Wheelchair posture classification based on POF pressure sensors and machine learning algorithms

被引：6

作者：

Gonzalez-Cely, A. X. ^{[1
]}

Bastos-Filho, T. ^{[1
]}

Diaz, Camilo A. R. ^{[1
]}

机构：

[1] Univ Fed Espirito Santo, Grad Program Elect Engn, Av Fernando Ferrari 514, Vitoria, ES, Brazil

来源：

2022 IEEE LATIN AMERICAN ELECTRON DEVICES CONFERENCE (LAEDC) | 2022年

关键词：

POF pressure sensor; wheelchair; posture classification; machine learning algorithms;

D O I：

10.1109/LAEDC54796.2022.9907773

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

A proof of concept of a wheelchair posture monitoring based on Polymer Optical Fiber (POF) pressure array system using machine learning algorithms was made. Twelve lines of sensors were implemented in a wheelchair and ten postures were analyzed using classification algorithms. The classification system used a CAR filter and a SVM algorithm leading to an accuracy of 99.52%, and a cross validation of 98.83%. The best cross validation was 99.16% using a kNN algorithm.

引用

页数：4

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