Modeling ADLs with Timed HMMs: Conclusion

So here is what I think is reasonable to conclude from this data. Nothing earth shattering, but now there is data to support it:

1. Activity durations are not well characterized by exponential distributions. One might model them differently and possibly give an inference engine more accuracy as gaussian, gamma or poisson distributions
2. The HMM model is sufficient to recognize activities well if the objects involved do not overlap. When the objects involved overlap, the HMMs start to fail. Particularly when you want the system to segment the activities, which is a reasonable expectation.

So I think that the next step is to actually a step backwards in terms of modeling. I want to see how well a purely event driven version of this model does in comparison. That means that there are no "null" observations.