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Device-ing Personalized Diet Interventions for Weight Management

The presentation will discuss technological advancements in weight management research and how these systems may be used by dietitians to provide weight management care.

Member Price $24.00

Nonmember Price $54.00

DPG/MIG Price $0.00


This product is free for Research DPG members.

This webinar was presented live on September 13, 2022.

There is growing interest in developing personalized nutrition approaches to combat obesity. These approaches include the use of digital technologies and mobile health systems that collect data on eating behaviors, individualized responses to food, and contextual factors – environmental, psychosocial, and biological – that influence these responses. This webinar will: 1) summarize the cutting-edge technology and systems that are being used in eating behavior research and 2) explore possible solutions of how we can merge technology and humanity to advance obesity-related research and care.

CPEU: 1.0
CPE Level: 2
Performance Indicators: 5.1.10, 10.5.12, 11.2.8

Learning Objectives

  1. Participants will be able to summarize the current evidence on technology-assisted tools used in personalized weight management interventions. 
  2. Participants will be able to explain how contextual factors (e.g., environmental, psychosocial) can be applied in just-in-time weight interventions using technology. 
  3. Participants will be able to summarize potential research opportunities for technology-assisted weight management care.


Annie W. Lin, PhD, RDN

Dr. Annie W. Lin is an Assistant Professor in Nutrition at Benedictine University. She completed a joint MS/RD program at Rush University and received a PhD degree in Human Nutrition at Cornell University. She was a Postdoctoral Fellow in the NCI-funded T32 Behavioral and Psychosocial Research Training Program in Cancer Prevention and Control at Northwestern University. She currently holds a dual appointment as Adjunct Assistant Professor of Preventive Medicine at Northwestern University.

Her research program focuses on using technology-assisted strategies to promote healthy dietary behaviors in the context of cancer prevention and treatment. She is currently leading several collaborations that investigate how to effectively facilitate conversations about health promotion between patients and clinicians via technology. She received internal and external grants supporting this research program and was recognized as an Emerging Leader in Nutrition Science finalist by the American Society of Nutrition in 2020. With the support her research assistants and collaborators, she hopes to facilitate successful translation of nutrition research into clinical practice.

Nabil Alshurafa, PhD, MS

Dr. Nabil Alshurafa is an Associate Professor of Preventive Medicine and of Computer Science at Northwestern University. He received his PhD in Computer Science at the University of California Los Angeles (UCLA) where he received several awards for his dissertation on advancing human behavior and health using technology. He currently directs the HABits Lab at Northwestern, which aims to bridge between computer science and behavioral science research. He also leads the Sensor Analytics program in the Institute for Augmented Intelligence in Medicine (I-AIM) at Northwestern.

His current research seeks to transform our understanding of health constructs by designing objective, verifiable wearable sensor measures to more effectively design interventions that improve lifestyle habits. He has received several government grants to develop and test privacy-conscious technology and analytics that advance our understanding of human behavior. His research has been recognized by the National Institute of Nursing Research with an Outstanding Poster Abstract Award, Army SBIR with both Phase-I and Phase-II award, and several ACM and IEEE peer-reviewed conferences and journals with a Distinguished Paper Award at ACM IMWUT; a Best Presentation Award at ACM IMWUT; a Best Poster Award at ACM IMWUT; and Best Paper Awards in IEEE Body Sensor Networks, EAI BODYNETS, The Obesity Society (TOS), and IEEE PerCom (Samsung Best Paper Award). With the support of his lab, he hopes to transform how we understand, detect, and predict factors that influence eating behavior.

Release Date: September 13, 2022


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