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Context classification during blood pressure self-measurement using the sensor seat and the audio classification device

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

Blood pressure self-measurement (BPSM) requires the patient to follow a range of recommendations. Patients must remain silent during measurements, be seated correctly with back support and legs uncrossed, and must have rested at least 5 minutes prior to taking the measurement. Current blood pressure (BP) devices cannot verify whether the patient has followed these recommendations or not. As a result, the data quality of BP measurements could be biased. We present a proof-of-concept demonstration prototype that uses audio context classification for detecting speech during the measurement process, as well as a sensor seat for measuring patient posture and activity before and during the BPSM process.
Original languageEnglish
Title of host publicationThe 6th International Conference on Pervasive Computing Technologies for Healthcare and Workshops
Number of pages2
PublisherICST, The Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
Publication year2012
Pages201 - 202
ISBN (print)978-1-4673-1483-1
ISBN (Electronic)978-1-936968-43-5
Publication statusPublished - 2012
EventInternational Conference on Pervasive Computing Technologies for Healthcare - San Diego, United States
Duration: 21 May 201224 May 2012
Conference number: 6


ConferenceInternational Conference on Pervasive Computing Technologies for Healthcare
LandUnited States
BySan Diego

    Research areas

  • blood pressure self-measurement , context classification, data quality, pervasive healthcare

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