Research Article
Context Classification during Blood Pressure Self-Measurement using the Sensor Seat and the Audio Classification Device
@INPROCEEDINGS{10.4108/icst.pervasivehealth.2012.248700, author={Stefan Wagner and Niels Rasmussen and Peter Ahrendt and Thomas Toftegaard and Olav Bertelsen}, title={Context Classification during Blood Pressure Self-Measurement using the Sensor Seat and the Audio Classification Device}, proceedings={6th International Conference on Pervasive Computing Technologies for Healthcare}, publisher={IEEE}, proceedings_a={PERVASIVEHEALTH}, year={2012}, month={7}, keywords={blood pressure self-measurement context classification pervasive healthcare data quality}, doi={10.4108/icst.pervasivehealth.2012.248700} }- Stefan Wagner
Niels Rasmussen
Peter Ahrendt
Thomas Toftegaard
Olav Bertelsen
Year: 2012
Context Classification during Blood Pressure Self-Measurement using the Sensor Seat and the Audio Classification Device
PERVASIVEHEALTH
ICST
DOI: 10.4108/icst.pervasivehealth.2012.248700
Abstract
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.
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