Non-Invasive Data Acquisition and IoT Solution for Human Vital Signs Monitoring: Applications, Limitations and Future Prospects

The rapid development of technology has brought about a revolution in healthcare stimulating a wide range of smart and autonomous applications in homes, clinics, surgeries and hospitals. Smart healthcare opens the opportunity for a qualitative advance in the relations between healthcare providers and end-users for the provision of healthcare such as enabling doctors to diagnose remotely while optimizing the accuracy of the diagnosis and maximizing the benefits of treatment by enabling close patient monitoring. This paper presents a comprehensive review of non-invasive vital data acquisition and the Internet of Things in healthcare informatics and thus reports the challenges in healthcare informatics and suggests future work that would lead to solutions to address the open challenges in IoT and non-invasive vital data acquisition. In particular, the conducted review has revealed that there has been a daunting challenge in the development of multi-frequency vital IoT systems, and addressing this issue will help enable the vital IoT node to be reachable by the broker in multiple area ranges. Furthermore, the utilization of multi-camera systems has proven its high potential to increase the accuracy of vital data acquisition, but the implementation of such systems has not been fully developed with unfilled gaps to be bridged. Moreover, the application of deep learning to the real-time analysis of vital data on the node/edge side will enable optimal, instant offline decision making. Finally, the synergistic integration of reliable power management and energy harvesting systems into non-invasive data acquisition has been omitted so far, and the successful implementation of such systems will lead to a smart, robust, sustainable and self-powered healthcare system

Effect of Preform Thickness and Volume Fraction on Injection Pressure and Mechanical Properties of Resin Transfer Molded Composites

An experimental study is performed to characterize the effect of the thickness of random preforms on injection pressure and mechanical properties of resin transfer molded (RTM) parts. Center-gated, disk-shaped parts are molded using two different chopped-strand glass fiber preforms. Both preforms have random microstructure but different planar densities (i.e., different uncompressed layer thicknesses). Tensile strength, short-beam shear strength, and elastic modulus are measured for parts molded with each preform type at three different fiber volume fractions of 6.84, 15.55, and 24.83%. Although mechanical properties are found to increase linearly with volume fraction, significant difference is not observed between disks containing thick and thin mats at equivalent fiber volume fraction.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Idiopathic portal hypertension complicating systemic sclerosis: a case report

BACKGROUND: Patients with systemic sclerosis may develop mild abnormalities of liver function tests. More serious hepatic involvement has been well documented but is rare. Idiopathic portal hypertension had been reported only in a few female patients with systemic sclerosis. CASE PRESENTATION: An 82-year-old man with known systemic sclerosis presented with melaena. Urgent gastroscopy revealed oesophageal varices, which re-started bleeding during the procedure and were treated ensocopically, with Sengstaken tube and glypressin. Liver function tests and coagulation were normal. Non-invasive liver screen (including hepatitis viral serology and autoantibodies) was negative. Ultrasound scan of the abdomen revealed a small liver with coarse texture and no focal lesion. Hepato-portal flow was demonstrated in the portal vein. The spleen was enlarged. A moderate amount of free peritoneal fluid was present. A CT scan confirmed the absence of portal vein thrombosis. One month following discharge the patient had a liver biopsy. Histological examination showed essentially normal liver tissue; there was no evidence of any excess inflammation and no features to suggest cirrhosis or drug-induced liver disease. Taking into account the above evaluation we concluded that the patient had idiopathic portal hypertension. CONCLUSION: Both male and female patients with systemic sclerosis may – rarely – develop idiopathic portal hypertension

Conditional probabilities in quantum theory, and the tunneling time controversy

It is argued that there is a sensible way to define conditional probabilities in quantum mechanics, assuming only Bayes's theorem and standard quantum theory. These probabilities are equivalent to the ``weak measurement'' predictions due to Aharonov {\it et al.}, and hence describe the outcomes of real measurements made on subensembles. In particular, this approach is used to address the question of the history of a particle which has tunnelled across a barrier. A {\it gedankenexperiment} is presented to demonstrate the physically testable implications of the results of these calculations, along with graphs of the time-evolution of the conditional probability distribution for a tunneling particle and for one undergoing allowed transmission. Numerical results are also presented for the effects of loss in a bandgap medium on transmission and on reflection, as a function of the position of the lossy region; such loss should provide a feasible, though indirect, test of the present conclusions. It is argued that the effects of loss on the pulse {\it delay time} are related to the imaginary value of the momentum of a tunneling particle, and it is suggested that this might help explain a small discrepancy in an earlier experiment.Comment: 11 pages, latex, 4 postscript figures separate (one w/ 3 parts

How much time does a tunneling particle spend in the barrier region?

The question in the title may be answered by considering the outcome of a ``weak measurement'' in the sense of Aharonov et al. Various properties of the resulting time are discussed, including its close relation to the Larmor times. It is a universal description of a broad class of measurement interactions, and its physical implications are unambiguous.Comment: 5 pages; no figure

The course of mental health problems in children presenting with abdominal pain in general practice

Objective. To investigate the course of mental health problems in children presenting to general practice with abdominal pain and to evaluate the extent to which abdominal pain characteristics during follow-up predict the presence of mental health problems at 12 months' follow-up. Design. A prospective cohort study with one-year follow-up. Setting. 53 general practices in the Netherlands, between May 2004 and March 2006. Subjects. 281 children aged 4-17 years. Main outcome measures. The presence of a depressive problem, an anxiety problem, and multiple non-specific somatic symptoms at follow-up and odds ratios of duration, frequency, and severity of abdominal pain with these mental health problems at follow-up. Results. A depressive problem persisted in 24/74 children (32.9%; 95% CI 22.3-44.9%), an anxiety problem in 13/43 (30.2%; 95% CI 17.2-46.1%) and the presence of multiple non-specific somatic symptoms in 75/170 children (44.1%; 95% CI 36.7-51.6%). None of the abdominal pain characteristics predicted a depressive or an anxiety problem at 12 months' follow-up. More moments of moderate to severe abdominal pain predicted the presence of multiple nonspecific somatic symptoms at follow-up. Conclusions. In one-third of the children presenting to general practice for abdominal pain, anxiety and depressive problems persist during one year of follow-up. Characteristics of the abdominal pain during the follow-up period do not predict anxiety or depressive problems after one-year follow-up. We recommend following over time children seen in primary care with abdominal pain

Shrinking a large dataset to identify variables associated with increased risk of Plasmodium falciparum infection in Western Kenya

Large datasets are often not amenable to analysis using traditional single-step approaches. Here, our general objective was to apply imputation techniques, principal component analysis (PCA), elastic net and generalized linear models to a large dataset in a systematic approach to extract the most meaningful predictors for a health outcome. We extracted predictors for Plasmodium falciparum infection, from a large covariate dataset while facing limited numbers of observations, using data from the People, Animals, and their Zoonoses (PAZ) project to demonstrate these techniques: data collected from 415 homesteads in western Kenya, contained over 1500 variables that describe the health, environment, and social factors of the humans, livestock, and the homesteads in which they reside. The wide, sparse dataset was simplified to 42 predictors of P. falciparum malaria infection and wealth rankings were produced for all homesteads. The 42 predictors make biological sense and are supported by previous studies. This systematic data-mining approach we used would make many large datasets more manageable and informative for decision-making processes and health policy prioritization