Non-invasive detection of hyperglycaemia in type 1 diabetic patients using electrocardiographic signals

University of Technology Sydney. Faculty of Engineering and Information Technology.Hyperglycaemia is the medical term for a state caused by a high level of blood glucose, resulting from defects in insulin secretion, insulin action, or both. Hyperglycaemia is a common dangerous complication to glycaemic control in Type 1 diabetic patients. The chronic hyperglycaemia of diabetes is associated with long-term damage, dysfunction, and failure of different organs, especially the eyes, kidneys, nerves, heart, and blood vessels. Therefore, reliable detection of hyperglycaemic episodes is important in order to avoid major health conditions. Conventionally, diabetic patients need to frequently monitor blood glucose levels to determine whether they have hyperglycaemia or not. A patient has to prick their finger (finger-stick) for a drop of blood several times a day, which can therefore significantly discourage many patients from periodically checking blood glucose levels. Another choice for hyperglycaemia detection might be continuous glucose monitoring systems (CGMS), which measure the glucose level in the interstitial fluid. For patients using CGMS, finger-sticks are still required to calibrate the sensor. The main shortcoming of CGMS is that glucose levels in interstitial fluid lag temporally behind blood glucose values, normally 10-15 minutes, which absolutely limits the accuracy of the detection. There is a strong demand to have a non-invasive technique to help patients to diagnose the disease easily and painlessly. Few methods have been reported to detect hyperglycaemia non-invasively or minimally invasively such as in exhaled methyl nitrates, and early detection of ongoing β cell death. However, the purpose of these studies was on real-time glucose control rather than disease diagnosis. Electrocardiography (ECG) is a broadly used technique to obtain a quick, non-invasive clinical and research screen for diagnosing abnormal rhythms of the heart caused by diseases. In fact, observations of ECG changes have been found in hypoglycaemia and hyperglycaemia states in T1DM, such as increased heart rate and prolongation of QT interval in hypoglycaemia, whereas hyperglycaemia was related to reduced heart rate variability. By using these findings in hypoglycaemia, researchers have developed an effective and sensitive system to detect hypoglycaemia non-invasively. These excellent performances of hypoglycaemia detection using ECG is the motivation of this thesis to study the effect of hyperglycaemia on ECG signals, and based on the findings to exploit the computational intelligence on the non-invasive detection of hyperglycaemia. This research firstly explores the changes of ECG parameters associated with the hyperglycaemic state in T1DM. The ECG parameters consist of ECG intervals relating to repolarisation phase and heart rate variability (HRV) measures. A clinical study of ten T1DM patients and ECG feature extraction process are conducted to collect ECG features. Statistical analysis is then applied to every ECG feature to estimate the significant difference between hyperglycaemic and normoglycaemic states. The results show that the selected ECG parameters in hyperglycaemia differ significantly from those in normoglycaemia (p< 0.05). It implies that certain ECG parameters are correlated with high blood glucose levels and they possibly contribute to the performance of hyperglycaemia detection. Thus, the ECG parameters are used for input data of hyperglycaemia classifiers in this thesis. Furthermore, the thesis introduces novel computational intelligent methods for hyperglycaemia detection using the ECG parameters. A neural network using Levenberg-Marquardt algorithm is the first method explored for hyperglycaemia detection in this thesis, known as LM-NN. The second algorithm is the integration of principal component analysis (PCA) with a neural network utilising the Levenberg-Marquardt algorithm, which is called a PCA-LM-NN network. PCA is a useful tool for dimensionality reduction to diminish the computational requirement and overcome the problem of multicollinearity. It is employed to filter the data so that only the significant independent ECG variables responsible for the high blood glucose levels can be used as input for the network training, in order that the neural network performs well for hyperglycaemia detection. The third method is for the improvement of the second method where particle swarm optimization is included. This algorithm is a combination of PCA, PSO and neural network, which is called PSO-NN. The PSO is utilised as an effective training algorithm to optimise the weights of the neural network. The proposed methods are compared with each other and with other traditional classifiers. All the algorithms are investigated with the clinical electrocardiographic data extracted from ten T1DM patients. The results show that the performance of PCA-LM model for hyperglycaemia detection is better than that of LM-NN (70.88% vs. 67.94%, in terms of geometric mean). In addition, the PSO-NN outperforms the PCA-LM-NN (77.58% vs. 70.88%, in terms of geometric mean). In short, the PSO-NN significantly improves the performances of both the LM-NN and PCA-LM-NN, with considerable sensitivity, specificity and geometric mean of 82.35%, 73.08% and 77.58%, respectively

Recent advances in experimental testing and computational modelling for characterisation of mechanical properties of biomaterials and biological cells

Biomaterials and biological cells possess a number of different properties; amongst them, mechanical properties are extremely important in studies and applications about tissue engineering, design and development of implants, surgical tools and medical devices for treatments and diagnosis of diseases. Changes in mechanical properties such as a stiffness of cells are often the signs of changes in cell physiology or diseases in tissues; and studying these changes can lead to the development of devices for early disease detection and new drug delivery mechanisms. This paper presents advances in recent years in experimental testing and computational modelling for characterisation of mechanical properties of biomaterials and biological cells, in which the presented research projects and related studies were mainly implemented by research groups in the UK. The recent important findings as well as research directions and challenges are emphasised and discussed, to open channels for research collaborations in development of cost-effective medical diagnosis and treatment solutions

Measurement of the branching ratio of pi^0 -> e^+e^- using K_L -> 3 pi^0 decays in flight

The branching ratio of the rare decay pi^0 -> e^+e^- has been measured in E799-II, a rare kaon decay experiment using the KTeV detector at Fermilab. The pi^0's were produced in fully-reconstructed K_L -> 3 pi^0 decays in flight. We observed 275 candidate pi^0 -> e^+e^- events, with an expected background of 21.4 +- 6.2 events which includes the contribution from Dalitz decays. We measured BR(pi^0 -> e^+e^-, x>0.95) = (6.09 +- 0.40 +- 0.24) times 10^{-8}, where the first error is statistical and the second systematic. This result is the first significant observation of the excess rate for this decay above the unitarity lower bound.Comment: New version shortened to PRL length limit. 5 pages, 4 figures. Published in Phys. Rev. Let

A search for the decay modes B+/- to h+/- tau l

We present a search for the lepton flavor violating decay modes B+/- to h+/- tau l (h= K,pi; l= e,mu) using the BaBar data sample, which corresponds to 472 million BBbar pairs. The search uses events where one B meson is fully reconstructed in one of several hadronic final states. Using the momenta of the reconstructed B, h, and l candidates, we are able to fully determine the tau four-momentum. The resulting tau candidate mass is our main discriminant against combinatorial background. We see no evidence for B+/- to h+/- tau l decays and set a 90% confidence level upper limit on each branching fraction at the level of a few times 10^-5.Comment: 15 pages, 7 figures, submitted to Phys. Rev.

Evidence for an excess of B -> D(*) Tau Nu decays

Based on the full BaBar data sample, we report improved measurements of the ratios R(D(*)) = B(B -> D(*) Tau Nu)/B(B -> D(*) l Nu), where l is either e or mu. These ratios are sensitive to new physics contributions in the form of a charged Higgs boson. We measure R(D) = 0.440 +- 0.058 +- 0.042 and R(D*) = 0.332 +- 0.024 +- 0.018, which exceed the Standard Model expectations by 2.0 sigma and 2.7 sigma, respectively. Taken together, our results disagree with these expectations at the 3.4 sigma level. This excess cannot be explained by a charged Higgs boson in the type II two-Higgs-doublet model. We also report the observation of the decay B -> D Tau Nu, with a significance of 6.8 sigma.Comment: Expanded section on systematics, text corrections, improved the format of Figure 2 and included the effect of the change of the Tau polarization due to the charged Higg

Study of Bc+B_c^+ decays to the K+K−π+K^+K^-\pi^+ final state and evidence for the decay Bc+→χc0π+B_c^+\to\chi_{c0}\pi^+

A study of $B_c^+\to K^+K^-\pi^+$ decays is performed for the first time using data corresponding to an integrated luminosity of 3.0 $\mathrm{fb}^{-1}$ collected by the LHCb experiment in $pp$ collisions at centre-of-mass energies of $7$ and $8$ TeV. Evidence for the decay $B_c^+\to\chi_{c0}(\to K^+K^-)\pi^+$ is reported with a significance of 4.0 standard deviations, resulting in the measurement of $\frac{\sigma(B_c^+)}{\sigma(B^+)}\times\mathcal{B}(B_c^+\to\chi_{c0}\pi^+)$ to be $(9.8^{+3.4}_{-3.0}(\mathrm{stat})\pm 0.8(\mathrm{syst}))\times 10^{-6}$. Here $\mathcal{B}$ denotes a branching fraction while $\sigma(B_c^+)$ and $\sigma(B^+)$ are the production cross-sections for $B_c^+$ and $B^+$ mesons. An indication of $\bar b c$ weak annihilation is found for the region $m(K^-\pi^+)<1.834\mathrm{\,Ge\kern -0.1em V\!/}c^2$, with a significance of 2.4 standard deviations.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://lhcbproject.web.cern.ch/lhcbproject/Publications/LHCbProjectPublic/LHCb-PAPER-2016-022.html, link to supplemental material inserted in the reference

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Search for direct pair production of the top squark in all-hadronic final states in proton-proton collisions at s√=8 TeV with the ATLAS detector

The results of a search for direct pair production of the scalar partner to the top quark using an integrated luminosity of 20.1fb−1 of proton–proton collision data at √s = 8 TeV recorded with the ATLAS detector at the LHC are reported. The top squark is assumed to decay via t˜→tχ˜01 or t˜→ bχ˜±1 →bW(∗)χ˜01 , where χ˜01 (χ˜±1 ) denotes the lightest neutralino (chargino) in supersymmetric models. The search targets a fully-hadronic final state in events with four or more jets and large missing transverse momentum. No significant excess over the Standard Model background prediction is observed, and exclusion limits are reported in terms of the top squark and neutralino masses and as a function of the branching fraction of t˜ → tχ˜01 . For a branching fraction of 100%, top squark masses in the range 270–645 GeV are excluded for χ˜01 masses below 30 GeV. For a branching fraction of 50% to either t˜ → tχ˜01 or t˜ → bχ˜±1 , and assuming the χ˜±1 mass to be twice the χ˜01 mass, top squark masses in the range 250–550 GeV are excluded for χ˜01 masses below 60 GeV

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT