• Skip to main content
  • Skip to footer

University of Tennessee Research Foundation

Technology Transfer & Licensing

  • About
    • Our Mission
    • Foundation History & Details
    • Student Opportunities
    • Frequently Asked Questions
    • UTRF Staff
    • Projects & Partners
  • Technologies
    • Available Technologies
    • Express Licensing
  • For Innovators
    • UT Research Foundation Accelerate Fund
    • Resources
    • IDEA Tutorial & Manuals
    • Technology Transfer Process
    • Business Incubator
    • UTRF Technology Maturation Grant Funding
  • Industry
    • Industry Partnerships
    • Agreement Examples
  • Media
    • News
    • Newsletters
    • Tech Talks
    • Annual Reports
  • Contact

Wearable Sensors for Optimizing Medication Regimens in Parkinson's (PD) Treatment​

The Problem

Effectively managing Parkinson's disease (along with other chronic diseases) is a formidable healthcare challenge, especially considering the considerable heterogeneity of symptoms and treatment responses among patients. Optimization of medication administration, especially in Levodopa (L-dopa) dosage, holds great promise in effectively managing Parkinson's, but such administration must be carefully prescribed due to the short half-life of L-dopa and the competing effects of bradykinesia and dyskinesia. ​

The Solution

Dr. Khojandi and Dr. Ramdhani have developed a data-driven framework for implementation in wearable sensors and technology which makes use of the fact that accelerometers can accurately estimate Parkinson's symptoms. A statistical model of PD symptom progression was created to train and evaluate personalized medication strategies of L-dopa therapy.​

Overview of the developed reinforcement learning (RL) framework.

 

Overview of the methodology underlying the proposed framework.

Benefits

Benefit
Utilizes wearable tech as a prescriptive rather than descriptive healthcare tool.​
Tested using real PD patient data acquired from wearable movement trackers over two separate six-day periods.​
Wearable medication regimen shows statistical patient improvements over physician prescribed regimens (20.1% clinically significant improvement versus 13.6% improvement respectively).​

More Information

  • Kusum Rathore, Ph.D.
  • UTRF Vice President
  • 865-974-1882 | krathore@tennessee.edu
  • UTRF Reference ID: 21170
  • Patent Status:
Doctor physician hand on happy elderly senior patient to comfort in hospital examination room or hospice nursing home or wellbeing county.

Innovators

Anahita Khojandi​

Associate Professor and Director of the RME Program​, Department of Industrial and Systems Engineering, Tickle College of Engineering, UT Knoxville

Dr. Khojandi received her PhD in Industrial Engineering from the University of Pittsburgh. Her research interests include machine and reinforcement learning, environmental engineering and sustainability, and intelligent transportation systems. Her research has been supported by the National Science Foundation (NSF), National Institutes of Health (NIH), and Department of Energy (DOE).​

Read more about Anahita Khojandi​

Ritesh Ramdhani

Deep Brain Stimulation Program Director, Northwell Health​

Dr. Ramdhani is the director of the Deep Brain Stimulation Program and the Associate Director of the Parkinson's and Movement Disorders Division at Northwell Health. Dr. Ramdhani obtained his medical degree from the Icahn School of Medicine at Mount Sinai, where he also trained in neurology and served as chief resident. He is interested in the study of wearable sensor technology to improve therapeutics for movement disorders.​

Read more about Ritesh Ramdhani

Footer

  • Facebook
  • LinkedIn
  • Twitter
  • YouTube

Multi Campus Office

400 W. Summit Hill Drive
UT Tower 961A
Knoxville, TN 37902
Phone: 865-974-1882

Health Science Center

UT Health Science Center
910 Madison Avenue, Suite 827
Memphis, TN 38163
Phone: 901-448-7827


Copyright © 2025


University of Tennessee Campuses & Institutes

  • UT Knoxville
  • UT Knoxville
  • UT Chattanooga
  • UT Chattanooga
  • UT Southern
  • UT Southern
  • UT Martin
  • UT Martin
  • UT Health Science Center
  • UT Health Science Center
  • UT Institute of Agriculture
  • UT Institute of Agriculture
  • UT Institute for Public Service
  • UT Institute for Public Service
  • UT Alumni Association
  • UT Alumni Association
  • UT Foundation
  • UT Foundation
  • UT Research Park
  • UT Research Park
X