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Minimize RSR Award Detail

Research Spending & Results

Award Detail

Awardee:RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK, THE
Doing Business As Name:SUNY at Albany
PD/PI:
  • Ricky Leung
  • (518) 402-6512
  • rleung@albany.edu
Award Date:01/10/2020
Estimated Total Award Amount: $ 50,000
Funds Obligated to Date: $ 50,000
  • FY 2020=$50,000
Start Date:01/15/2020
End Date:06/30/2021
Transaction Type:Grant
Agency:NSF
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.041
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:I-Corps: Developing a data analytics platform for pain management and alternative treatment
Federal Award ID Number:2011302
DUNS ID:152652822
Parent DUNS ID:020657151
Program:I-Corps
Program Officer:
  • Ruth Shuman
  • (703) 292-2160
  • rshuman@nsf.gov

Awardee Location

Street:1400 WASHINGTON AVE MSC 100A
City:Albany
State:NY
ZIP:12222-0100
County:Albany
Country:US
Awardee Cong. District:20

Primary Place of Performance

Organization Name:The Research Foundation for the SUNY, UAlbany
Street:1400 Washington Ave., MSC100
City:Albany
State:NY
ZIP:12222-0100
County:Albany
Country:US
Cong. District:20

Abstract at Time of Award

The broader impact of this I-Corps project is to provide insight to support pain management with minimal intervention. The envisioned system uses off-the-shelf mobile and wearable devices already available as consumer devices to minimize costs to the consumer, recording pain episodes, sleep patterns, and associated lifestyle factors impacting pain management. Furthermore, it will enable communication between patients and health care providers so they can jointly identify effective treatment regimens to manage pain and reduce health care costs. It is anticipated that this will have particular value for shoulder, back and other musculoskeletal pains. This I-Corps project draws on artificial intelligence (AI) and deep learning algorithms to help patients record their pain episodes, sleep and exercise patterns, and related activities. The research on which this project is based has shown that mobile and wearable devices are able to utilize sensors, including accelerometers, high-definition cameras, gyroscopes, thermometers and other environmental sensors, to collect diverse data and produce intelligent deep learning algorithms. Additional studies suggest that healthy lifestyles and alternative treatments impact reduced use of prescription drugs. The technology in this project provides an infrastructure for patients to collect their own data securely. Patients and health providers can access these data through an internet-based platform to analyze factors such as: 1) patient sleep patterns, exercises and similar activities; 2) frequency and severity of pain episodes; and 3) treatment effectiveness. The technology will serve as a technological infrastructure for patients to manage chronic pain intelligently. It also will support the development of related smart and connected health applications. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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