Toggle Main Menu Toggle Search

Open Access padlockePrints

Grasp Classification With Weft Knit Data Glove Using a Convolutional Neural Network

Lookup NU author(s): Emmanuel AYODELE, Dr Jane Scott

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


Abstract

Grasp classification using data gloves can enable therapists to monitor patients efficiently by providing concise information about the activities performed by these patients. Although, classical machine learning algorithms have been applied in grasp classification, they require manual feature extraction to achieve high accuracy. In contrast, convolutional neural networks (CNNs) have outperformed popular machine learning algorithms in several classification scenarios because of their ability to extract features automatically from raw data. However, they have not been implemented on grasp classification using a data glove. In this study, we apply a CNN in grasp classification using a piezoresistive textile data glove knitted from conductive yarn and an elastomeric yarn. The data glove was used to collect data from five participants who grasped thirty objects each following Schlesinger’s taxonomy. We investigate a CNN’s performance in two scenarios where the validation objects are known and unknown. Our results show that a simple CNN architecture outperformed k-nn, Gaussian SVM, and Decision Tree algorithms in both scenarios in terms of the classification accuracy.


Publication metadata

Author(s): Ayodele E, Bao T, Zaidi SAR, Hayajneh A, Scott J, Zhang Z-Q, McLernon D

Publication type: Article

Publication status: Published

Journal: IEEE Sensors Journal

Year: 2021

Volume: 21

Issue: 9

Pages: 10824-10833

Print publication date: 01/05/2021

Online publication date: 12/02/2021

Acceptance date: 05/02/2021

ISSN (print): 1530-437X

ISSN (electronic): 1558-1748

Publisher: IEEE

URL: https://doi.org/10.1109/JSEN.2021.3059028

DOI: 10.1109/JSEN.2021.3059028


Altmetrics

Altmetrics provided by Altmetric


Share