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Smartphone-Based Self-Diagnosis of Parkinson’s Disease

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Conference

2022 ASEE Gulf Southwest Annual Conference

Location

Prairie View, Texas

Publication Date

March 16, 2022

Start Date

March 16, 2022

End Date

March 18, 2022

Tagged Topic

Diversity

Page Count

6

DOI

10.18260/1-2--39206

Permanent URL

https://peer.asee.org/39206

Download Count

326

Paper Authors

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Jailyn Battle

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Ve’an Randall Jr

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Karl Duncan McKenzie

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I am a Virginia Commonwealth University student in his second-year, at the time of the publishing of this paper, majoring in Bio-medical Engineering.

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Jordan E Burton Norfolk Public Schools / Norfolk State University

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Jordan Burton Project Lead The Way Teacher at Maury High School in Norfolk, Virginia. 8 Years of teaching experience in various environments in Virginia, New York, and Washington D.C. received a Bachelor’s Degree in Occupational and Technical studies and Secondary Education from Old Dominion University.

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Monica Brown Granby High School Mathematics Teacher

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Taught Secondary Mathematics for 20 years.
Masters in Secondary Education from The College of New Jersey
BS in Electrical Engineering from Polytechnic Institute Bucharest (accredited in US)

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Bright S Tsevi Norfolk State University

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Sheryl Shaji

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Sacharia Albin Norfolk State University

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Dr. Sacharia Albin joined Norfolk State University in July 2011 as the Chair of the Engineering Department. He received his BS and MS degrees from the University of Kerala, and Ph.D. from the University of Poona, India. He was a design engineer in microelectronics at Hindustan Aeronautics, India for three years. He was awarded a Post-Doctoral Research Fellowship by the Science and Engineering Research Council at the University of Liverpool, UK. Dr. Albin conducted research on Si and GaAs electronic devices and semiconductor lasers at the research laboratories of GEC and ITT and published numerous articles in this field. He was a professor of Electrical and Computer Engineering at Dominion University. He has advised 14 PhD and 20 MS students. He received numerous awards: Doctoral Mentor Award 2010; Excellence in Teaching Award 2009; Most Inspiring Faculty Award 2008; Excellence in Research Award 2004; and Certificate of Recognition for Research - NASA, 1994. He is a Senior Member of the IEEE and a Member of the Electrochemical Society.

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Makarand Deo Norfolk State University

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Dr. Makarand Deo is an Associate Professor in the Department of Engineering at Norfolk State University. Dr. Deo has earned his PhD in Electrical Engineering from University of Calgary, Canada. His graduate and undergraduate degrees are from Indian Institute of Technology (IIT) Bombay and University of Pune, India, respectively. After PhD, Dr. Deo joined the reputed Center for Arrhythmia Research at the University of Michigan, Ann Arbor, MI, for his postdoctoral training followed by a research faculty position at the University of Toledo, OH. Dr. Deo's research interests are in computational modeling of bioelectrical systems and optics-based biosensing. Dr. Deo’s research has been funded by National Science Foundation, National Institutes of Health and American Heart Association.

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Abstract

Parkinson’s Disease (PD) is a degenerative nervous system disorder that affects the motor system progressively over a long period of time leading to shaking, body stiffness, and difficulty with walking, balance, and coordination. Over 60,000 people are diagnosed with PD every year in America alone. This number is expected to amount to 1.2million people living with PD by the year 2030. PD is an incurable disease, but it can be managed efficiently by medication, therapy, and or surgery if diagnosed early to help relieve symptoms and maintain a good quality of life. However, there is no reliable, easily accessible, and affordable testing procedure for the patients to self-administer for detecting early onset of PD. The main goal of this project was to develop a smartphone-based easy-to-use self-diagnostic tool to detect early stages of PD while creating awareness about its symptoms and the importance of seeking early intervention. This work uses a cross-platform mobile application development environment to develop an android and iOS compatible smartphone app. The app uses smartphone’s built-in hardware sensors such as accelerometer and gyroscope to measure and analyse the frequency of body tremors (4-6 Hz range), using Fast Fourier Transformations (FFT). The app also utilizes a specially designed spiral test to analyse the user’s tracing of an Archimedean spiral which is another indicator of deteriorating motor functions in PD. These two tests combined with the user information collected from a demographic questionnaire probing various risk factors of PD are used to estimate a likely occurrence of PD, suggesting the user to seek medical assistance. Our project exploits the ubiquitous smartphone technology to provide user-friendly and affordable means to self-monitor the symptoms of Parkinson’s disease and create a much-needed societal awareness about the disease.

Battle, J., & Randall, V., & McKenzie, K. D., & Burton, J. E., & Brown, M., & Tsevi, B. S., & Shaji, S., & Albin, S., & Deo, M. (2022, March), Smartphone-Based Self-Diagnosis of Parkinson’s Disease Paper presented at 2022 ASEE Gulf Southwest Annual Conference, Prairie View, Texas. 10.18260/1-2--39206

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