Development of a non-intrusive system to monitor radial pulse wave velocity

Understanding arterial distensibility has shown to be important in the pathogenesis of cardiovascular abnormalities like hypertension. It is also known that arterial pulse wave velocity (PWV) is a measure of the elasticity or stiffness of peripheral arterial blood vessels. However, it generally requires complex instrumentations to have an accurate measurement and not suited for continual monitoring. In this paper, it describes a simple and non-intrusive method to detect the cardiovascular pulse from a human wrist above the radial artery and a fingertip. The main components of this proposed method are a piezoelectric transducer and a photo-plethysmography circuitry. 5 healthy adults (4 male) with age ranging from 25 to 38 years were recruited. The timing consistency of the detected pulsations is first evaluated and compared to that obtained from a commercial electrocardiogram. Furthermore, the derived PWV is then assessed by the predicted values attained from regression equations of two previous similar studies. The results show good correlations (p < 0.05) and similarities for the former and latter respectively. The simplicity and non-invasive nature of the proposed method can be attractive for even younger or badly disturbed patients. Moreover, it can be used for prolonged monitoring for the comfort of the patients.

Customer information system data pre-processing with feature selection techniques for non-technical losses prediction in an electricity market

Non-technical losses (NTL) identification and prediction are important tasks for many utilities. Data from customer information system (CIS) can be used for NTL analysis. However, in order to accurately and efficiently perform NTL analysis, the original data from CIS need to be pre-processed before any detailed NTL analysis can be carried out. In this paper, we propose a feature selection based method for CIS data pre-processing in order to extract the most relevant information for further analysis such as clustering and classifications. By removing irrelevant and redundant features, feature selection is an essential step in data mining process in finding optimal subset of features to improve the quality of result by giving faster time processing, higher accuracy and simpler results with fewer features. Detailed feature selection analysis is presented in the paper. Both time-domain and load shape data are compared based on the accuracy, consistency and statistical dependencies between features.

Bifurcation analysis of a dynamic power system with SVC devices

Bifurcation analysis is a very useful tool for power system stability assessment. In this paper, detailed investigation of power system bifurcation behaviour is presented. One and two parameter bifurcation analysis are conducted on a 3-bus power system. We also examined the impact of FACTS devices on power system stability through Hopf bifurcation analysis by taking static Var compensator (SVC) as an example. A simplified first-order model of the SVC device is included in the 3-bus sample system. Real and reactive powers are used as bifurcation parameter in the analysis to compare the system oscillatory properties with and without SVC. The simulation results indicate that the linearized system model with SVC enlarge the voltage stability boundary by moving Hopf bifurcation point to higher level of loading conditions. The installation of SVC increases the dynamic stability range of the system, however complicates the Hopf bifurcation behavior of the system

Tracking of non-stationary time-series using resource allocating RBF networks

In this paper, we discuss some practical implications for implementing adaptable network algorithms applied to non-stationary time series problems. Using electricity load data and training with the extended Kalman filter, we demonstrate that the dynamic model-order increment procedure of the resource allocating RBF network (RAN) is highly sensitive to the parameters of the novelty criterion. We investigate the use of system noise and forgetting factors for increasing the plasticity of the Kalman filter training algorithm, and discuss the consequences for on-line model order selection. We also find that a recently-proposed alternative novelty criterion, found to be more robust in stationary environments, does not fare so well in the non-stationary case due to the need for filter adaptability during training.

A novel, dynamic, in vivo, non-contact method of measuring oxygen depletion rate of the anterior eye

Despite the importance of oxygen measurements, techniques have been limited by their invasive nature and small corneal area of assessment. The aim of this study was to assess a non-contact way of measuring oxygen uptake of the whole anterior eye.