Digital Health Seedling Award
Digital Health Seedling awards are designed to promote innovative, high-risk research that advances the development, approval, adoption and use of innovative digital health tools, methods and approaches. Preference will be given to proposals that are innovative, interdisciplinary and have a high potential for significant impact. The award provides a maximum of $25,000 for a period of one year.
The principal investigators (PI) on all proposals must be a full-time faculty member at the University of Rochester. Each faculty member can participate in only one application in any capacity.
Applications may exploit a range of digital health approaches, tools and data, including topics in the areas of:
- Electronic medical records
- Sensors and mobile technologies
- Real World Data/Evidence
- Social media
- Other approaches and tools focused on advancing clinical research and addressing regulatory science needs
View the 2021 RFA for the Digital Health Seedling Awards.
CTSI Cost Sharing Information
CTSI Signoff Form
The following dates apply to the current solicitation:
- February 8, 2021 at 5:00 p.m. – Proposals must be received via electronic submission in REDCap.
- March 8, 2021 – Notification of Award will be made.
- July 1, 2021 – The earliest anticipated start date.
Measurement and relationship of physiological arousal and stress in children with autism spectrum disorder and caregivers
Suzannah Iadarola, Ph.D., Assistant Professor of Pediatrics at the University of Rochester Medical Center
Kenneth Shamlian, Psy.D., Assistant Professor of Pediatrics at the University of Rochester Medical Center
Samantha Daley, Ed.D., Assistant Professor of Counseling & Human Development at the University of Rochester Warner School of Education
Zhi Zheng, Ph.D., Assistant Professor of Biomedical Engineering at the Rochester Institute of Technology
Remote Longitudinal outcome assessments in amyotrophic lateral sclerosis: Laying the foundation to overcome diagnostic delays through remote digital technologies and machine learning
Peter Creigh, M.D., Assistant Professor of Neurology at the University of Rochester Medical Center