Efficient Upper Limb Position Estimation Based on Angular Displacement Sensors for Wearable Devices

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 obta...

Full description

Bibliographic Details
Main Authors: Aldo-Francisco Contreras-González, Manuel Ferre, Miguel Ángel Sánchez-Urán, Francisco Javier Sáez-Sáez, Fernando Blaya Haro
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/20/22/6452
_version_ 1797548166145376256
author Aldo-Francisco Contreras-González
Manuel Ferre
Miguel Ángel Sánchez-Urán
Francisco Javier Sáez-Sáez
Fernando Blaya Haro
author_facet Aldo-Francisco Contreras-González
Manuel Ferre
Miguel Ángel Sánchez-Urán
Francisco Javier Sáez-Sáez
Fernando Blaya Haro
author_sort Aldo-Francisco Contreras-González
collection DOAJ
description 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.
first_indexed 2024-03-10T14:54:40Z
format Article
id doaj.art-2a1445bd2c8146019cda81fa21f0693a
institution Directory Open Access Journal
issn 1424-8220
language English
last_indexed 2024-03-10T14:54:40Z
publishDate 2020-11-01
publisher MDPI AG
record_format Article
series Sensors
spelling doaj.art-2a1445bd2c8146019cda81fa21f0693a2023-11-20T20:39:21ZengMDPI AGSensors1424-82202020-11-012022645210.3390/s20226452Efficient Upper Limb Position Estimation Based on Angular Displacement Sensors for Wearable DevicesAldo-Francisco Contreras-González0Manuel Ferre1Miguel Ángel Sánchez-Urán2Francisco Javier Sáez-Sáez3Fernando Blaya Haro4Centro de Automática y Robótica (CAR) UPM-CSIC, ETS Ingenieros Industriales, Universidad Politécnica de Madrid, Calle de José Gutiérrez Abascal, 2, 28006 Madrid, SpainCentro de Automática y Robótica (CAR) UPM-CSIC, ETS Ingenieros Industriales, Universidad Politécnica de Madrid, Calle de José Gutiérrez Abascal, 2, 28006 Madrid, SpainCentro de Automática y Robótica (CAR) UPM-CSIC, ETS Ingenieros Industriales, Universidad Politécnica de Madrid, Calle de José Gutiérrez Abascal, 2, 28006 Madrid, SpainCentro de Automática y Robótica (CAR) UPM-CSIC, ETS Ingenieros Industriales, Universidad Politécnica de Madrid, Calle de José Gutiérrez Abascal, 2, 28006 Madrid, SpainETS Ingeniería y Diseño Industrial, Universidad Politécnica de Madrid, Ronda de Valencia, 3, 28012 Madrid, SpainMotion 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.https://www.mdpi.com/1424-8220/20/22/6452motion capturesoft angular displacement sensorsupper limbmotion trackingwearable sensors
spellingShingle Aldo-Francisco Contreras-González
Manuel Ferre
Miguel Ángel Sánchez-Urán
Francisco Javier Sáez-Sáez
Fernando Blaya Haro
Efficient Upper Limb Position Estimation Based on Angular Displacement Sensors for Wearable Devices
Sensors
motion capture
soft angular displacement sensors
upper limb
motion tracking
wearable sensors
title Efficient Upper Limb Position Estimation Based on Angular Displacement Sensors for Wearable Devices
title_full Efficient Upper Limb Position Estimation Based on Angular Displacement Sensors for Wearable Devices
title_fullStr Efficient Upper Limb Position Estimation Based on Angular Displacement Sensors for Wearable Devices
title_full_unstemmed Efficient Upper Limb Position Estimation Based on Angular Displacement Sensors for Wearable Devices
title_short Efficient Upper Limb Position Estimation Based on Angular Displacement Sensors for Wearable Devices
title_sort efficient upper limb position estimation based on angular displacement sensors for wearable devices
topic motion capture
soft angular displacement sensors
upper limb
motion tracking
wearable sensors
url https://www.mdpi.com/1424-8220/20/22/6452
work_keys_str_mv AT aldofranciscocontrerasgonzalez efficientupperlimbpositionestimationbasedonangulardisplacementsensorsforwearabledevices
AT manuelferre efficientupperlimbpositionestimationbasedonangulardisplacementsensorsforwearabledevices
AT miguelangelsanchezuran efficientupperlimbpositionestimationbasedonangulardisplacementsensorsforwearabledevices
AT franciscojaviersaezsaez efficientupperlimbpositionestimationbasedonangulardisplacementsensorsforwearabledevices
AT fernandoblayaharo efficientupperlimbpositionestimationbasedonangulardisplacementsensorsforwearabledevices