Article information
| Title | Intelligent system for identification of wheelchair user’s posture using machine learning techniques |
| Authors | Rosero-Montalvo, P.D. , Vivian López Batista , et al. , Peluffo-Ordóñez |
| Summary | This paper presents an intelligent system aimed at detecting a person's posture when sitting in a wheelchair. The main use of the proposed system is to warn an improper posture to prevent major health issues. A network of sensors is used to collect data that are analyzed through a scheme involving the following stages: selection of prototypes using condensed nearest neighborhood rule (CNN), data balancing with the Kennard-Stone algorithm, and reduction of dimensionality through principal component analysis. In doing so, acquired data can be both stored and processed into a micro controller. Finally, to carry out the posture classification over balanced, pre-processed data, and the K-nearest neighbors algorithm is used. It turns to be an intelligent system reaching a good tradeoff between the necessary amount of data and performance is accomplished. As a remarkable result, the amount of required data for … |
| Magazine name | IEEE Sensors Journal |
| Magazine number | 5 |
| Initial page | 1936 |
| End page | 1942 |
| Year | 2019 |
| Volume | 19 |
| ISSN | |
| Last impact factors | 3.076 (2018) |
| DOI | |
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