Comparative Analysis of Probabilistic Models for Activity Recognition with an Instrumented Walker
This work addresses activity recognition for older adults using walkers, but it is incremental as it compares existing probabilistic models without introducing a new method.
The paper tackled the problem of automatically recognizing activities performed by users of rollating walkers to understand mobility patterns and fall risks, and it presented a comparative evaluation of several probabilistic models with data from control subjects and retirement community users.
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.