Use of accelerometers for automatic regional chest movement recognition during tidal breathing in healthy subjects

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dc.contributor.authorDe la Fuente, Carlos
dc.contributor.authorWeinstein, Alejandro
dc.contributor.authorGuzman-Venegas, Rodrigo
dc.contributor.authorArenas, Juan
dc.contributor.authorCartes, Jorge
dc.contributor.authorSoto, Marcos
dc.contributor.authorCarpes, Felipe P.
dc.date.accessioned2025-01-23T21:13:10Z
dc.date.available2025-01-23T21:13:10Z
dc.date.issued2019
dc.description.abstractRecognition of breathing patterns helps clinicians to understand acute and chronic adaptations during exercise and pathological conditions. Wearable technologies combined with a proper data analysis provide a low cost option to monitor chest and abdominal wall movements. Here we set out to determine the feasibility of using accelerometry and machine learning to detect chest-abdominal wall movement patterns during tidal breathing. Furthermore, we determined the accelerometer positions included in the clusters, considering principal component domains. Eleven healthy participants (age: 21 +/- 0.2 y, BMI: 23.4 +/- 0.7 kg/m(2), FEV1: 4.1 +/- 0.3 L, VO2: 4.6 +/- 0.2 mL/min kg) were included in this cross-sectional study. Spirometry and ergospirometry assessments were performed with participants seated with 13 accelerometers placed over the thorax. Data collection lasted 10 min. Following signal pre-processing, principal components and clustering analyses were performed. The Euclidean distances in respect to centroids were compared between the clusters (p < 0.05), identifying two clusters (p < 0.001). The first cluster included sensors located at the right and left second rib midline, body of sternum, left fourth rib midline, right and left second thoracic vertebra midline, and fifth thoracic vertebra. The second cluster included sensors at the fourth right rib midline, right and left seventh ribs, abdomen at linea alba, and right and left tenth thoracic vertebra midline. Costal-superior and costal-abdominal patterns were also recognized. We conclude that accelerometers placed on the chest and abdominal wall permit the identification of two clusters of movements regarding respiration biomechanics.
dc.fuente.origenWOS
dc.identifier.doi10.1016/j.jelekin.2019.05.016
dc.identifier.eissn1873-5711
dc.identifier.issn1050-6411
dc.identifier.urihttps://doi.org/10.1016/j.jelekin.2019.05.016
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/100993
dc.identifier.wosidWOS:000470104000012
dc.language.isoen
dc.pagina.final112
dc.pagina.inicio105
dc.revistaJournal of electromyography and kinesiology
dc.rightsacceso restringido
dc.subjectChest wall
dc.subjectAbdominal wall
dc.subjectMachine learning
dc.subjectClustering
dc.subjectWearable technology
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleUse of accelerometers for automatic regional chest movement recognition during tidal breathing in healthy subjects
dc.typeartículo
dc.volumen47
sipa.indexWOS
sipa.trazabilidadWOS;2025-01-12
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