Wearable Sensing

Watch with data visuals

Background

BrilliAnt is building a smartwatch app and a companion app to monitor and analyze stroke patient exercise. We plan to create a set of unique features to stimulate patient motivation to exercise and know their projected recovery timeline and current progress. Exercise quality is of critical importance in understanding and evolving the recovery process, and we hope to connect patients to their physical trainers on a daily basis, only digitally. Stroke patients need to feel encouraged and have a clear sense of their body movements during the long-term recovery phase. Signal processing and/or machine learning are the main elements used to create features and analyze patient data.

Goals and Objectives

  • Create a motivating and insightful platform for both patients and doctors to monitor and assess the recovery process for stroke patients.
  • Encourage consistent exercise and maintain patient motivation levels to the highest degree possible.
  • Analyze the traits that signify a quality exercise to better understand recovery success.
  • Ensure patients understand how and why they are doing exercises.
  • Develop both a smartwatch app and a smartphone app that work together to provide analytics based on the hardware from the watch's sensors by the end of the 2020-2021 academic year.

Hardware/Software

  • Fitbit Versa 3 with any compatible smartphone.
  • Android companion, iOS once complete.

Team Contact(s)

Project Manager: Nicholas Gurnard - ngurnard@uci.edu

Movement Quality Lead: Colin Nisbet - cnisbet@uci.edu

User Interface Lead: Xianling Yan - xianliny@uci.edu

Motivation Lead: Zachary Montoya - zjmontoy@uci.edu

Exercise Lead: Philip Park - philipsp@uci.edu

Project Advisor

Professor Reinkensmeyer - dreinken@uci.edu

Documentation

Link to Google Drive found here

Link to GitHub can be found here

Project status: 
Active
Department: 
MAE
Term: 
Fall
Academic year: 
2020-2021