility and consistency of Doppler radar which includes the combination of the states of normal breathing, deep breathing and apnoea state were demonstrated. The obtained Doppler radar signals were correlated and compared with the gold standard medical device, spirometer, yielding a good correlations between both devices.

A syntactic two-component encoding model for the trajectories of human actions.

Human actions have been widely studied for their potential application in various areas such as sports, pervasive patient monitoring, and rehabilitation. However, challenges still persist pertaining to determining the most useful ways to describe human actions at the sensor, then limb and complete action levels of representation and deriving important relations between these levels each involving their own atomic components. In this paper, we report on a motion encoder developed for the sensor level based on the need to distinguish between the shape of the sensor's trajectory and its temporal characteristics during execution.