Autonomous collection of voiding events for sound uroflowmetries with machine learning

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dc.contributor.authorArjona Aguilera, Laura
dc.contributor.authorHernández López, Sergio
dc.contributor.authorNarayanswamy, Girish
dc.contributor.authorBahillo, Alfonso
dc.contributor.authorPatel, Shwetak
dc.date.accessioned2026-01-09T09:27:45Z
dc.date.available2026-01-09T09:27:45Z
dc.date.issued2025-02-04
dc.date.updated2026-01-09T09:27:45Z
dc.description.abstractWe present AutoFlow, a Raspberry Pi-based acoustic platform that uses machine learning to autonomously detect and record voiding events. Uroflowmetry, a noninvasive diagnostic test for urinary tract function. Current uroflowmetry tests are not suitable for continuous health monitoring in a nonclinical environment because they are often distressing, costly, and burdensome for the public. To address these limitations, we developed a low-cost platform easily integrated into daily home routines. Using an acoustic dataset of home bathroom sounds, we trained and evaluated five machine learning models. The Gradient Boost model on a Raspberry Pi Zero 2 W achieved 95.63% accuracy and 0.15-second inference time. AutoFlow aims to enhance personalized healthcare at home and in areas with limited specialist access.en
dc.description.sponsorshipLaura received funding as Juan de la Cierva Incorporation Fellow from the Spanish Ministry of Economy and Competitiveness, Spain (IJC2020-045901-I). This research has been supported by the Spanish Ministry of Science, Innovation and Universities under the AGINPLACE project, Spain (PID2023-146254OA-C44)en
dc.identifier.citationArjona, L., Hernández, S., Narayanswamy, G., Bahillo, A., & Patel, S. (2025). Autonomous collection of voiding events for sound uroflowmetries with machine learning. Biomedical Signal Processing and Control, 105. https://doi.org/10.1016/J.BSPC.2025.107556
dc.identifier.doi10.1016/J.BSPC.2025.107556
dc.identifier.eissn1746-8108
dc.identifier.issn1746-8094
dc.identifier.urihttps://hdl.handle.net/20.500.14454/4652
dc.language.isoeng
dc.publisherElsevier Ltd
dc.rights© 2025 The Authors
dc.subject.otherAcoustics
dc.subject.otherEdge computing
dc.subject.otherIoT
dc.subject.otherMachine learning
dc.subject.otherSound sensing
dc.subject.otherSound-based uroflowmetry
dc.titleAutonomous collection of voiding events for sound uroflowmetries with machine learningen
dc.typejournal article
dcterms.accessRightsopen access
oaire.citation.titleBiomedical Signal Processing and Control
oaire.citation.volume105
oaire.licenseConditionhttps://creativecommons.org/licenses/by-nc-nd/4.0/
oaire.versionVoR
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