- author = "James Alexander Hughes and Joseph {Alexander Brown} and Adil Mehmood Khan and Asad {Masood Khattak} and Mark Daley",
- booktitle = "2019 IEEE Congress on Evolutionary Computation (CEC)",
- title = "User and Task Identification of Smartwatch Data with an Ensemble of Nonlinear Symbolic Models",
- year = "2019",
- pages = "2506--2513",
- abstract = "Smart devices are becoming more universally adopted and can be used to track and model user activity and monitor for abnormalities. Deviations from what is expected may indicate that a fall is imminent or that an injury has been sustained. Healthcare practitioners can use descriptive models of human kinematics as a tool to monitor patient recovery. This work extends previous work which generated descriptive nonlinear symbolic models of human kinematics with genetic programming. Previously, linear models were developed and compared to the nonlinear models. Although the linear models fit the data well, they were significantly worse than the nonlinear models. In this phase of the project, ensembles of nonlinear models were created to more accurately fit and classify data. Different model selection strategies for the ensembles were investigated. As one would expect, ensembles of models were significantly better than a single model classifier. It was also observed that, although more models in the ensemble yielded better results, only 2 models were required to obtain significantly better results. It was also observed that a random model selection strategy for the ensembles produced competitive results when compared to a more rigorous model selection strategy.",
- keywords = "genetic algorithms, genetic programming",
-
DOI = "
doi:10.1109/CEC.2019.8790249",
- month = jun,
-
notes = "Mathematics, Statistics, and Computer Science, St.
Francis Xavier University, Antigonish, Nova Scotia,
Canada
Also known as \cite{8790249}",
