Jonathan Zia

Jonathan Zia
Georgia Institute of Technology | GT · School of Electrical & Computer Engineering

Doctor of Philosophy

About

16
Publications
2,012
Reads
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94
Citations
Additional affiliations
August 2018 - May 2020
Georgia Institute of Technology
Position
  • Research Assistant
November 2013 - May 2016
Arizona State University
Position
  • Student
Education
August 2018 - May 2020
Georgia Institute of Technology
Field of study
  • Electrical Engineering
July 2016 - May 2022
Emory University
Field of study
  • Medicine
August 2012 - May 2016
Arizona State University
Field of study
  • Electrical Engineering

Publications

Publications (16)
Article
Full-text available
This paper presents a novel computational algorithm to estimate blood volume decompensation state based on machine learning (ML) analysis of multi-modal wearable-compatible physiological signals. To the best of our knowledge, our algorithm may be the first of its kind which can not only discriminate normovolemia from hypovolemia but also classify h...
Article
Objective: Wearable systems that enable continuous non-invasive monitoring of hemodynamic parameters can aid in cardiac health evaluation in non-hospital settings. The seismocardiogram (SCG) is a non-invasively acquired cardiovascular biosignal for which timings of fiducial points, like aortic valve opening (AO) and aortic valve closing (AC), can...
Article
Full-text available
Background and objective Dynamic muscle fascicle length measurements through B-mode ultrasound have become popular for the non-invasive physiological insights they provide regarding musculoskeletal structure-function. However, current practices typically require time consuming post-processing to track muscle length changes from B-mode images. A rea...
Article
Hypovolemia remains the leading cause of preventable death in trauma cases. Recent research has demonstrated that using noninvasive continuous waveforms rather than traditional vital signs improves accuracy in early detection of hypovolemia progression to assist in triage and resuscitation efforts. In this work, random forest models trained on diff...
Preprint
Full-text available
Background and objective: Dynamic muscle fascicle length measurements through B-mode ultrasound have become popular for the non-invasive physiological insights they provide regarding musculoskeletal structure-function. However, current practices typically require time consuming post-processing to track muscle length changes from B-mode images. A re...
Article
Full-text available
In this paper, we quantify the joint acoustic emissions (JAEs) from the knees of children with juvenile idiopathic arthritis (JIA) and support their use as a novel biomarker of the disease. JIA is the most common rheumatic disease of childhood; it has a highly variable presentation, and few reliable biomarkers which makes diagnosis and personalizat...
Article
Full-text available
Objective: Local oscillation of the chest wall in response to events during the cardiac cycle may be captured using a sensing modality called seismocardiography (SCG), which is commonly used to infer cardiac time intervals (CTIs) such as the pre-ejection period (PEP). An important factor impeding the ubiquitous application of SCG for cardiac monit...
Article
Full-text available
As the leading cause of trauma-related mortality, blood loss due to hemorrhage is notoriously difficult to triage and manage. To enable timely and appropriate care for patients with trauma, this work elucidates the externally measurable physiological features of exsanguination, which were used to develop a globalized model for assessing blood volum...
Conference Paper
Full-text available
Pulse transit time (PTT) is a hemodynamic indicator that may be obtained non-invasively using photoplethysmogram (PPG) signals for continuous blood pressure (BP) monitoring. Among the most promising applications of this technology are military and civilian trauma cases, where reduced blood volume due to hemorrhage, or absolute hypovolemia, is the l...
Conference Paper
Full-text available
Captured with a chest-mounted sensor, the seismocardiogram (SCG) is a useful signal for assessing cardiomechanical function. However, the reliability of information obtained from this signal often depends upon sensor location. This has important practical implications, as consistent placement is not guaranteed in at-home and other uncontrolled sett...
Article
Full-text available
The seismocardiogram (SCG) measures the movement of the chest wall in response to underlying cardiovascular events. Though this signal contains clinically-relevant information, its morphology is both patient-specific and highly transient. In light of recent work suggesting the existence of population-level patterns in SCG signals, the objective of...
Article
Full-text available
The seismocardiogram (SCG) is a noninvasively-obtained cardiovascular bio-signal that has gained traction in recent years, however is limited by its susceptibility to noise and motion artifacts. Because of this, signal quality must be assured before data is used to inform clinical care. Common methods of signal quality assurance include signal clas...
Conference Paper
With the appropriate mathematical models, data from wearable devices can be used to help Parkinson's patients live safer and more independent lives. Inspired by this idea, the purpose of this study was to determine the viability of neural networks in predicting Freezing of Gait (FoG), a symptom of Parkinson's disease in which the patient's legs are...
Conference Paper
At-home exercise programs have met limited success in rehabilitation and training. A primary cause for this is the lack of a trainer’s presence for feedback and guidance in the home. To create such an environment, we have developed a model for the representation of motor learning tasks and training protocols. We designed a toolkit based on this mod...
Conference Paper
Conditions like Parkinson’s disease (PD) remain largely a mystery in the way that they affect individuals even under today’s modern medical practices. One of the main secondary effects associated with PD can be seen in issues with the individual’s gait and is referred to as Freezing of Gait (FoG). The symptom often responds poorly and sometimes par...

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Projects

Projects (3)
Archived project
Applying ubiquitous computing to adverse event prediction in Parkinson's disease as well as physical rehabilitation neuromuscular disease.
Project
Enabling estimation of blood volume status via non-invasive wearable monitoring systems for triage and management of trauma injury.
Project
Enabling robust, high-level cardiovascular monitoring via non-invasive and unobtrusive cardiomechanical biosignals.