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Efficient upper limb position estimation based on angular displacement sensors for wearable devices

Authors :
Ministerio de Ciencia, Innovación y Universidades (España)
Contreras-González, Aldo-Francisco [0000-0003-0627-1832]
Ferre, Manuel [0000-0003-0030-1551]
Sánchez-Urán, Miguel Ángel [0000-0001-6652-0090]
Sáez-Sáez, Francisco Javier [0000-0002-9750-8606]
Blaya Haro, Fernando [0000-0001-9151-9067]
Contreras-González, Aldo-Francisco
Ferre, Manuel
Sánchez-Urán, Miguel Ángel
Sáez-Sáez, Francisco Javier
Blaya Haro, Fernando
Ministerio de Ciencia, Innovación y Universidades (España)
Contreras-González, Aldo-Francisco [0000-0003-0627-1832]
Ferre, Manuel [0000-0003-0030-1551]
Sánchez-Urán, Miguel Ángel [0000-0001-6652-0090]
Sáez-Sáez, Francisco Javier [0000-0002-9750-8606]
Blaya Haro, Fernando [0000-0001-9151-9067]
Contreras-González, Aldo-Francisco
Ferre, Manuel
Sánchez-Urán, Miguel Ángel
Sáez-Sáez, Francisco Javier
Blaya Haro, Fernando
Publication Year :
2020

Abstract

Motion tracking techniques have been extensively studied in recent years. However, capturing movements of the upper limbs is a challenging task. This document presents the estimation of arm orientation and elbow and wrist position using wearable flexible sensors (WFSs). A study was developed to obtain the highest range of motion (ROM) of the shoulder with as few sensors as possible, and a method for estimating arm length and a calibration procedure was proposed. Performance was verified by comparing measurement of the shoulder joint angles obtained from commercial two-axis soft angular displacement sensors (sADS) from Bend Labs and from the ground truth system (GTS) OptiTrack. The global root-mean-square error (RMSE) for the shoulder angle is 2.93 degrees and 37.5 mm for the position estimation of the wrist in cyclical movements; this measure of RMSE was improved to 13.6 mm by implementing a gesture classifier.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1286564254
Document Type :
Electronic Resource