Stanford Assistive Robotics and Manipulation Laboratory (ARMLab)

Trajectory and Sway Prediction for Fall Prevention

Research Goals:

  • “Develop a wearable sensor that can predict a person’s path and their stability over the expected path, alerting them if there is a significant possibility they may fall or become unstable” (Project Overview)
  • Led by Monroe Kennedy III (PI) and Ken Wang (PhD researcher) in the ARMLab

My Role:

  • Selected to participate in the Department of Mechanical Engineering 2023 Stanford Undergraduate Research Institute (SURI) as 1/30 undegraduate students for a 10 week research internship
  • Continuing to work in the ARMLab during the school year!

My Work:

  • Developed an iOS application in Swift (programming language) that leverages the LiDAR sensor in iPhones to collect environment data and generate a depth panorama
  • Application demo (below) shows the generation of the depth panorama in real time as a person walks down a hallway. The FPS on the screen needs to be multiplied by the number of GPUs (6 for the iPhone 12 Pro that the testing was conducted on)
  • The depth panorama is used as input to a VAE/LSTM trajectory and sway prediction model, which will eventually be deployed directly on the phone
  • Currently working on deploying the PyTorch model in the iPhone and designing an ergonomic/aesthetically pleasing phone harness

Research Poster

Research Presentations:

  • SURI Poster Session, August 2023: Presented summer research progress to Stanford mechanical engineering labs and the SURI cohort
  • Innovation and Discovery Expo, October 2023: Presented to biosciences, engineering, and medical researchers as part of the ARMLab demonstrational booth. The expo was hosted by Stanford Bio-X and Wu Tsai Human Performance Alliance.