Dimensionality reduction for the quantitative evaluation of a smartphone-based Timed Up and Go test.
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Date
2012-01-18
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Abstract
The Timed Up and Go is a clinical test to assess mobility in the elderly and in Parkinson s disease Lately instrumented versions of the test are being considered where inertial sensors assess motion To improve the pervasiveness ease of use and cost we consider a smartphone s accelerometer as the measurement system Several parameters usually highly correlated can be computed from the signals recorded during the test To avoid redundancy and obtain the features that are most sensitive to the locomotor performance a dimensionality reduction was performed through principal component analysis PCA Forty nine healthy subjects of different ages were tested PCA was performed to extract new features principal components which are not redundant combinations of the original parameters and account for most of the data variability They can be useful for exploratory analysis and outlier detection Then a reduced set of the original parameters was selected through correlation analysis with the principal components This set could be recommended for studies based on healthy adults The proposed procedure could be used as a first level feature selection in classification studies i e healthy Parkinson s disease fallers non fallers and could allow in the future a complete system for movement analysis to be incorporated in a smartphone