Published on in Vol 5, No 10 (2017): October

Fall Detection in Individuals With Lower Limb Amputations Using Mobile Phones: Machine Learning Enhances Robustness for Real-World Applications

Fall Detection in Individuals With Lower Limb Amputations Using Mobile Phones: Machine Learning Enhances Robustness for Real-World Applications

Fall Detection in Individuals With Lower Limb Amputations Using Mobile Phones: Machine Learning Enhances Robustness for Real-World Applications

Nicholas Shawen   1, 2 * , MS ;   Luca Lonini   1, 2, 3 * , PhD ;   Chaithanya Krishna Mummidisetty   1 , MS ;   Ilona Shparii   1, 2, 4 , MS ;   Mark V Albert   1, 2, 3, 4 , PhD ;   Konrad Kording   5, 6 , PhD ;   Arun Jayaraman   1, 2, 3, 7 , PT, PhD

1 Max Nader Lab for Rehabilitation Technologies and Outcomes Research, Shirley Ryan AbilityLab, Chicago, IL, United States

2 Center for Bionic Medicine, Shirley Ryan AbilityLab, Chicago, IL, United States

3 Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL, United States

4 Department of Computer Science, Loyola University Chicago, Chicago, IL, United States

5 Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, United States

6 Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, United States

7 Department of Physical Therapy and Human Movement Sciences, Northwestern University, Chicago, IL, United States

*these authors contributed equally

Corresponding Author:

  • Luca Lonini, PhD
  • Max Nader Lab for Rehabilitation Technologies and Outcomes Research
  • Shirley Ryan AbilityLab
  • 355 E Erie St
  • Suite #11-1101
  • Chicago, IL, 60611
  • United States
  • Phone: 1 312-238-1619
  • Email: llonini@ricres.org