Publications by authors named "Guy Dumont"

Article Synopsis
  • - The study introduces a new method for non-contact respiratory rate (RR) estimation in infants, which is important given their sensitive skin, particularly in a neonatal intensive care unit (NICU) setting.
  • - Researchers used an advanced technique called Eulerian video magnification to enhance video footage and developed a unique way to set peak prominence thresholds to handle challenges like low light and babies being swaddled.
  • - The results show that the new algorithm reliably estimates RR, achieving high agreement with visual counts compared to traditional methods, indicating its effectiveness even in challenging NICU conditions.
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Article Synopsis
  • Infectious diseases contribute to a significant portion of under-five mortality in low- and middle-income countries, and clinical prediction models like Smart Triage can help identify critically ill infants to improve care.
  • A study aimed to externally validate the Smart Triage model using data from Uganda and Kenya, finding it performed better for children over one month than for neonates.
  • After adjusting for neonate-specific thresholds, the model showed improved predictive accuracy, suggesting it could be incorporated into local healthcare guidelines, though further validation is necessary.
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This paper explores automated face and facial landmark detection of neonates, which is an important first step in many video-based neonatal health applications, such as vital sign estimation, pain assessment, sleep-wake classification, and jaundice detection. Utilising three publicly available datasets of neonates in the clinical environment, 366 images (258 subjects) and 89 (66 subjects) were annotated for training and testing, respectively. Transfer learning was applied to two YOLO-based models, with input training images augmented with random horizontal flipping, photo-metric colour distortion, translation and scaling during each training epoch.

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Spreading depression (SD), a pathological cortical negative DC potential, is caused by an elevation of potassium ions in the extracellular space. This leads to a transient relocation of ions within neurons and a slow spread through brain tissue. Our previous research established a correlation between scalp SD and seizures in patients with intractable epilepsy using our novel electroencephalography (EEG).

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Inter-individual variability in Pharmacokinetic (PK) and Pharmacodynamic (PD) models significantly affects the accuracy of Target Controlled Infusion and closed-loop control of anesthesia. We hypothesize that the novel Eleveld PK model captures more inter-individual variability relevant to both open-loop and closed-loop control design, resulting in reduced variability in PD models identified using the Eleveld PK model's plasma prediction compared to the Schuttler or Schnider PK model. We used a dataset of propofol infusion rates and Depth of Hypnosis measurements across three demographic groups: elderly, obese, and adult.

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Introduction: Repetitive subconcussive head impacts can lead to subtle neural changes and functional consequences on brain health. However, the objective assessment of these changes remains limited. Resting state blink-related oscillations (BROs), recently discovered neurological responses following spontaneous blinking, are explored in this study to evaluate changes in BRO responses in subconcussive head impacts.

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Ionic currents within the brain generate voltage oscillations. These bioelectrical activities include ultra-low frequency electroencephalograms (DC-EEG, frequency less than 0.1 Hz) and conventional clinical electroencephalograms (AC-EEG, 0.

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Objective: To inform digital health design by evaluating diagnostic test properties of antenatal blood pressure (BP) outputs and levels to identify women at risk of adverse outcomes.

Design: Planned secondary analysis of cluster randomised trials.

Setting: India, Pakistan, Mozambique.

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Accurate clinical sensors and devices are essential to support optimal medical decision-making, and accuracy can be demonstrated through the conduct of clinical validation studies using validated reference sensors and/or devices for comparison. Typically unmeasurable, the true reference value can be substituted with an accepted physiological measurement with an associated uncertainty. We describe a basic model of measurement uncertainty that specifies the factors that may degrade the accuracy of an observed measurement value from a sensor, and we detail validation study design strategies that may be used to quantify and minimize these uncertainties.

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The COVID-19 pandemic has had an enormous toll on human health and well-being and led to major social and economic disruptions. Public health interventions in response to burgeoning case numbers and hospitalizations have repeatedly bent down the epidemic curve, effectively creating a feedback control system. Worst case scenarios have been avoided in many places through this responsive feedback.

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Stethoscope-recorded chest sounds provide the opportunity for remote cardio-respiratory health monitoring of neonates. However, reliable monitoring requires high-quality heart and lung sounds. This paper presents novel artificial intelligence-based Non-negative Matrix Factorisation (NMF) and Non-negative Matrix Co-Factorisation (NMCF) methods for neonatal chest sound separation.

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Neonatal respiratory distress is a common condition that if left untreated, can lead to short- and long-term complications. This paper investigates the usage of digital stethoscope recorded chest sounds taken within 1 min post-delivery, to enable early detection and prediction of neonatal respiratory distress. Fifty-one term newborns were included in this study, 9 of whom developed respiratory distress.

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Obtaining high quality heart and lung sounds enables clinicians to accurately assess a newborns cardio-respiratory health and provide timely care. However, noisy chest sound recordings are common, hindering timely and accurate assessment. A new Non-negative Matrix Co-Factorisation based approach is proposed to separate noisy chest sound recordings into heart, lung and noise components to address this problem.

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. Investigation of the night-to-night (NtN) variability of pulse oximetry features in children with suspicion of Sleep Apnea..

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This paper presents a two-component framework to detect model-plant mismatch (MPM) in cross-directional (CD) processes on paper machines under model-predictive control. First, routine operating data is used for system identification in closed loop; second, a one-class support vector machine (SVM) is trained to predict MPM. The iterative identification method alternates between identifying the finite impulse response coefficients of the spatial and temporal models.

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Background: Closed-loop control of propofol-remifentanil anesthesia using the processed electroencephalography depth-of-hypnosis index provided by the NeuroSENSE monitor (WAVCNS) has been previously described. The purpose of this placebo-controlled study was to evaluate the performance (percentage time within ±10 units of the setpoint during the maintenance of anesthesia) of a closed-loop propofol-remifentanil controller during induction and maintenance of anesthesia in the presence of a low dose of ketamine.

Methods: Following ethical approval and informed consent, American Society of Anesthesiologist (ASA) physical status I-II patients aged 19-54 years, scheduled for elective orthopedic surgery requiring general anesthesia for >60 minutes duration, were enrolled in a double-blind randomized, placebo-controlled, 2-group equivalence trial.

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Conducting collaborative and comprehensive epidemiological research on neonatal sepsis in low- and middle-income countries (LMICs) is challenging due to a lack of diagnostic tests. This prospective study protocol aims to obtain epidemiological data on bacterial sepsis in newborns and young infants at Kamuzu Central Hospital in Lilongwe, Malawi. The main goal is to determine if the use of whole blood transcriptome host immune response signatures can help in the identification of infants who have sepsis of bacterial causes.

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With advances in digital stethoscopes, internet of things, signal processing and machine learning, chest sounds can be easily collected and transmitted to the cloud for remote monitoring and diagnosis. However, low quality of recordings complicates remote monitoring and diagnosis, particularly for neonatal care. This paper proposes a new method to objectively and automatically assess the signal quality to improve the accuracy and reliability of heart rate (HR) and breathing rate (BR) estimation from noisy neonatal chest sounds.

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Objective: Monitoring of the ultra-low frequency potentials, particularly cortical spreading depression (CSD), is excluded in epilepsy monitoring due to technical barriers imposed by the scalp ultra-low frequency electroencephalogram (EEG). As a result, clinical studies of CSD have been limited to invasive EEG. Therefore, the occurrence of CSD and its interaction with epileptiform field potentials (EFP) require investigation in epilepsy monitoring.

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Article Synopsis
  • The study aims to evaluate the effectiveness of advanced control structures (Youla controllers) versus simpler PID-based controllers in hypnosis regulation during anesthesia.
  • It uses a two-step methodology: synthesizing robust optimal filtered PID controllers based on 47 pediatric pharmacological models, followed by individualizing the controllers for each model.
  • The results show that while all designs had similar frequency response characteristics, the performance difference between the Youla and the individually optimized PID controllers was minimal, indicating that personalized PID controllers may be equally effective without the complexity of advanced control systems.
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Closed-loop controlled drug dosing has the potential of revolutionizing clinical anesthesia. However, inter-patient variability in drug sensitivity poses a central challenge to the synthesis of safe controllers. Identifying a full individual pharmacokinetic-pharmacodynamic (PKPD) model for this synthesis is clinically infeasible due to limited excitation of PKPD dynamics and presence of unmodeled disturbances.

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Background: Sepsis is the leading cause of death and disability in children. Every hour of delay in treatment is associated with an escalating risk of morbidity and mortality. The burden of sepsis is greatest in low- and middle-income countries where timely treatment may not occur due to delays in diagnosis and prioritization of critically ill children.

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Dose-dependent effects of ketamine on processed electroencephalographic depth-of-hypnosis indices have been reported. Limited data are available for the NeuroSENSE WAV index. Our aim was to establish the feasibility of closed-loop propofol-remifentanil anesthesia guided by the WAV index in the presence of an analgesic dose of ketamine.

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