Activity Recognition with Time-Delay Emobeddings

Applications range from the detection of potential all times t 1,...T (m 1)τ. We refer to such a sequence problems (such as an elderly person who has fallen down as a model of the system. Note that these models are in their home) to general monitoring of disease progression nonparametric. Theoretically, under some smoothness assumptions (e.g. in Parkinson's disease), or simply tracking the amount (Takens, 1981), if m is big enough, and τ is not of exercise and physical activity that a person gets. Ideally, a multiple of the period of the system, such a model captures such activities should be monitored as precisely as possible, all the relevant dynamics. However, real data is noisy, but using cheap or easily available devices, and in a way that so nonparametric models of the same activity can have high does not interfere with daily life.