Stephan Wegerich

• MS EECS
• Principal Investigator at physIQ

Sepsis is the leading cause of child death globally with low- and middle-income countries (LMICs) bearing a disproportionate burden of pediatric sepsis deaths. Limited diagnostic and critical care capacity and health worker shortages contribute to delayed recognition of advanced sepsis (severe sepsis, septic shock, and/or multiple organ dysfunction...

Effective response to vaccination requires activation of the innate immune system, triggering the synthesis of inflammatory cytokines. The subjective symptoms related to this, referred to as reactogenicity, affect a variable percentage of vaccinated people to different degrees, with evidence supporting a relationship between the severity of symptom...

Background: Atrial fibrillation (AF) is a common comorbidity in patients with heart failure with preserved ejection fraction (HFpEF) and in heart failure with mildly reduced ejection fraction (HFmrEF). Objectives: This study sought to describe AF burden and its clinical impact among individuals with HFpEF and HFmrEF who participated in a randomi...

Introduction: Little is known if, and to what extent, outpatient red blood cell (RBC) transfusions benefit chronic transfusion-dependent patients. Costs, labour, and potential side effects of RBC transfusions cause a restrictive transfusion strategy to be the standard of care. However, effects on the actual performance and quality of life of patie...

Mounting clinical evidence suggests that viral infections can lead to detectable changes in an individual's normal physiologic and behavioral metrics, including heart and respiration rates, heart rate variability, temperature, activity, and sleep prior to symptom onset, potentially even in asymptomatic individuals. While the ability of wearable dev...

The COVID-19 pandemic has accelerated the adoption of innovative healthcare methods, including remote patient monitoring. In the setting of limited healthcare resources, outpatient management of individuals newly diagnosed with COVID-19 was commonly implemented, some taking advantage of various personal health technologies, but only rarely using a...

Photoplethysmography (PPG) is a non-invasive and economical technique to extract vital signs of the human body. Although it has been widely used in consumer and research grade wrist devices to track a user's physiology, the PPG signal is very sensitive to motion which can corrupt the signal's quality. Existing Motion Artifact (MA) reduction techniq...

Photoplethysmography (PPG) is a non-invasive and economical technique to extract vital signs of the human body. Although it has been widely used in consumer and research grade wrist devices to track a user's physiology, the PPG signal is very sensitive to motion which can corrupt the signal's quality. Existing Motion Artifact (MA) reduction techniq...

BACKGROUND Little is known if and to what extent outpatient RBC transfusions benefit chronic transfusion dependent patients. Costs, labour, and small but remaining side effects of RBC transfusions cause restrictive transfusions strategy to be the standard of care. However, the actual performance and quality of life of patients who require RBC’s on...

Background: During the COVID-19 pandemic, novel digital health technologies have the potential to improve our understanding of SARS Co-V2/ COVID-19, improve care delivery and produce better health outcomes. The National Institutes of Health called on digital health leaders to contribute to a high-quality data repository that will support the work...

Background: Implantable cardiac sensors have shown promise in reducing rehospitalization for heart failure (HF), but the efficacy of noninvasive approaches has not been determined. The objective of this study was to determine the accuracy of noninvasive remote monitoring in predicting HF rehospitalization. Methods: The LINK-HF study (Multisensor...

Objective: Critical care capabilities needed for the management of septic patients, such as continuous vital sign monitoring, are largely unavailable in most emergency departments (EDs) in low- and middle-income country (LMIC) settings. This study aimed to assess the feasibility and accuracy of using a wireless wearable biosensor device for contin...

Introduction Low and middle-income countries (LMICs) bear a disproportionately high burden of sepsis, contributing to an estimated 90% of global sepsis-related deaths. Critical care capabilities needed for septic patients, such as continuous vital sign monitoring, are often unavailable in LMICs. Aim This study aimed to assess the feasibility and a...

Background The recent Ebola epidemic in West Africa strained existing healthcare systems well beyond their capacities due to the extreme volume and severity of illness of the patients. The implementation of innovative digital technologies within available care centres could potentially improve patient care as well as healthcare worker safety and ef...

A method and apparatus for monitoring and responding to conditions of an industrial process. Industrial process signals, such as repetitive manufacturing, testing and operational machine signals, are generated by a system. Sensor signals characteristic of the process are generated over a time length and compared to reference signals over the time l...

A method and system for performing surveillance of transient signals of an industrial device to ascertain the operating state. The method and system involves the steps of reading into a memory training data, determining neural network weighting values until achieving target outputs close to the neural network output. If the target outputs are inade...

A method and system for monitoring at least one of a system, a process and a data source. A method and system have been developed for carrying out surveillance, testing and modification of an ongoing process or other source of data, such as a spectroscopic examination. A signal from the system under surveillance is collected and compared with a ref...

This wireless sensor technology, currently being field-tested in an Ebola Treatment Unit in Sierra Leone, monitors multiple vital signs continuously and remotely. When connected with enhanced analytics software, it can discern changes in patients’ status much more quickly and intelligently than conventional periodic monitoring, thus saving critical...

Unlabelled: Background. Monitoring cardiovascular hemodynamics in the modern clinical setting is a major challenge. Increasing amounts of physiologic data must be analyzed and interpreted in the context of the individual patient’s pathology and inherent biologic variability. Certain data-driven analytical methods are currently being explored for s...

Ambulatory or in-hospital monitoring of patients is provided with early warning and prioritization, enabling proactive intervention and amelioration of both costs and risks of health care. Multivariate physiological parameters are estimated by empirical model to remove normal variation. Residuals are tested using a multivariate probability density...

Nonparametric model-based analytics personalized to the physiology of each patient are investigated for predictive monitoring of exacerbation in heart failure patients at home. Multivariate vital sign data are provided by means of continuous bio-signal acquisition with a mobile phone-based wearable sensor system worn by patients for several hours a...

Background: Accurate and early assessment of hemorrhage in the field is essential for the initiation of optimal prehospital care. At present this is done using clinical signs and symptoms. Stroke volume (SV) is a primary indicator of the degree of central blood volume, but measurement is not feasible in the field. The purpose of this study was to a...

Nonparametric modeling techniques are utilized extensively in applications involving the analysis of complex data sets. Nonparametric approaches have the desirable characteristic that they do not require a priori knowledge of the analytical form of the model meant to characterize a dataset. Instead, they rely exclusively on the available data to es...

Purpose – To provide an overview of the similarity‐based modeling (SBM) technology and review its application to condition monitoring of rotating equipment using features calculated from vibration sensor signals. Design/methodology/approach – Concentrates on the practical capabilities and underlying technology of SBM. Examines the effectiveness of...

A similarity-based modeling (SBM) technique is demonstrated that provides very early annunciation of the onset of gas path faults in aircraft engines. This powerful approach is shown to provide high fidelity estimates for real-time condition monitoring of aircraft engine signals. These estimates are used to detect the onset of changes in the inter-...

Monitoring rotating machinery is often accomplished with the aid of vibration sensors. The vibration sensor signals contain a wealth of complex information that characterizes the dynamic behavior of the machinery. Transforming this information into useful knowledge about the health of the machine can be challenging due to the presence of extraneous...

A method and system for automatically establishing operational parameters of a statistical surveillance system. The method and system performs a frequency domain transition on time dependent data, a first Fourier composite is formed, serial correlation is removed, a series of Gaussian whiteness tests are performed along with an autocorrelation test...

A method and system for monitoring a process and determining its condition. Initial data is sensed, a first set of virtual data is produced by applying a system state analyzation to the initial data, a second set of virtual data is produced by applying a neural network analyzation to the initial data and a parity space analyzation is applied to the...

A method and system for analyzing a source of data. The system and method involves initially training a system using a selected data signal, calculating at least two levels of sensitivity using a pattern recognition methodology, activating a first mode of alarm sensitivity to monitor the data source, activating a second mode of alarm sensitivity to...

A method and apparatus for monitoring a source of data for determining an operating state of a working system. The method includes determining a sensor (or source of data) arrangement associated with monitoring the source of data for a system, activating a method for performing a sequential probability ratio test if the data source includes a singl...

In this paper the authors develop further the results reported in Ref. 1 to include a systematic study of the effects of varying multivariate state estimation technique (MSET) models and model parameters for the Crystal River-3 (CR) feedwater flow system. The study used archived CR process computer files from November 1 to December 15, 1993, that w...

In this paper we expand on the results reported previously to include an effective method for improving the fault tolerance of an empirical PWR feedwater flow system model

A method and system are disclosed for providing nuclear fuel rods with a configuration of isotopic gas tags. The method includes selecting a true location of a first gas tag node, selecting initial locations for the remaining n-1 nodes using target gas tag compositions, generating a set of random gene pools with L nodes, applying a Hopfield network...

The analysis of archived Crystal River-3 feedwater flow data reveals a slow and steady degradation of the flow meter measurements during the 1992/1993 operating cycle. MSET can reliably estimate the true flow rate and quantify the degree of departure between the indicated signal and the true flow rate with high accuracy. The MSET computed flow rate...

A system and method for monitoring an industrial process and/or industrial data source. The system includes generating time varying data from industrial data sources, processing the data to obtain time correlation of the data, determining the range of data, determining learned states of normal operation and using these states to generate expected v...

The theoretical basis and validation studies of a real-time, model-based process monitoring and fault detection system is presented. Through use of a non-linear state estimation technique coupled with a probabilistically-based statistical hypothesis test, it is possible to detect and identify sensor, component and process faults at extremely early...

To assure the continued safe and reliable operation of a nuclear power station, it is essential that accurate online information on the current state of the entire system be available to the operators. Such information is needed to determine the operability of safety and control systems, the condition of active components, the necessity of preventa...

A neural network originally proposed by Szu for performing pattern recognition has been modified for use in a noisy manufacturing environment. Signals from the factory floor are frequently affine transformed and, as a consequence, a signal may not be properly aligned with respect to the input node that corresponds to the signal leading edge or with...

A properly designed automotive sensor monitoring and diagnostic system must be capable of detecting and distinguishing sensor and component malfunctions in the presence of signal noise, varying vehicle operating conditions and multiple faults. The technique presented in this paper addresses these objectives through the implementation of a multivari...

A properly designed monitoring and diagnostic system must be capable of detecting and distinguishing sensor and process malfunctions in the presence of signal noise, varying process states, and multiple faults. The technique presented addresses these objectives through the implementation of a multivariate state estimation algorithm based upon patte...

Complex special nuclear material (SNM) storage systems can benefit from automated monitoring and data integration systems that maximize safety and security and optimize system maintainability. Current methods of verification, which rely on physical access, are costly and labor intensive. A prototype data analysis. system for nuclear material monito...

Monitoring of the vibration characteristics of mechanical systems provides valuable insight into the health of the equipment. Evaluation of vibration features using standards derived from performance of new systems provides benefits in numerous applications. Analysis of the data stream is carried out either on-line or off-line, often utilizing Four...