Title
Influence of motion artifacts on a smart garment for monitoring respiratory rate
Abstract
Wearable devices are gaining large acceptance in the continuous monitoring of vital signs. Among others, respiratory rate (f <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</sub> ) can be used to detect physiological abnormalities and health status changes.The purpose of this work was to investigate how the output of a smart garment used for respiratory monitoring is influenced by walking and running. This garment consists of three bands, each one embeds two piezoresistive elements sensitive to strain.Experimental trials were carried out on a volunteer who worn the three bands at the level of upper thorax, inferior thorax and abdomen during three different activities (i.e., static pose, walking and running). A treadmill was used to set specific speeds (i.e., from 1.6 km·h <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> to 8.8 km·h <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> ). The f <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</sub> values estimated by the proposed garment were compared to the ones monitored by a reference system (i.e., a flowmeter).The analysis in the frequency-domain demonstrated differences up to 3 bpm between the average f <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</sub> estimated by the two systems. The mean absolute error (MAE) was used to investigate the performances of the garment against the reference device in estimating the instantaneous f <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</sub> . MAE increased with speed (it reached 1.8 bpm during running). Bland-Altman analysis showed a bias of -0.02±2.02 bpm when all the data of walking and running were considered.The garment based on 6 sensing elements provides good performances for estimating both average and instantaneous f <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</sub> values during activities of walking and running.
Year
DOI
Venue
2019
10.1109/MeMeA.2019.8802226
2019 IEEE International Symposium on Medical Measurements and Applications (MeMeA)
Keywords
Field
DocType
smart garment,textile,respiratory rate,wearable,motion artifacts
Simulation,Computer science,Wearable computer,Mean absolute error,Respiratory rate,Continuous monitoring,Respiratory monitoring,Treadmill,Wearable technology
Conference
ISBN
Citations 
PageRank 
978-1-5386-8429-0
0
0.34
References 
Authors
3
15