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In this paper, a tool to assess a person's fall risk with the Nintendo Wii Balance Board based on Center of Pressure (CoP) recordings is presented. Support Vector Machine and K-Nearest Neighbours classifiers are used to distinguish between people who experienced a fall in the past twelve months and those who have not. The classifiers are trained using data recorded from 39 people containing a mix of students and elderly. Validation is done using 10-fold cross-validation and the classifiers are also validated against additional data recorded from 12 elderly. A cross-validated average accuracy of 96.49% ± 4.02 is achieved with the SVM classifier with radial basis function kernel and 95.72% ± 1.48 is achieved with the KNN classifier with k = 4. Validation against the additional dataset of 12 elderly results in a maximum accuracy of 76.6% with the linear SVM.

Original publication

DOI

10.5220/0005208700750081

Type

Conference paper

Publication Date

01/01/2015

Pages

75 - 81