Community, GHC15

IOT and Emerging Tech: Gina Sprint Presentation

 

IOT and pres431s2-auth_pic_0EMERGING TECH -Gina Sprint

PHD STUDENT OF WASHINGTON STATE UNIVERSITY

Gina Sprint received a B.S. degree in computer science from Eastern Washington University, Cheney, WA, in 2012. Currently she is working toward the Ph.D. degree in computer science at Washington State University, Pullman, WA. She is a National Science Foundation Fellow in the IGERT Integrative Training Program in Health-Assistive Smart Environments at Washington State University. Her research interests include wearable computing, machine learning, technology applications for healthcare, and computer science education.

Today I attended the IOT and Emerging Tech session at the Grace Hopper Conference 2015. Gina Sprint spoke on wearable sensors for clinical outcome predictions. This is an extremely interesting topic. I also do research on mHealth so I am happy that I was able to attend her presentation.

Gina went over 3 aspects of wearable rehabilitation.

  • Why technology for rehabilitation:She explains there is objective data that can be used.
  • Why wear able sensors? : They are portable  and inexpensive
  • Why ecological environments : They are more representative of abilities and resembles discharge environments.

Her study is still on going. Most her participants are older.

I was most interested in how she computes her data. She explained that she collects measurements from the body . She spoke on time stamp alignment, orientation correction, band pass filtering- to prevent noise and clinical assessments of process.

 

Linear SVM,linear regression, random forest w/100 trees are some of the models she currently uses in her research.

Project Models

1)Patient is admitted – they have access to data. (M1)

2)Patient is recruited.(M2)

3)Combining data from session one and two. Sensor data and metrics improves the accuracy. (M3)

Model approaches

  • Cumulative model construction
  • Separate model construction

She states that their is obvious room for improvement of the accuracy of the models.

Gina expresses that her tool can be used in Industry. 7/7 people interviewed showed support for the project expressing that they would use it. She would like to create a mobile app for her system and advance the its technology. I think that Gina has a great project on her hands. Best of luck to Gina and her future  plans with this project. 🙂

If you would like to know more about her project contact her on  Linkedin .