• Workshop Topic

    The workshop will focus on designing sensors, systems, and analytics to monitor a person’s metabolic health, detect events that are important for assessing metabolic health, and to design interventions for maintaining metabolic health and preventing chronic conditions arising from metabolic complications. The workshop will inform the audience about state-of-the-art research and future directions on end-to-end systems including sensor development, system deployment, data generation, and analytics to process and interpret findings. The workshop aims to cover the following topics:

    • Measurement: this refers to search on developing sensors and tools for measuring behavioral, physiological, and biological determinants of metabolic health such as diet, physical activity, stress, and microbiome.
    • Phenotyping: this refers to research on discovering and calculating biomarkers of metabolic health from multimodal wearable, environmental, and health data.
    • Intervention: this topic refers to effective approaches that promote initiation and enhance maintenance of interventions that improve metabolic health, as well as new ways to design interventions, and how to identify optimal personalized interventions for precision health.
    Workshop Schedule

    2:45 – 3:00 | Introduction from Chairs

    3:00 – 4:00 | Talks

    • List of Speakers (Mini-Talks)
      • Amir Rahmani (University of California Irvine): Exploring the Significance of Multimedia Food Logging and Personal Models in Food Computing
      • Lauren Lederrer (Duke University): TBD
      • Elena Idi and Francesco Prendin (Universita Degli Studi Di Padova): Detecting malfunctioning of CGM sensor and insulin pumps for safer T1D treatment
      • Hassan Ghasemzadeh (Arizona State University): Counterfactual Explanations for Simulating Behavioral Treatments
      • Bobak J Mortazavi (Texas A&M University): Multimodal Learning for Automated Nutrition Monitoring 

    4:00 – 4:15 | Break

    4:15 – 5:15 | Panel on Digital Twin for Metabolic Health

    • Moderator:
      • Hassan Ghasemzadeh (Arizona State University)
    • Panelists:
      • Amir Rahmani (University of California Irvine): Topic: Digital twin (or personal model) augmented LLMs for personalized food recommendations
      • Ali Roghanizad (Duke University): TBD
      • Giacomo Cappon (Universita Degli Studi Di Padova): Digital twin methods and decision support systems in diabetes therapy
      • Bobak J. Mortazavi (Texas A&M University): Automated and Personalized Nutrition Monitoring

    5:15 – 5:30 | Closing Remarks

  • For more information, please visit the workshop website:

    Workshop Overview:

    Recent advancements in wearable robotics, including exoskeletons and prosthetics, offer transformative potential for rehabilitation and mobility assistance. However, the optimal benefit hinges on the devices’ ergonomic design, intuitiveness, and integration with human physiology and cognition—a domain where NeuroDesign plays an important role. NeuroDesign is an interdisciplinary approach that integrates neuroscience insights into the design of products, systems, or experiences to optimize human’s perception and interaction. Our workshop, “NeuroWearX: Amplifying Digital Healthcare with Neurodesign in Wearable Robotics,” explores the integration of NeuroDesign methodologies in wearable robotics to enhance digital healthcare. We will bring together domain experts to discuss critical aspects spanning the following spectrum:

    • Personalized Treatment
    • Improved Patient Experience
    • Increased Accessibility and Affordability of the Devices
    • Enhanced Rehabilitation
    • Prevention and Early Intervention


    • Sunil K Agrawal, Columbia University
    • Hermano Igo Krebs, Massachusetts Institute of Technology
    • Nitin Sharma, North Carolina State University
    • Eric Leuthardt, Washington University in St. Louis

    Organizing Committee: 

    • Ker-Jiun Wang, University of Pittsburgh
    • Ramana Vinjamuri, University of Maryland, Baltimore County
    • Zhi-Hong Mao, University of Pittsburgh
    • Maryam Alimardani, Tilburg University
    • Midori Sugaya, Shibaura Institute of Technology