Optical tomography provides a means for the determination of the spatial distribution of materials with different optical density in a volume by non-intrusive means. This paper presents results of concentration measurements of gas bubbles in a water column using an optical tomography system. A hydraulic flow rig is used to generate vertical air-water two-phase flows with controllable bubble flow rate. Two approaches are investigated. The first aims to obtain an average gas concentration at the measurement section, the second aims to obtain a gas distribution profile by using tomographic imaging. A hybrid back-projection algorithm is used to calculate concentration profiles from measured sensor values to provide a tomographic image of the measurement cross-section. The algorithm combines the characteristic of an optical sensor as a hard field sensor and the linear back projection algorithm.
Monitoring clinical activity at the bedside in the intensive care unit (ICU) can provide useful information to evaluate nursing care and patient recovery. However, it is labour intensive to quantify these activities and there is a need for an automated method to record and quantify these activities. This paper presents an automated system, Clinical Activity Tracking System (CATS), to monitor and evaluate clinical activity at the patient's bedside. The CATS uses four Microsoft Kinect infrared sensors to track bedside nursing interventions. The system was tested in a simulated environment where test candidates performed different motion paths in the detection area. Two metrics, 'Distance' and 'Dwell time', were developed to evaluate interventions or workload in the detection area. Results showed that the system can accurately track the intervention performed by individual or multiple subjects. The results of a 30-day, 24-hour preliminary study in an ICU bed space matched clinical expectations. It was found that the average 24-hour intervention is 22.0minutes/hour. The average intervention during the day time (7am-11pm) is 23.6minutes/hour, 1.4 times higher than 11pm-7am, 16.8minutes/hour. This system provides a unique approach to automatically collect and evaluate nursing interventions that can be used to evaluate patient acuity and workload demand.