The Effect of Walking on the Estimation of Breathing Pattern Parameters using Wearable Bioimpedance
| Autor: | Dolores Blanco-Almazan, Willemijn Groenendaal, Francky Catthoor, Raimon Jane |
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| Přispěvatelé: | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial |
| Rok vydání: | 2022 |
| Předmět: |
Respiration - Measurement
Informàtica::Automàtica i control [Àrees temàtiques de la UPC] breathing Monitoring Bio-impedance Bioengineering Walking Breathing patterns electronic device Daily life activities Wearable Electronic Devices Parameter estimation Pulmonary diseases Humans Bioenginyeria Respiratory airflow Static measurements human procedures Clinical investigation Physiologic physiologic monitoring Monitoring Physiologic Percentage error algorithm Chronic obstructive pulmonary disease Respiratory rate Respiration Enginyeria biomèdica [Àrees temàtiques de la UPC] Wearable technology Active measurement Respiració -- Mesurament Algorithms |
| Zdroj: | 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). |
| DOI: | 10.1109/embc48229.2022.9871633 |
| Popis: | © 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. 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. 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. |
| Databáze: | OpenAIRE |
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