dc.contributor
Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial
dc.contributor.author
Blanco Almazán, María Dolores
dc.contributor.author
Groenendaal, Willemijn
dc.contributor.author
Catthoor, Francky
dc.contributor.author
Jané Campos, Raimon
dc.identifier
Blanco, M. [et al.]. The effect of walking on the estimation of breathing pattern parameters using wearable bioimpedance. A: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. "2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)". 2022, p. 3257-3260. ISBN 9781728127828. DOI 10.1109/EMBC48229.2022.9871633.
dc.identifier
9781728127828
dc.identifier
https://hdl.handle.net/2117/386331
dc.identifier
10.1109/EMBC48229.2022.9871633
dc.description.abstract
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.description.abstract
Wearable bioimpedance is a technique proposed to estimate breathing parameters such as respiratory rate (RR). However, its potential application lies in clinical investigation of daily-life activities like walking. This study evaluated the effect of the walking interference on the estimation of breathing parameters. 50 chronic obstructive pulmonary disease patients performed static and active measurements during thoracic bioimpedance acquisition. The static measurements included respiratory airflow for reference. The active measurements were used to estimate the walking interference from bioimpedance, and the obtained signals were added to static measurements for comparison with the reference. Afterward, we applied four different preprocessing methods to remove this walking interference and the resulting signals were used to detect the respiratory cycles and estimate breathing parameters (inspiratory time, expiratory time, duty cycle, and RR). The methods performed differently in terms of accuracy and mean average percentage error (MAPE), showing the need for specific preprocessing for active measurements. Furthermore, the MAPE values in the RR estimation were close to 3 % indicating that breathing parameters can be accurately estimated during walking. Accordingly, the present study reinforces the applicability of wearable bioimpedance for respiratory monitoring. Clinical relevance- This study exhibits the suitability of wearable bioimpedance to estimate accurate breathing param-eters during walking activities.
dc.description.abstract
This work was supported in part by the Universities and Research Secretariat from the Generalitat de Catalunya under Grant GRC 2017 SGR 01770 and, GrantFI-DGR, in part by the Agencia Estatal de Investigación from the Spanish Ministry of Science, Innovation and Universities and the European Regional Development Fund, under the Grant RTI 2018 098472B-I00, and in part by the CERCA Programme/Generalitat de Catalunya.
dc.description.abstract
Peer Reviewed
dc.description.abstract
Postprint (author's final draft)
dc.format
application/pdf
dc.relation
https://ieeexplore.ieee.org/document/9871633
dc.relation
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-098472-B-I00/ES/ECOSISTEMA DE SALUD INTELIGENTE (HERRAMIENTAS-APPS-DISPOSITIVOS) PARA LA MEDICINA PERSONALIZADA Y LA ASISTENCIA SANITARIA EN ENFERMEDADES RESPIRATORIAS Y TRASTORNOS DEL SUEÑO/
dc.subject
Àrees temàtiques de la UPC::Informàtica::Automàtica i control
dc.subject
Àrees temàtiques de la UPC::Enginyeria biomèdica
dc.subject
Respiration - Measurement
dc.subject
Bioengineering
dc.subject
Parameter estimation
dc.subject
Pulmonary diseases
dc.subject
Active measurement
dc.subject
Breathing patterns
dc.subject
Chronic obstructive pulmonary disease
dc.subject
Clinical investigation
dc.subject
Daily life activities
dc.subject
Percentage error
dc.subject
Respiratory airflow
dc.subject
Respiratory rate
dc.subject
Static measurements
dc.subject
Wearable technology
dc.subject
electronic device
dc.subject
physiologic monitoring
dc.subject
Wearable Electronic Devices
dc.subject
Respiració -- Mesurament
dc.title
The effect of walking on the estimation of breathing pattern parameters using wearable bioimpedance
dc.type
Conference report