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Safarishahrbijari et al evaluated the effectiveness of particle filtering subject to specifics of the configuration, such as frequency of data sampling and representation of behavior change in the form of an evolving contact rate for H1 N1 [3,5]. Oraji et al developed a system dynamics model for studying the tuberculosis transmission and applied particle filtering to estimate the latent state of the system, including many epidemiological quantities that are not directly measured.
JMIR Public Health Surveill 2019;5(2):e11615
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Applying Multivariate Segmentation Methods to Human Activity Recognition From Wearable Sensors’ Data
JMIR Mhealth Uhealth 2019;7(2):e11201
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