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Measurement Innovations: Integrating Machine Learning and Digital Technologies in Rehabilitation Task Force

 

 

 

Mission

To advance responsive and innovative use of machine learning and digital technologies in clinical research, focusing on improved research design and data analysis practices in rehabilitation.

 

Vision

To be a leading collaborative platform that sets global standards and drives innovation in using machine learning and digital technologies, transforming clinical research and practice in rehabilitation.

CO-CHAIRS

Andrew D. Delgado, PhD, MS

Andrew D. Delgado, PhD, MS

CO-CHAIR

Icahn School of Medicine at Mount Sinai

Zijian Huang, MS

Zijian Huang, MS

CO-CHAIR

PhD Candidate, Graduate Student Researcher
School of Health and Rehabilitation Sciences, University of Pittsburgh
 

Goals/Products

  • To grow membership.
  • To develop protocol and report standards using technological measurements (e.g., wearable devices) in rehabilitation
    • Task 1: A need analysis survey/focus group on what variable(s)/metrics the researchers would like to assess using technological measurements. (Estimated completion time: year 1)
    • Task 2: A technology literacy survey/focus group on the knowledge regarding the use of technological measurements. Understand what our fellow researchers already know and where they need assistance. (Estimated completion time: year 1)
    • Task 3: Write editorial/primer article(s) about Machine Learning and wearable devices. Explain why and how important these technological measurements are in rehabilitation medicine and call for action. (Estimated completion time: year 2)
    • Task 4: Develop abstract(s) for ACRM symposium/instructional course and publish paper(s) on this topic at Archives PM&R (Estimated completion time: abstract(s) for years 1 and 2, and paper(s) for year 2)
  • To develop “cheat sheets” (study design and data collection) for use in wearable devices and machine learning for investigators in study design. 
    • Task 1: Write a proposal to the PVA educational fund to create cheat sheets/infographics for guiding healthcare professionals and researchers to incorporate technological measurements into study design (Estimated completion time: Nov 2024)
    • Task 2: Develop infographics  (Estimated completion time: year 2)
  • To develop “cheat sheets” for (data report and analysis) for use in wearable devices and machine learning for investigators in reporting findings
    • Task 1: Write a proposal to the PVA educational fund to create cheat sheets/infographics for guiding healthcare professionals and researchers to properly report study results involving technological measurements (Estimated completion time: Nov 2024)
    • Task 2: Develop infographics  (Estimated completion time: year 2)