Biomedical Commons^™

Design And Validation Of A Low-Cost Wearable Electromyography (Emg) System For Monitoring Exercise-Induced Changes In Muscle Activity, Ingrid E. Halverson

Dissertations, Master's Theses and Master's Reports

Wearable technologies have expanded opportunities for monitoring athletic performance, but many existing systems remain costly and confined to laboratory or medical settings. This thesis presents the design, development, and evaluation of a low-cost, wearable EMG platform for monitoring neuromuscular activity during exercise. A wireless device incorporating a surface EMG sensor, an ESP32 microcontroller, and Wi-Fi transmission was developed to acquire muscle activation data. Signal processing techniques, including filtering, root-mean-square (RMS), mean frequency (MNF), and median frequency (MDF) analyses, were used to evaluate changes in muscle activation. Experimental testing demonstrated reliable wireless data acquisition and successful capture of physiological changes before …

Identification Of Fiducial Points In Seismocardiographic Cycles Using Manual And Automated Annotation Methods, Jasmine-Vy T. Truong

Honors Undergraduate Theses

There is currently a need for complementary methods for non-invasive cardiac monitoring. Seismocardiography (SCG), the measurement of cardiac-induced vibrations at the chest surface, has shown potential clinical utility. Improving the reliability of detecting fiducial points of electrocardiography (ECG) and SCG, which collectively capture the electro-mechanical cardiac activities, could expand ECG/SCG utility as a low-cost, accessible tool for clinical assessment. This study identifies commonly accepted criteria for fiducial point detection in SCG and ECG through an extensive literature review and signal processing techniques. The previous criteria were evaluated to identify their strengths and weaknesses. Based on the findings, an improved set …

Heartfev1: A Mobile Electrocardiogram Based System For Inferring Forced Expiratory Volume In One Second From Patients With Chronic Obstructive Pulmonary Disease, Maria Nyamukuru

Dartmouth College Ph.D Dissertations

Chronic Obstructive Pulmonary Disease (COPD), characterized by chronic airway inflammation and airflow obstruction, is the third leading cause of death globally. Patients with COPD experience exacerbated symptoms like breathlessness and cough, significantly impacting their quality of life and leading to costly hospitalizations. Early detection of COPD exacerbations is crucial for mitigating these negative effects.

The most critical element for early detection of COPD exacerbations is daily monitoring of lung function, particularly forced expiratory volume in one second (FEV1), a key metric of lung function. By tracking declines in FEV1, COPD exacerbations can be predicted up to two weeks in advance, …

Synthetic Heart Sound Dataset, Davoud Shariat Panah, Andrew Hines, Susan Mckeever

Datasets

The repository contains synthetic heart sound recordings. The publication related to this dataset is "Exploring the impact of noise and degradations on heart sound classification models", Biomedical Signal Processing and Control journal.

Error Prevention In Sensors And Sensor Systems, Pedro J. Chacon Dominguez

LSU Doctoral Dissertations

Achievements in all fields of engineering and fabrication methods have led towards optimization and integration of multiple sensing devices into a concise system. These advances have caused significant innovation in various commercial, industrial, and research efforts. Integrations of subsystems have important applications for sensor systems in particular. The need for reporting and real time awareness of a device’s condition and surroundings have led to sensor systems being implemented in a wide variety of fields. From environmental sensors for agriculture, to object characterization and biomedical sensing, the application for sensor systems has impacted all modern facets of innovation. With these innovations, …

Detecting Suicide Risk From Wristworn Activity Tracker Data Using Machine Learning Approaches, Pallavi Atluri

Electrical Engineering Theses

Suicide is a prevalent cause of death worldwide and depression is a primary concern of many suicidal acts. It is possible that an individual during depression never has any suicidal thoughts at all. On the other hand, some individuals in stable condition with no apparent symptoms of depression feel urges to commit suicide (suicidal ideation). Many such individuals never let anyone know what they are feeling or planning. Suicidal ideation considered an important precursor to suicidal acts.

Detecting the suicide risk in individuals with mood disorders is a major challenge. The current clinical practice to assess suicide risk in these …

Experimental And Computational Studies Of Cortical Neural Network Properties Through Signal Processing, Wesley Patrick Clawson

Graduate Theses and Dissertations

Previous studies, both theoretical and experimental, of network level dynamics in the cerebral cortex show evidence for a statistical phenomenon called criticality; a phenomenon originally studied in the context of phase transitions in physical systems and that is associated with favorable information processing in the context of the brain. The focus of this thesis is to expand upon past results with new experimentation and modeling to show a relationship between criticality and the ability to detect and discriminate sensory input. A line of theoretical work predicts maximal sensory discrimination as a functional benefit of criticality, which can then be characterized …

Application Of Signal Advance Technology To Electrophysiology, Chris M. Hymel

Dissertations and Theses (Open Access)

Medical instrumentation used in diagnosis and treatment relies on the accurate detection and processing of various physiological events and signals. While signal detection technology has improved greatly in recent years, there remain inherent delays in signal detection/ processing. These delays may have significant negative clinical consequences during various pathophysiological events. Reducing or eliminating such delays would increase the ability to provide successful early intervention in certain disorders thereby increasing the efficacy of treatment.

In recent years, a physical phenomenon referred to as Negative Group Delay (NGD), demonstrated in simple electronic circuits, has been shown to temporally advance the detection of …

Signal Processing Methodologies For An Acoustic Fetal Heart Rate Monitor, Robert A. Pretlow Iii

Electrical & Computer Engineering Theses & Dissertations

Research and development is presented of real time signal processing methodologies for the detection of fetal heart tones within a noise-contaminated signal from a passive acoustic sensor. A linear predictor algorithm is utilized for detection of the heart tone event and additional processing derives heart rate. The linear predictor is adaptively "trained" in a least mean square error sense on generic fetal heart tones recorded from patients. A real time monitor system is described which outputs to a strip chart recorder for plotting the time history of the fetal heart rate. The system is validated in the context of the …