Hybrid RF mapping and Kalman filtered spring relaxation for sensor network localization

An accurate and low-cost hybrid solution to the problem of autonomous self-localization in wireless sensor networks (WSN) is presented. The solution is designed to perform robustly under challenging radio propagation conditions in mind, while requiring low deployment efforts, and utilizing only low-cost hardware and light-weight distributed algorithms for location computation. Our solution harnesses the strengths of two approaches for environments with complex propagation characteristics: RF mapping to provide an initial estimate of each sensor's position based on a coarse-grain RF map acquired with minimal efforts; and a cooperative light-weight spring relaxation technique for each sensor to refine its estimate using Kalman filtered inter-node distance measurements. Using Kalman filtering to pre-process noisy distance measurements inherent in complex propagation environments, is found to have significant positive impacts on the subsequent accuracy and the convergence of our spring relaxation algorithm. Through extensive simulations using realistic settings and real data set, we show that our approach is a practical localization solution which can achieve sub-meter accuracy and fast convergence under harsh propagation conditions, with no specialized hardware or significant efforts required to deploy. © 2012 IEEE

RSS ranging based Wi-Fi localization for unknown path loss exponent

Localization of mobile phones is important to location-based mobile services, but achieving good location estimation of mobile phones is difficult especially in environment whose path loss exponent is unknown. In this paper, we present a Wi-Fi localization solution specifically designed for dense WLANs with unknown path loss exponent. In order to leverage between the computational cost and localization accuracy, our solution establishes a neighbor selection scheme based on the Voronoi diagram to identify a subset of Access Points (APs) to participate in localization. It considers the identified subset of APs and a mobile phone to be located as a mass-spring system. Provided with information of known coordinates of APs, the solution estimates the path loss exponent of the physical environment, infers inter-distances between APs and the mobile phone from Wi-Fi signals received, and implements spring relaxation algorithm to approximate the geographical location of the mobile phone, where this location estimation is fed back to refine the estimated exponent iteratively. Extensive simulation results confirm that our solution is able to provide location estimation with an attractive average accuracy of below 2 m in a typical Wi-Fi setup. © 2011 IEEE

RSS ranging based Wi-Fi localization for unknown path loss exponent

Localization of mobile phones is important to location-based mobile services, but achieving good location estimation of mobile phones is difficult especially in environment whose path loss exponent is unknown. In this paper, we present a Wi-Fi localization solution specifically designed for dense WLANs with unknown path loss exponent. In order to leverage between the computational cost and localization accuracy, our solution establishes a neighbor selection scheme based on the Voronoi diagram to identify a subset of Access Points (APs) to participate in localization. It considers the identified subset of APs and a mobile phone to be located as a mass-spring system. Provided with information of known coordinates of APs, the solution estimates the path loss exponent of the physical environment, infers inter-distances between APs and the mobile phone from Wi-Fi signals received, and implements spring relaxation algorithm to approximate the geographical location of the mobile phone, where this location estimation is fed back to refine the estimated exponent iteratively. Extensive simulation results confirm that our solution is able to provide location estimation with an attractive average accuracy of below 2 m in a typical Wi-Fi setup. © 2011 IEEE

Proceedings of the 3rd ACMIEEE international conference on Human robot interaction [electronic resource].

Title from The ACM Digital Library

Implication of Major Adverse Postoperative Events and Myocardial Injury on Disability and Survival: A Planned Subanalysis of the ENIGMA-II Trial.

BACKGROUND: Globally, >300 million patients have surgery annually, and ≤20% experience adverse postoperative events. We studied the impact of both cardiac and noncardiac adverse events on 1-year disability-free survival after noncardiac surgery. METHODS: We used the study cohort from the Evaluation of Nitrous oxide in Gas Mixture of Anesthesia (ENIGMA-II) trial, an international randomized trial of 6992 noncardiac surgical patients. All were ≥45 years of age and had moderate to high cardiac risk. The primary outcome was mortality within 1 postoperative year. We defined 4 separate types of postoperative adverse events. Major adverse cardiac events (MACEs) included myocardial infarction (MI), cardiac arrest, and myocardial revascularization with or without troponin elevation. MI was defined using the third Universal Definition and was blindly adjudicated. A second cohort consisted of patients with isolated troponin increases who did not meet the definition for MI. We also considered a cohort of patients who experienced major adverse postoperative events (MAPEs), including unplanned admission to intensive care, prolonged mechanical ventilation, wound infection, pulmonary embolism, and stroke. From this cohort, we identified a group without troponin elevation and another with troponin elevation that was not judged to be an MI. Multivariable Cox proportional hazard models for death at 1 year and assessments of proportionality of hazard functions were performed and expressed as an adjusted hazard ratio (aHR) and 95% confidence intervals (CIs). RESULTS: MACEs were observed in 469 patients, and another 754 patients had isolated troponin increases. MAPEs were observed in 631 patients. Compared with control patients, patients with a MACE were at increased risk of mortality (aHR, 3.36 [95% CI, 2.55-4.46]), similar to patients who suffered a MAPE without troponin elevation (n = 501) (aHR, 2.98 [95% CI, 2.26-3.92]). Patients who suffered a MAPE with troponin elevation but without MI had the highest risk of death (n = 116) (aHR, 4.29 [95% CI, 2.89-6.36]). These 4 types of adverse events similarly affected 1-year disability-free survival. CONCLUSIONS: MACEs and MAPEs occur at similar frequencies and affect survival to a similar degree. All 3 types of postoperative troponin elevation in this analysis were associated, to varying degrees, with increased risk of death and disability