Smartphone-Enabled Hemodynamic Monitoring for Patients with Peripheral Artery Diseases
Project Title: Smartphone-Enabled Hemodynamic Monitoring for Patients with Peripheral Artery Diseases
Project Duration: May 23 – July 29, 2016 (10 weeks), 40 hours per week.
Project Mentors –
- Primary Faculty Mentor (Name, Affiliation, website and Email/Phone):
Zion Tsz Ho Tse, PhD, Assistant Prof of Medical Devices, College of Engineering, UGA
Email: firstname.lastname@example.org Tel: 706-542-4189
- Secondary Faculty Mentor (Name, Affiliation, website and Email/Phone):
Johnathan Murrow, MD, ARMC Cardiology, Assistant Prof of Medicine, GRU/UGA Medical Partnership
Email: email@example.com Tel: 706-475-1700
- Graduate Student/PostDoc mentors (Name, Affiliation and Email/Phone):
Kevin J. Wu, T. Stan Gregory, Medical Robotics Lab, College of Engineering, UGA
Email: firstname.lastname@example.org , email@example.com Tel: 706-542-4189
Project Description: Cardiovascular diseases are rising at an increased rate in the world. Aside from the commonly discussed afflictions of stroke and heart attack, Peripheral artery disease (PAD), the narrowing of arteries usually due to atherosclerosis, affects roughly 8 million people in the United States. Coupled with many cardiovascular diseases is type II diabetes, which leads to nerve damage and poor circulation. With the obesity epidemic, it is important to have preventative measures in place to prevent such circulation issues from becoming out of control. A valuable clinical metric for diagnosis and monitoring of these circulation diseases is regional blood flow.
Currently, blood flow is able to be quantified through many techniques: Ultrasound, Laser Doppler Flowmetry (LDF), multiple forms of Plethysmography, Contrast Computer Tomography (CT) and Magnetic Resonance Imaging (MRI) scans and Phase Contrast MRI (PCMR), to name a few. The majority of these methods requires an immobile device (Ultrasound, LDF, Plethysmography, MRI, CT) and thus are accessible to very few patients in need of the technology.
In recent studies conducted at the University of Georgia have shown voltages (VMHD) induced due to the interaction of the blood flow with the static magnetic field through the magnetohydrodynamic (MHD) effect are correlated with blood flow and other hemodynamic parameters. From this, a proof-of-concept device that induces the MHD effect in vessels through a static neodymium magnet and measures the induced VMHD through an electrophysiology monitoring sensor has been developed as a promising methodology for obtaining clinically useful hemodynamic information.
This project aims to further develop the prototype and convert it into a smartphone-based miniaturized sensor capable of non-invasively detecting alterations in regional blood volumes, allowing for an increased efficacy in patient monitoring during the progression of cardiovascular diseases.
REU Student Role and Responsibility: Over the course of the REU program, the student will assist in the optimizing of a portable, smartphone-enabled sensor for the monitoring of flow through observation of induced VMHD. The student’s project includes designing a physical vessel model to study the blood flow, optimizing the smartphone sensor, and using the measured data to quantify the relationship between VMHD and blood flow. The student will gain experience in electrical engineering design, rapid-prototyping (3-D printing), and clinical practice. Weekly meetings with mentors will aid in the guidance of the REU student.
Expected Outcome for REU student: The student’s work will contribute to the development of publications, aimed for submission as a conference paper in the International Society for Magnetic Resonance Imaging (ISMRM). Upon completion of the entire project, a comprehensive paper on the device will be submitted for journal publication. The device may also be in consideration for commercialization pending experimental outcomes.
 Centers for Diease Control and Prevention. (2014). Peripheral Arterial Disease (PAD) Fact Sheet. Available: http://www.cdc.gov/dhdsp/data_statistics/fact_sheets/fs_pad.htm
 Z. Tse, C. L. Dumoulin, G. D. Clifford, J. Schweitzer, L. Qin, J. Oster, et al., “A 1.5T MRI-conditional 12-lead electrocardiogram for MRI and intra-MR intervention,” Magn Reson Med, vol. 71, pp. 1336-1347, Apr 11 2013.