Comparative Analysis of Probabilistic Models for Activity Recognition
  with an Instrumented Walker
  Rollating walkers are popular mobility aids used by older adults to improve
balance control. There is a need to automatically recognize the activities
performed by walker users to better understand activity patterns, mobility
issues and the context in which falls are more likely to happen. We design and
compare several techniques to recognize walker related activities. A
comprehensive evaluation with control subjects and walker users from a
retirement community is presented.
