Biomedical Commons^™

Technologies For Wearable Seizure Detection: A Systematic Review, Rhema Losli

University Honors Theses

Knowing when a seizure occurred is helpful because this information can be used to evaluate the effectiveness of seizure interventions and possibly alert caregivers to emergency situations. The current practice for recording seizures outside of a hospital and without sensors is through keeping a self-reported seizure diary. This practice may be unreliable if the diary is not updated or the person having the seizure does not realize it is happening. Wearable seizure detectors aim to solve this problem by reliably recording when a seizure happened and either sending out an alert or storing the data for later analysis. In this …

Short-Term Tracking Of Orientation With Inertial Sensors, Golriz Sedaghat

Dissertations and Theses

In the past several years, IMU's have been widely used to measure the orientation of a moving body over a continuous period of time. Although, inertial navigation is a common approach for estimating the orientation, it greatly suffers from the accumulation of error in the orientation estimation. Most of the current common practices apply zero velocity update as a calibration method to address this problem and improve the estimation accuracy. However, this approach requires the sensors to be stationary frequently.

This thesis introduces a novel method of calibration for estimating the elevation and bank angles of the orientation over a …

Associative Learning In Biochemical Networks, Yasmin S. Sepulveda

REU Final Reports

Emerging evidence suggests that biochemical networks can be modeled by exploiting their ability to learn through associative learning. This type of learning in biomolecular structures gives it a the advantage to be able to be computationally model, and condition. Associative learning in biochemical networks is a developing area of study that once understood, can further develop diagnostic applications, and be used as tools for data analysis. Although it is a open ended project the motive of this research was to find the the best method of association learning being used in current work. After reading current work three associative learning …

Deciphering The Rules Of Cell-To-Cell Coupling By Molecular Modeling And Simulation, Linda D. Lee

REU Final Reports

Intercellular communication is vital for quick adjustments and maintenance for cell function and development. Gap junctions are membranes channel proteins that enable this direct communication between adjacent cells throughout the body. The compatibility of connexins (Cx), which make up a gap junction, determines whether a gap junction can form. Though many studies show which connexins are compatible, the molecular basis is not known (Bai & Wang, 2014). Through computational modeling, we identify the residues that energetically contribute most favorably at the docking interface of homotypic and heterotypic combinations of Cx43, Cx46, and Cx50 gap junctions. However, due to instability of …

Toward Improving Electrocardiogram (Ecg) Biometric Verification Using Mobile Sensors: A Two-Stage Classifier Approach, Robin Tan, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

Electrocardiogram (ECG) signals sensed from mobile devices pertain the potential for biometric identity recognition applicable in remote access control systems where enhanced data security is demanding. In this study, we propose a new algorithm that consists of a two-stage classifier combining random forest and wavelet distance measure through a probabilistic threshold schema, to improve the effectiveness and robustness of a biometric recognition system using ECG data acquired from a biosensor integrated into mobile devices. The proposed algorithm is evaluated using a mixed dataset from 184 subjects under different health conditions. The proposed two-stage classifier achieves a total of 99.52% subject …

Algorithm For Premature Ventricular Contraction Detection From A Subcutaneous Electrocardiogram Signal, Iris Lynn Shelly

Dissertations and Theses

Cardiac arrhythmias occur when the normal pattern of electrical signals in the heart breaks down. A premature ventricular contraction (PVC) is a common type of arrhythmia that occurs when a heartbeat originates from an ectopic focus within the ventricles rather than from the sinus node in the right atrium. This and other arrhythmias are often diagnosed with the help of an electrocardiogram, or ECG, which records the electrical activity of the heart using electrodes placed on the skin. In an ECG signal, a PVC is characterized by both timing and morphological differences from a normal sinus beat.

An implantable cardiac …

A Novel Particle Filtering Method For Estimation Of Pulse Pressure Variation During Spontaneous Breathing, Sunghan Kim, Fouzia Noor, Mateo Aboy, James Mcnames

Electrical and Computer Engineering Faculty Publications and Presentations

Background: We describe the first automatic algorithm designed to estimate the pulse pressure variation ([Formula: see text]) from arterial blood pressure (ABP) signals under spontaneous breathing conditions. While currently there are a few publicly available algorithms to automatically estimate [Formula: see text] accurately and reliably in mechanically ventilated subjects, at the moment there is no automatic algorithm for estimating [Formula: see text] on spontaneously breathing subjects. The algorithm utilizes our recently developed sequential Monte Carlo method (SMCM), which is called a maximum a-posteriori adaptive marginalized particle filter (MAM-PF). We report the performance assessment results of the proposed algorithm on …

Device, Method, And Algorithm To Assess Changes In Cardiac Output Via Intracardiac Impedance Monitoring, Geoffrey Fredrick Schau

Dissertations and Theses

Cardiac output, the volume of blood pumped by the heart over time, is a powerful clinical metric used by physicians to assess overall cardiac health and patient well-being. However, current cardiac output estimation methods are typically invasive, time-consuming, expensive, or some combination of all three. Patients that receive artificial cardiac pacemaker devices are particularly susceptible to cardiac dysfunction and often require long-term cardiac monitoring support.

This thesis proposes a novel cardiac output monitoring solution which leverages an implantable intracardiac medical device. The principles of traditional impedance cardiography, an established cardiac output monitoring technique in practice for over fifty years, have …

Design, Construction, And Utilization Of Physical Vapor Deposition Systems For Medical Sensor Fabrication, Nicholas Sayre, Abdul Almetairi, Alex Chally, Joe Kowalski, Erik J. Sánchez

Student Research Symposium

The development of a novel blood glucose sensor is realized through construction of a homemade plasma coating system and utilization of semiconductor manufacturing processes in a small scale cleanroom environment. Photolithography, plasma sputtering, chemical etching and thin film measurement technologies are used in the medical sensor fabrication process. General process flow will be discussed, and system design and the plasma sputtering process will be presented as it is achieved by the system currently under development.

Chemical Reaction Network Control Systems For Agent-Based Foraging Tasks, Joshua Stephen Moles

Dissertations and Theses

Chemical reaction networks are an unconventional computing medium that could benefit from the ability to form basic control systems. In this work, we demonstrate the functionality of a chemical control system by evaluating classic genetic algorithm problems: Koza's Santa Fe trail, Jefferson's John Muir trail, and three Santa Fe trail segments. Both Jefferson and Koza found that memory, such as a recurrent neural network or memories in a genetic program, are required to solve the task. Our approach presents the first instance of a chemical system acting as a control system. We propose a delay line connected with an artificial …

Automated Channel Assessment For Single Chip Medradio Transceivers, Mark Alexander Hillig

Dissertations and Theses

Modern implantable and body worn medical devices leverage wireless telemetry to improve patient experience and expand therapeutic options. Wireless medical devices are subject to a unique set of regulations in which monitoring of the available frequency spectrum is a requirement. To this end, implants use software protocols to assess the in-band activity to determine which channel should be used. These software protocols take valuable processing time and possibly degrade the operational lifetime of the battery. Implantable medical devices often take advantage of a single chip transceiver as the physical layer for wireless communications. Embedding the channel assessment task in the …

Measuring The Accuracy Of Predictions From Patient-Specific Models Of Intracranial Pressure Dynamics, Wayne W. Wakeland

Complex Systems Faculty Publications and Presentations

Objective: Determine the prediction capability of a computer model of Intracranial pressure (ICP) dynamics.

Creating Clinically Useful In Silico Models Of Intracranial Pressure Dynamics, Wayne W. Wakeland, Joe Fusion, Brahm Goldstein

Complex Systems Faculty Publications and Presentations

To create clinically useful computer simulation models of intracranial pressure (ICP) dynamics by using prospective clinical data to estimate subject-specific physiologic parameters.

Using Optimization To Calibrate Models Of Intracranial Pressure Dynamics To Patients With Intracranial Hypertension, Wayne W. Wakeland, A. Bulbul, Mateo Aboy, James Mcnames, Brahm Goldstein

Complex Systems Faculty Publications and Presentations

Aim: Automatically calibrate ICP Dynamic model to a specific patients.

Method: Use optimization algorithm to estimate parameter values (ICP, compliances, resistances) that minimize the squared error in predicted ICP.

Results: Estimated parameter values are plausible and improve predicted ICP. Optimization time for 18 minute episode = 2.5 min. for 1 parameter, 10 to 200 min. for multiple simultaneous parameters (too long).

A Comparison Of System Dynamics And Agent-Based Simulationapplied To The Study Of Cellular Receptor Dynamics, Wayne W. Wakeland, Edward J. Gallaher, Louis Macovsky, C. Athena Aktipis

Complex Systems Faculty Publications and Presentations

Cellular receptor dynamics are often analyzed using differential equations, making system dynamics (SD) a candidate methodology. In some cases it may be useful to model the phenomena at the biomolecular level, especially when concentrations and reaction probabilities are low and might lead to unexpected behavior modes. In such cases, agent-based simulation (ABS) may be useful. We show the application of both SD and ABS to simulate non-equilibrium ligand-receptor dynamics over a broad range of concentrations, where the probability of interaction varies from low to very low. Both approaches offer much to the researcher and are complementary. We did not find …

Calibrating An Intracranial Pressure Dynamics Model With Clinical Data - A Progress Report, Wayne W. Wakeland, James Mcnames, Brahm Goldstein

Complex Systems Faculty Publications and Presentations

We describe the calibration of a computer model of intracranial pressure (ICP) dynamics to correspond with annotated clinical data taken from a patient being treated for elevated ICP due to a traumatic brain injury. The research protocol employed during treatment includes adjusting the elevation of the head of the bed, adjusting the ventilator settings to induce mild hyperventilation and hypoventilation, and adjusting the height of the cerebrospinal fluid drainage system. The model behavior corresponds to the experimental data quite well in the case of the changing the head of the bed, but less well in the case of changing the …

Modeling Intracranial Fluid Flows And Volumes During Traumatic Brain Injury To Better Understand Pressure Dynamics, Wayne W. Wakeland, James Mcnames, Mateo Aboy, D. Hollemon, Brahm Goldstein

Complex Systems Faculty Publications and Presentations

See additional files below for the Presentation.

We describe a computer model of intracranial pressure (ICP) dynamics that evaluates clinical treatment options for elevated ICP during traumatic brain injury (TBI). The model uses fluid volumes as primary state variables and explicitly models fluid flows as well as the resistance, compliance, and pressure associated with each intra - and extracranial compartment (arteries and arterioles, capillary bed, veins, venous sinus, ventricles, and brain parenchyma). The model evaluates clinical events and therapies such as intra - and extra-parenchymal hemorrhage, cerebral edema, cerebrospinal fluid drainage, mannitol administration, head elevation, and mild hyperventilation. The model …