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.
6th International Conference on Pervasive Computing Technologies for Healthcare and Workshops, 2012, p. 201-202
blood pressure self-measurement; context classification; data quality; pervasive healthcare
Main Research Area:
International Conference on Pervasive Computing Technologies for HealthcareInternational Conference on Pervasive Computing Technologies for Healthcare, 2012
ICST, The Institute for Computer Sciences, Social Informatics and Telecommunications Engineering