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...
Main Authors: | , , , , |
---|---|
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 |