Feasibility Assessment of Using Smart Trackers in Telemedicine Systems to Remotely Monitor the Overall Health of Patients in Real-Time

Introduction. The development of telemedicine systems intended to remotely monitor the health status of patients constitutes one of the most promising areas of contemporary science. Particularly relevant is the use of such systems to track the health of surgically treated patients. Since such patients are mobile, sensors measuring vital signs should not cause any discomfort in regular use. Thus, wearable smart trackers can be used for these purposes.Aim. The paper aims to study the possibility of using smart trackers in a telemedicine system for monitoring patient health.Materials and methods. In the study, a series of measurements was performed using GSMIN WR 41 smart bracelets in order to estimate their accuracy when measuring pulse, blood pressure, and oxygen saturation for different research subjects at rest and during intense physical exercises. In addition, the average measurement interval of the smart bracelet was determined; the operation of the smart bracelet in the telemedicine system for monitoring vital signs was considered.Results. The studies show that an average error in the measurement of vital signs (except for systolic pressure) using the smart bracelet does not exceed 10 %. In order to avoid the high error in measuring systolic pressure, an algorithm for assessing the general health of patients was developed. In addition, it is shown that the smart bracelet can detect an abrupt change in the vital signs of patients, with the average time of their measurement and data transmission to the server of the telemedicine system coming to 45 seconds.Conclusion. The study results indicate that smart bracelets can be used to remotely monitor the health of patients in real-time. These findings are confirmed by the telemedicine system designed on the basis of the smart bracelets considered in the paper.

Longitudinal Doppler Assessments in Late Preterm Fetal Growth Restriction

Purpose To assess the longitudinal variation of the ratio of umbilical and cerebral artery pulsatility index (UCR) in late preterm fetal growth restriction (FGR). Materials and Methods A prospective European multicenter observational study included women with a singleton pregnancy, 32+ 0–36+ 6, at risk of FGR (estimated fetal weight [EFW] or abdominal circumference [AC] < 10th percentile, abnormal arterial Doppler or fall in AC from 20-week scan of > 40 percentile points). The primary outcome was a composite of abnormal condition at birth or major neonatal morbidity. UCR was categorized as normal (< 0.9) or abnormal (≥ 0.9). UCR was assessed by gestational age at measurement interval to delivery, and by individual linear regression coefficient in women with two or more measurements. Results 856 women had 2770 measurements; 696 (81 %) had more than one measurement (median 3 (IQR 2–4). At inclusion, 63 (7 %) a UCR ≥ 0.9. These delivered earlier and had a lower birth weight and higher incidence of adverse outcome (30 % vs. 9 %, relative risk 3.2; 95 %CI 2.1–5.0) than women with a normal UCR at inclusion. Repeated measurements after an abnormal UCR at inclusion were abnormal again in 67 % (95 %CI 55–80), but after a normal UCR the chance of finding an abnormal UCR was 6 % (95 %CI 5–7 %). The risk of composite adverse outcome was similar using the first or subsequent UCR values. Conclusion An abnormal UCR is likely to be abnormal again at a later measurement, while after a normal UCR the chance of an abnormal UCR is 5–7 % when repeated weekly. Repeated measurements do not predict outcome better than the first measurement, most likely due to the most compromised fetuses being delivered after an abnormal UCR.

FO-Sketch: A Fast Oblivious Sketch for Secure Network Measurement Service in the Cloud

Network measurements are the foundation for network applications. The metrics generated by those measurements help applications improve their performance of the monitored network and harden their security. As severe network attacks using leaked information from a public cloud exist, it raises privacy and security concerns if directly deployed in network measurement services in a third-party public cloud infrastructure. Recent studies, most notably OblivSketch, demonstrated the feasibility of alleviating those concerns by using trusted hardware and Oblivious RAM (ORAM). As their performance is not good enough, and there are certain limitations, they are not suitable for broad deployment. In this paper, we propose FO-Sketch, a more efficient and general network measurement service that meets the most stringent security requirements, especially for a large-scale network with heavy traffic volume and burst traffic. Let a mergeable sketch update the local flow statistics in each local switch; FO-Sketch merges (in an Intel SGX-created enclave) these sketches obliviously to form a global “one big sketch” in the cloud. With the help of Oblivious Shuffle, Divide and Conquer, and SIMD speedup, we optimize all of the critical routines in our FO-Sketch to make it 17.3x faster than a trivial oblivious solution. While keeping the same level of accuracy and packet processing throughput as non-oblivious Elastic Sketch, our FO-Sketch needs only ∼4.5 MB enclave memory space in total to record metrics and for PORAM to store the global sketch in the cloud. Extensive experiments demonstrate that, for the recommended setting, it takes only ∼ 0.6 s in total to rebuild those data during each measurement interval.

Research on Risk Measurement and Early Warning of Electronic Banking Business Based on GMDH Algorithm

In order to deal with the problems of traditional e-banking risk measurement and early warning methods, such as low accuracy of e-banking risk measurement and longer early warning time, an e-banking risk measurement and early warning method based on the GMDH algorithm is proposed. This scheme mines the e-banking risk measurement and early warning indicators by the GMDH algorithm, and it will input the influencing factors and risk factors as independent variables into the GMDH modeling network and then input the e-banking business growth rate as the dependent variable into the GMDH modeling network which is standardized by the normative method of processing the e-banking business risk measurement and early warning index data. According to the processing results, it calculates the weight of the measurement and early warning index by the entropy method, and it constructs the e-banking risk measurement model with the genetic algorithm which can help to calculate the optimal solution of the parameters, formulate the risk measurement interval, and determine the risk in order to realize the risk warning of electronic banking business. The simulation results show that the proposed method has a higher accuracy of e-banking risk measurement and a shorter warning time.

EZ-DripLoss Assessment in Chicken Breast Meat Using Different Sample Areas, Fiber Orientation, and Measurement Intervals

Although the EZ-DripLoss method has been performed in numerous studies, there is a deficiency in our knowledge of the EZ-DripLoss method’s suitability for poultry meat analysis. This study aimed to research the effect of different sample areas (10, 20, and 30 mm; n = 240), and fiber orientations (vertical vs. horizontal) on the EZ-DripLoss in chicken breast meat measured across a period of five days. The influence of sample area on the EZ-DripLoss of chicken breast meat with respect to the fiber orientation and across the five-day measurement interval was significant between 10 and 30 mm samples, and between 20 and 30 mm samples (p < 0.001). The estimated regression coefficient showed that EZ-DripLoss for the samples with horizontal and vertical fiber direction of 10 and 20 mm, significantly increased by 0.04% per hour, while for the samples with vertical fiber direction whose diameter was 30 mm, it significantly increased by 0.06% per hour, and for the horizontal fiber direction, it significantly increased by 0.07% per hour. The samples with vertical fiber orientation had 0.50% greater EZ-DripLoss compared to the samples with horizontal fiber orientation. EZ-DripLoss evaluation in chicken breast should be performed with a sample core diameter of 20 mm, a vertical fiber orientation, and over the course of longer measurement intervals.

A Method for Measuring the Maximum Measurable Gain of a Passive Intermodulation Chamber

This paper presents an approximate method that allows the calculation of the maximum measurable gain (MMG) in an anechoic chamber. This method is realized by using a low passive intermodulation (PIM) medium-gain directional antenna. By reducing the distance between the antenna and the wall of the chamber to reduce path loss, the purpose of replacing a high-gain antenna with a medium-gain antenna is achieved. The specific relationship between distance and equivalent gain is given in this paper. The measurement interval is determined by the 3 dB beamwidth of the measurement antenna to scan the whole chamber. A set of corresponding data for the residual PIM level and the MMG of the chamber can be obtained by the method of measurement outlined herein. The feasibility of this method was verified by measurements in two PIM measurement chambers.

Experiments on the influence of spot fire and topography interaction on fire rate of spread

Spotting is thought to increase wildfire rate of spread (ROS) and in some cases become the main mechanism for spread. The role of spotting in wildfire spread is controlled by many factors including fire intensity, number of and distance between spot fires, weather, fuel characteristics and topography. Through a set of 30 laboratory fire experiments on a 3 m x 4 m fuel bed, subject to air flow, we explored the influence of manually ignited spot fires (0, 1 or 2), the presence or absence of a model hill and their interaction on combined fire ROS (i.e. ROS incorporating main fire and merged spot fires). During experiments conducted on a flat fuel bed, spot fires (whether 1 or 2) had only a small influence on combined ROS. Slowest combined ROS was recorded when a hill was present and no spot fires were ignited, because the fires crept very slowly downslope and downwind of the hill. This was up to, depending on measurement interval, 5 times slower than ROS in the flat fuel bed experiments. However, ignition of 1 or 2 spot fires (with hill present) greatly increased combined ROS to similar levels as those recorded in the flat fuel bed experiments (depending on spread interval). The effect was strongest on the head fire, where spot fires merged directly with the main fire, but significant increases in off-centre ROS were also detected. Our findings suggest that under certain topographic conditions, spot fires can allow a fire to overcome the low spread potential of downslopes. Current models may underestimate wildfire ROS and fire arrival time in hilly terrain if the influence of spot fires on ROS is not incorporated into predictions.

Abstract 14978: Heart Failure Patient Adherence and Decreased Perception of Illness During Remote Hemodynamic Monitoring

Introduction: Effective management of ambulatory heart failure (HF) requires active patient (pt) participation. In telemonitoring of weights and symptoms, pt adherence to transmission is often halved within 6 months (M). Although ambulatory pulmonary pressure-guided management decreases hospitalizations and improves quality of life, the time course of pt perception of illness and sense of security in relation to monitoring frequency is not known. Hypothesis: Pts will perceive decreased impact of their HF during pulmonary pressure-guided management, which may contribute to their engagement in transmission of ambulatory PAP. Methods: The post-approval study for the implanted PA sensor was amended to include serial measurements of pt reported outcomes, (PRO, n=143), including the Brief Illness Perception Questionnaire (BIPQ). Treatment was adjusted to a target PA diastolic pressure 8 to 20 mmHg and adherence to transmitting pressure data from home was collected. Results: In the PRO cohort, mean age was 68 years, 58% were male, and 55% with HFpEF. Negative illness perception (BIPQ) decreased during each measurement interval. Pts reported improvement in symptoms, sense of security, sense of control and less impact of illness on their emotions at each time point, equally with HFpEF or HFrEF. In this cohort pt adherence to transmitting pressures was high throughout 24 M, Fig.1. Perception of illness was most favorable at 2 years, at which time there was a slight decline in transmission frequency. Conclusions: Pt perception of HF was positively impacted during ambulatory hemodynamic monitoring including improvement in symptoms, less emotional effect of illness, improved sense of security and control over their HF throughout follow-up. This was associated with high-level pt adherence to pressure data transmission. The optimal level of chronic monitoring for stable pts to maintain clinical benefit while minimizing disease awareness beyond 2 years is still unknown.

A SOM based Anomaly Detection Method for Wind Turbines Health Management through SCADA Data

In this paper, a data driven method for Wind Turbine system level anomaly detection and root sub-component identification is proposed. Supervisory control and data acquisition system (SCADA) data of WT is adopted and several parameters are selected based on physical knowledge in this domain and correlation coefficient analysis to build a normal behavior model. This model which is based on Self-organizing map (SOM) projects higher-dimensional SCADA data into a two-dimension-map. Afterwards, the Euclidean distance based indicator for system level anomalies is defined and a filter is created to screen out suspicious data points based on quantile function. Moreover, a failure data pattern based criterion is created for anomaly detection from system level. In order to track which sub-component should be responsible for an anomaly, a contribution proportion (CP) index is proposed. The method is tested with a two-month SCADA dataset with the measurement interval as 20 seconds. Results demonstrate capability and efficiency of the proposed method.